var textForPages = ["","","obalka a vstupy Current trends_23_Sestava 1  18.06.2019  9:55  Stránka 1                         Current Trends in Public Sector Research                  Proceedings of the 23 International Conference                                          rd                                                                                             MUNI                                                                        MUNI                   Press                                                                       ECON","obalka a vstupy Current trends_23_Sestava 1  18.06.2019  9:55  Stránka 2                         The conference is held under the patronage of                    The Governor of the South Moravian Region Bohumil Šimek                        and with financial support of the South Moravian Region.","obalka a vstupy Current trends_23_Sestava 1  18.06.2019  9:55  Stránka 3                           Current Trends                      in Public Sector                      Research                         Proceedings of the                    23 International Conference                        rd                             Brno, 24–25 January 2019                                                                    Masaryk University                                           Faculty of Economics and Administration                                           Department of Public Economics                                             Brno 2019","obalka a vstupy Current trends_23_Sestava 1  18.06.2019  9:55  Stránka 4                         Programme Committee                  Jiří Špalek (Head), Masaryk University, Brno (Czechia)                  Pavel Bachmann, University of Hradec Králové (Czechia)                  Beáta Mikušová Meričková, Matej Bel University, Banská Bystrica (Slovakia)                  Juraj Nemec, Matej Bel Univesity, Banská Bystrica (Slovakia)                  Romana Provazníková, University of Pardubice (Czechia)                  Lucie Sedmihradská, University of Economics, Prague (Czechia)                  Katarína Staroňová, Comenius University, Bratislava (Slovakia)                  Petr Tománek, VŠB-Technical University of Ostrava (Czechia)                  Jaroslav Vostatek, University of Finance and Administration, Prague (Czechia)                   Organizing Committee                  Petra Dvořáková (Head)                  Jana Biskupová                   Markéta Páleníková                   Reviewer                  Emília Beblavá                   Editor                  Petra Dvořáková                   Technical editor                  Petra Dvořáková                    Supported by Association of Public Economics                   Suggested citation                  AUTHOR, A. Title of the paper. In: Dvořáková, P. (ed.) Proceedings of the 23rd                  International Conference Current Trends in Public Sector Research 2019. Brno:                  Masaryk University, 2019. pp. xx-xx. ISSN 2336-1239. ISBN 978-80-210-9256-3                  (print), ISBN 978-80-210-9257-0 (online : pdf)                   The publisher assumes no responsibility for proofreading and editing of the                  contributions.                   All papers were reviewed by external reviewers and the Programme                  Committee.                      Copyright © 2019 Masarykova univerzita                  ISBN 978-80-210-9256-3                  ISBN 978-80-210-9257-0 (online : pdf)                  ISSN 2336-1239                  https://doi.org/10.5817/CZ.MUNI.P210-9257-2019                     All rights reserved. No part of this e-book may be reproduced or transmitted in any form or by any                  means  without  prior  written  permission  of  copyright  administrator  which  can be  contacted  at                  Masaryk University Press, Žerotínovo náměstí 9, 601 77 Brno.","CONTENTS                 PROLOGUE (ŠPALEK Jiří)..........................................................................     7                 AMOAKO Martha:               Bridging the Gap: Ghana's National Health Insurance Scheme and Its Impact on Under-Five               Healthcare..............................................................................................................................    9                ANDERSON Henry Junior; GYAMFI Solomon; STEJSKAL Jan:               Industrial Cooperation, Knowledge Sources and the Role of Public Sector in Manufacturing Firms:               Case of Spain and Portugal ......................................................................................................    18                ANGELOVSKÁ Olga:               Organizational-Legal Form of Czech Hospitals – Analysis of the 2006 ´Window of Opportunities´    26                BACHMANN Pavel:               What Matters in Social Media Engagement? Czech Social Service Organizations´ Example...........    35                BOČKOVÁ Kateřina; LAJČIN Daniel; DOHNANSKÁ Monika:               Project Management Teaching at Czech Public Universities in the Context of Project Manager               Competencies Covered within the National Competence Baseline of Project Management, version 4               ..............................................................................................................................................    42                BUCCI Valeria:               The Role of Fiscal Considerations in Business Capital Structure: Evidence from Innovative Start-ups               ..............................................................................................................................................    50                COLE David; GUBALOVÁ Jolana; KUBIŠOVÁ Ľuboslava; MURRAY SVIDROŇOVÁ Mária:               The Nostalgianomics of Living Preferences: Where Would You Like to Live?................................    58                ČERNĚNKO Tomáš; PECIAR Vladimír:               Administrative Fragmentation and Productivity of Firms. Case Study: Slovakia ............................    66                GLASEROVÁ Martina; KOBLÍŽKOVÁ Klára:               Value Preferences of Employees Working in the Non-profit Sector..............................................    76                GYAMFI Solomon; ANDERSON Henry Junior; STEJSKAL Jan:               Public Sector Financial Support for SME Innovativeness: Case Study of Selected CEE Countries ...    84                HRŮZA Filip; MAKÝŠOVÁ Lucia:               Facebook Practices of the Czech Regional Capitals – Pilot Insights in the Character of the               Communication with Citizens ...................................................................................................    92                JACKO Tomáš; KAŇKOVÁ Alexandra:               Competencies and Financing of the City of Bratislava and its Boroughs.......................................    99                 JÍLKOVÁ Eva; ZÁVADSKÁ Miroslava:               The Impact of Public Expenditure Efficiency on Labour Productivity in V4 Countries ....................    107                KOTÝNKOVÁ Magdalena; WILDMANNOVÁ Mirka:               The Changing European Labour Market and its Consequences on Social Expenditure System.......    115               KRÁL Martin; HÁJEK Ladislav:               Efficiency Measuring in Public Administration from the Employees´ Perspective ..........................    122","KURTI Sllavka; DOLLANI Petrit:               Evaluation of the Service Quality in Public Hospitals from the Patient´s Perspective – the Case of               Albania...................................................................................................................................    130                MICHÁLEK Tomáš:               How to Evaluate the Effectiveness of Science-policy Interface: A Postmodernist Approach...........    140                MIKUŠOVÁ MERIČKOVÁ Beáta; MUTHOVÁ Nikoleta:               Innovative Ways of Citizen Participation in Delivering Public Services .........................................    148                MŰLLNER Vojtěch:               Optimization for Minimal State: Case Study of Bureaucracy Ratio in Czech Armed Forces 1997 -               2017  .....................................................................................................................................    157                PALA Tadeáš:               Consistency of Czech Foreign Policy and Export Tendencies towards States with Ongoing Conflict –               Case Study Comparison ...........................................................................................................    165                PALIČKOVÁ Irena:               Does Czech Republic Suffer from Baumol´s Cost Disease?.........................................................    173                PODSIADLO Piotr:               A Question of State Aid for Sectoral Development in the EU.......................................................    181                PROVAZNÍKOVÁ Romana; CHLEBOUNOVÁ Denisa:               Costs and Benefits of the Dual Vocational Training System and its Use in the Czech Republic ......    190               ROBAKIEWICZ Wioletta:               Talent Management in Public Healthcare ..................................................................................    198                ROZMARINOVÁ Jana:               Use of Cost Effectiveness Analysis in Health Care. Towards Efficiency in Health care?  ................    206                 SOBOTKA Martin; SOBOTKOVÁ Lucie:               Comparison of Inequalities in Incomes in the European Union ...................................................    213                ŠTARHOVÁ Iveta; GODAROVÁ Jana:               Non-take-up Phenomenon in Conditions of the Czech Republic ..................................................    221               VOKOUN Marek:               Innovation Activities of Public Organizations in the Czech Republic between 2008 and 2014 ........    228                VOKOUN Marek; STELLNER František:               Public Funding of Business R\&D Activities in the Czech Manufacturing Sector 2010 – 2014 ..........    237                VOSTATEK Jaroslav:               Paradigm Reform for the Czech Family Benefits and Credits.......................................................    245                ZIMMERMANNOVÁ Jarmila; SKALIČKOVÁ Jolana:               Splitting of Environmental Taxes Revenues in the EU ................................................................    253","Prologue                       It was a real pleasure to serve as the Head of the Programme Committee of the Current                trends in Public Sector Research conference, which was held in Brno in January 2019. During                last  years  the  conference  became  one  of  the  main  floors  for  the  debate  of  experts  in  public                economics, the non-profit sector, and public administration.                      The  conference  regularly  hosts  researchers involved  in modeling  public  sector  policies,                evaluating their impact on public finance and social policy. The second group of researchers is                usually  devoted  to  public  administration  topics, such  as  responses  to organizational changes,                public sector leadership, or effectiveness of administrative services.                      This year edition of the conference aimed to bridge the gap between these two main tracks                of  the  conference.  The  main  conference  topic  –  the  experimental  and  behavioral  research  in                public  administration  –  uniquely  links  theoretical  research  with  public  administration                applications.                      I  am  very  happy  that  Professor  Oliver  James,  University  of  Exeter  (UK),  accepted  the                invitation as a keynote speaker. Oliver James is a professor of political science and works on                issues in public policy, public administration and regulation. His primary interest is in academic                research  and  teaching.  Moreover,  he  works  with  public  sector  organizations  in  the  UK  and                elsewhere,  and  has  acted  as  a  consultant  to  bodies  including  the  World  Bank,  OECD,  UK                Treasury, UK National Audit Office and UK Audit Commission. As his current research agenda                covers applications of the method of laboratory and field experiment in public management, one                can hardly find a better keynote for this year’s conference topic.                      It became a tradition that the main conference topic is reflected in the programme of the                whole  conference.  It  was  a  pleasure  to  arrange  special  conference  session  “Experiments  in                Public  Management  Research,”  which  hosted  researchers  from  the  top  European  centers                involved  in  laboratory  and  field  experiments.  The  main  conference  topic  was  also  discussed                within other sessions, as can be seen from the papers included in conference proceedings.                      The second special session, “Killing the Messenger? Civil society in the CEE countries” was                oriented on another up-to-date discussion in the field. Mainly in the CEE countries a significant                backlash initiated by new political representatives towards the third sector is visible. The panel,                therefore, discussed the legitimacy of the third sector involvement in public policy, its picture in                the society, and the role of media in shaping citizens´ attitudes.                      As  usual,  the  scope  of  the  conference  is  broad  and  covers  a  variety  of  topics.  The                conference  proceedings  can  serve  as  an  overview  of  the  current,  highly  discussed  subject.                Besides that, the reader is also able to see the scope of the analytical and research methods used                in public sector research.                      I am pleased that the conference proceedings contain mostly the contributions of doctoral                students researching public sector. The quality of the analytical papers confirms that there is a                great  potential  of  the  new  generation  of  scholars  involved  in  public  economics  and  public                administration  research.  This  generation  is  in  close  connection  with  top  researchers  and  is                equipped with full access to resources in the field.                      As  this  conference  was  the  last  for  me  in  the  role  of  the  Head  of  the  Programme                Committee, I would like to thank all my colleagues who helped to keep this conference going. To                give  the  scholars  the  floor  to  meet,  discuss,  and  to  dispute  on  their  research  agenda  still                symbolize the focus of academic life.                      I wish Current Trends in Public Sector Research conference all the best in the future and                looking forward to meeting you at its 24  edition in January 2020.                                                      th                        Jiří Špalek                      Head of the Programme Committee                                                                  7","8","Bridging the Gap: Ghana's National Health Insurance Scheme                                 and Its Impact on Under-Five Healthcare                                                     AMOAKO Martha                       Department of Public and Social Policy, Faculty of Social Science, Charles University in Prague, Czech Republic                                            mamaoko24@gmail.com; 10836079@fsv.cuni.cz                 Abstract                 Children under-five health care and well-being is critical to achieving the Sustainable Development Goals.                An effective and sustained  health system drives health care delivery and leverages effective healthcare                outcomes,  –particularly  among  mothers  and  under-five  children.  This  study  reviewed  Ghana's  health                financing  policy,  the  National  Health  Insurance  Scheme  (NHIS),  and  its  consequent  impact  on  early                childhood  (0-5  month)  healthcare  outcomes.  Drawing  upon  qualitative  fieldwork  in  Ghana,  the  study                made use  of semi-structural interviews with women within the reproductive age (15-50 years) from a                diverse working  background (including officials from the GHS and selected hospitals) in three selected                study areas in the Western Region of Ghana. Institutional data from National Health Insurance Authority,                World Bank, and Ghana Health Service were used to complement the interviews. The study revealed that                though the  national health  insurance scheme  is positively correlated with good childhood outcome, its                implementation does not deliver on its intended purpose of closing the inequality gap in child healthcare.                The study recommends that national health insurance coverage be expanded through a partnership with                private medical insurance and service providers to  enable pregnant women and  nursing mothers have                easy access to healthcare.                 Keywords: Under-five healthcare; healthcare finance; NHIS; health equality; health policy                JEL Classification: I18, I130, I19                    1  Introduction                       Early childhood healthcare is one of the most prioritized topics in today's global health.                Better child health improves human production, sustains future wages, and leverages growth                and development of any economy. According to the report [15], about 5.4 million children die                before their fifth birthday. Almost all of these deaths occur in developing countries, especially in                sub-Sahara Africa (SSA), which contributes 50.1% of all the under-five death cases in 2017 [15].                Under-five mortality is distributed unequally across the globe. These deaths range from 123.3                per 1000 in Chad to 2.3 per 1000 in Finland [15]. These deaths are caused by preventable and                treatable diseases [6], which means better health needs to be attained if these early childhood                deaths  are  to  be  avoided.  Health  cost  makes  the  poor  poorer;  therefore,  world  leaders  are                committing  to  ‘health  for  all  policy'.  However,  government's  responsibility  in  the  delivery  of                health  services  has  an  inextricable  link  to  finance.  Finance  provides  a  boost  to  equality  and                universal health coverage.                      Ghana is among the few countries in sub-Saharan Africa (SSA), which have national health                insurance instituted as part of its pro-poor policies. The policy provides subsidies to augment                the cost of health care through the expansion of healthcare access, affordability and maternal                (antenatal  and  postnatal)  user  fee  exemption  policy.  Indeed,  the  government’s  choice  of  the                National  Health  Insurance  Scheme  (NHIS)  was  born  out  of  the  high  rate  of  mortality  in  the                country  during  the  period  ‘'cash  and  carry  system''-  a  term  used  to  describe  financial  setup                where payment is made before one can access healthcare. This system led to a tragic outcome in                the healthcare sector [14]. Also, the high-cost burden of healthcare on households, especially the                poor due to the out-of-pocket payment for health services, underpinned the implementation of                the  NHIS.  The  scheme  is  funded  based  on  the  combination  of  tax,  employer  deduction  and                informal  sector  based  on  the  capability  of  people  [4].  The  Free  Maternal  Healthcare  (FMH)                                                                9","programme,  an  aspect  of  the  NHIS,  ensures  that  all  pregnant  women  irrespective  of  your                economic  status  have  free  access  to  healthcare.  However,  the  financial  structure  of  Ghana's                healthcare faces a critical challenge because of the over-dependence on donor funds and delay of                the government to reimburse services providers.                      It  has  been  estimated  that  the  National  Health  Insurance  Authority  and  government                expenditure  on  preventive  and  public healthcare  was 29% out of  the  total  expenditure,  with                71% of the expenditure sourced from development partners (see: Health Sector Medium Term                Development  Plan  report  (HSMTDP  II).  The  volatility  and  uncertainty  of  donor  funds  for  the                health sector pushes healthcare service to the brink, hence, reducing its ability to cater for key                obstetrics and child health medication (e.g. Cytotec) and services [9]. This study reviews Ghana's                pro-poor social healthcare financing policy – the National Health Insurance Scheme (NHIS) and                its consequent impact on early childhood (under-five) health outcomes among the population.                Through this lens, the study analysed the NHIS policy developments and its implementation to                know whether or not it bridges the healthcare inequality gap among the populace as intended. It                also  discusses  the  maternal  fee  exemption  policy  under  the  NHIS,  its  impacts  on  early  child                health-related outcomes and how it influences household finance.                      The  main  question  addressed  in  this  study  is  to  what  extent  has  the  Ghana  health                insurance  policy  contributed  to  the  under-five  child  health  outcome?  What  has  NHIS  policy                achieved so far in closing the inequality gap between the people (poor and the rich, urban and                rural) as it intended?                 1.1 Background of Ghana’s Social Health Insurance                      The  government  of  Ghana’s  model  of  the  social  health  insurance  system  has  some                elements of both Bismarck and Beveridge system [12]. In mid of the 1970s through to 1980s,                World Bank and International Monetary Fund introduced Economic Recovery Programme, 1983,                which led to the removal of the free health subsidies and enforced a higher fee on HFA (Hospital                Fee  Act)  –  Hospital  fee  regulation  (L.I.1277).  In  1992  the  ‘Cash  and  Carry'  system  was                introduced. This policy deprived most of the population access to healthcare due to the high cost                of  service.  The  poor  could  not  afford  and  were  left  to  die  home  [10].  Children  and  pregnant                women were the most hit [16]. The NHIS was then introduced through the Act of Parliament in                2003 to abolish the ‘cash and carry’ system.                      Theoretically,  the  discussion  on  health  insurance  mostly  centred  on  the  effect  of  the                coverage in general and how it influences the health-seeking behaviour among the population of                a state. The rational decision - like let me try, I got nothing to lose - gave room for more women                to visit the hospital before and during pregnancy then right after birth. NHIS induced a shift                towards increase service utilisation [14]. Enrolment on the NHIS grew significantly with a total                active  registered  member  (both  exemption  and  non-exemption)  risen  from  6.6  %  to  38%  in                2005  and  2013  respectively  [11].  Those  covered  by  the  fee  exemption  policy  only  (most                impoverished and elderly) of the NHIS rose from 54.5 % in 2010 to 63% in 2013. It shows that                the insurance policy reached the targeted group. It is argued that Ghana's NHIS has an impact on                the family income and this supposedly was in favour of the poor [12]. However, it is also noted                that Ghana's pro-poor policy implementation process risk the poor since the change in relative                cost, which is the back-born for the rollout of the health insurance may directly affect the poor                [11].                 1.2 Financing Flow of the NHIS                      Operationally, financing flows into the National Health Insurance Fund (NHIF), created for                the implementation of the national health insurance scheme, has six main sources. Act 650 and                Act 852 of the NHIF defined by the Parliament of Ghana ensures the following categories for the                mobilisation  of  the  funds:  (1)  2.5  %  National  Health  Insurance  Levy  (NHIL)  added  on  value-                added tax (VAT) of selected goods and services; (2) A deduction of 2.5 % social security and                Pension Scheme Fund from the formal sector workers managed by Social Security and National                Insurance  Trust  (SSNIT);  (3)  Grants,  donation,  gifts  and  other  voluntary  contribution  from                                                               10","individuals, NGO's, multinational cooperation, international organisations and others; (4) The                government  of  Ghana  (GOG)  annual  budget  allocation  approved  by  parliament;  (5)  Money                accumulated  on  the  investment  made  by  the  surplus  fund  of  NHIF;  and  (6)                Premium/contribution fee pay by the informal sector to the NHIA.                      Parliament may also from time to time allocate money to the NHIS. Effective under-five                health  care  and  development  are  dependent  on  finances  that  have  been  invested  in  health                infrastructure and services [9]. From 2005, the proposition of GDP devoted to health was 6.4,                since then GDP investment in health has ranged from 3% in 2010 till date [11]. Out of this, an                estimate of 50% comes from annual budgetary allocation from the government, with the rest                coming from donors. The percentage of Ghana's GDP allocated to health is insufficient compared                to the 15% GDP that Abuja Declaration established.                                        Figure 1: Conceptual Framework of the Financial Flow                    Source of Funds     Income                                                                                                    Expenditure                    . 2.5% NHIL         . Health              Ministry of Finance     Administrative \&                    . 2.5% SSNIT        Insurance Levy                                Logistical Support                    deduction from the   (2.5% OF VAT)        \&Economic Planning      to DMHIS                    formal sector       . SSNIT                                       Administration and                    . Premiums from     contribution                                  general expenses of                    subscribers         (2.5% payroll)       National Health          NHIA                    . Funds from the                         Insurance Fund (NHIF),   . Support Partner                    government of Ghana   . Interest on Fund   Managed by NHIA        Institutions                    (GoG) allocation by   . Grant, gifts,                    Parliament          donations Other                    . Sector Budget                         Subsidies        Reinsurance                    Support                    . Returns on           Premium \&                                     Payment of                    Investment             registration fee        District Mutual       claim to                                           (informal sector        Health Insurance      Healthcare                                           people)                 Schemes (DMHIS)       providers                  Source: Adapted from Asenso-Boadi \& Agbeibor, 2010; Cited in [11] with a little adjustment.                  2  Material and Methods                       The research used both qualitative and quantitative data. Semi-structured interviews from                March  2018  to  October 2018  for  the  collection  of  data  were  employed. The  interviews  were                conducted  among  women  within  the  reproductive  age  as  defined  by  the  WHO  (15-50).                Respondents  were  all  women  within  the  reproductive  age  because  one  of  the  main  vital                components  of  the  policy.  Also,  biologically  women  get  pregnant  and  socially  women  have  a                greater responsibility as caretakers of babies in Ghana’s family settings. Assessing the views of                the  targeted  group  on  the  NHIS  policy  was  worth  exploring.  A  total  number  of  200  women                respondents  in Takoradi,  Mpohor and Shama  all  in  the Western  Region  (WR)  of  Ghana  were                interviewed. These included informants from the institutional level to get the social, economic                and political dimension of NHIS.                      Case study areas were selected based on their location (20kms from Takoradi the capital                city of the WR) and economic activities of the populace. Fifty (50) respondents from Mpohor, 50                respondents from Shama and 100 respondents from Sekondi-Takoradi were interviewed. This                distribution was done to get the clear disparity of the NHIS impact in the urban and rural area.                These communities are close to Takoradi yet under-developed in terms of infrastructure and                services. Demographic information such as age, educational background, household size, type of                employment and among others, which are essential indicators for assessing maternal and child                health outcome as well as the NHIS policy usage and impact were collected. This data helped to                examined whether the safe motherhood programmes under the NHIS are on target. Also, data                                                                 11","were employed as complementary from reputable organizations, such as GHS, WHO, UNICEF,                WB, and AFDB.                   3  Results and Discussion                       A majority of women respondent were between the ages cohort 31-40 years representing                40 % of the total respondent. The other groups between the ages less than 20, 20 – 31 and 41 -                50 years, representing 20, 28 and 12% of total respondents, respectively. The result indicates                that there were a high number of young women, which according to MOH have the highest level                of fertility rate of 4.5%. Out of this number of respondents, 62 of them were without any formal                education, 44 of them had primary education whereas 38 had junior high school and other 26                and  30  respondents  had  secondary  and  Tertiary  education  respectively  (see  Figure  2).  The                information  on  age  and  level  of  education  was  relevant  because  the  level  of  knowledge  and                maturity of women have linked to the development of children, especially children under-five                [15].                                         Figure 2: Age and level of education of respondents                               Source: Researchers own field survey, 2018.                 3.1 The relationship between household size and economic activities of respondents                      Study on the politics of Ghana's NHIS by [14] revealed that people nature of job influences                their income, which subsequently have impact on their household health expenditure. Research                shows that generally, household with heads who are farmers and mostly base in the rural areas                are  not  just  the  poorest  in  Ghana,  but  they  also  contribute  the  most  to  Ghana’s  poverty  [3].                According to [14] people with large household size are likely to enrol in the NHIS. This was true                for the respondents who were farmers (fishing and crop farming) and have larger household                size as well as lower level income but yet formed the largest registered NHIS members. The data                in (table 1) shows details of the occupation of the respondents and the size of their household.                ‘Others' represented in table 1, means employment other than those analysed below. Also, the                total  number  of  the  respondents  in  this  section  of  the  study  was  78.5%,  representing  157                respondents. 21.5% were not ready to disclose their job or family information.                          Table 1: The relationship between household size and economic activities of respondents                Household      Farming        Trading            Salary           Others        Total                Size                                            workers                Less than 6      15     7.5%    13      6.5%      25       12.5%    10    5.0%   63   31.5%                6-10             36    18.0%    28     14.0%       5        2.5%    8     4.0%   77   38.5%                11-20            7      3.5%     9      4.5%       0        0.0%    1     0.5%   17    8.5%                More than 20     0      0.0%     0      0.0%       0        0.0%    0     0.0%   0     0.0%                Total            58    29.0%    50     25,0%      30       15.0%    19    9.5%   157   78.5%                Source: Researchers own field survey, 2018.                                                                   12","3.1.2 The effect of NHIS on health service utilization                      Births attended by skilled personnel, antenatal and post-natal healthcare coverage, as well                as cost, quality of treatment and time of accessing healthcare by pregnant and nursing mothers,                are crucial for children under-five health [13]. These indicators (shown Table 2), are the critical                determinant  of  under-five  health  outcome,  since  better  maternal  healthcare  are  inextricably                linked with early childhood survival [18]. 102 respondents out of the 200 interviewed agreed to                be NHIS card holders. Sixty-eight (68) respondents do not have any form of health insurance                (both  NHIS  and  private  insurance)  whiles  24  of  the  200  respondents  have  Private  Health                Insurance (PHI). Of the 102 respondents, 98 women representing 96.1% agreed they utilised the                institutional  health  service  for  primary  healthcare  (PC).  Eighty-eight  (88)  representing  86%                accessed perinatal and antenatal care, 69 delivered their babies in the health facility whereas 54                and 97 respondents obtained post-natal care delivery and had Prescriptions.                      However,  the  same  cannot  be  said  for  the  women  without  NHIS  or  any  form  of  health                insurance, since few of them accessed the facilities as shown in table 2 below. Twenty-four (24)                respondents  with  the  private  health insurance  were  mostly co-operated  women,  working  for                private and so call private government companies such as Ghana Port and Harbour Authority                (GPHA),  Osmose  Energy  Company  etc.  Almost  all  the  24  respondents  have  access  to  all  the                indicators defined for the analysis in table 2, except for post-natal care which had 16 out of the                24 respondents agreed to have utilised the service. The low turnout of the post-natal attendance                for  the  private  insurance  cardholders  was  link  to  belief  and  culture,  whereby  the  new-born                babies were to be kept in the room for 7 days without the sun before bringing it out, unless                under  severe  illness  or  attack  most  women  obey  this  norm  to  avoid  the  supposed  spiritual                complication of it.                      Table 2: The relationship between NHIS and utilisation of professional health care of respondents                 Seeking Institutional             NHIS          No NHIS       Private HI     Total (200)                 Medical care                  Cardholders     Cardholder      cardholder                                              Freq   Percent   Freq   percent   Freq   Percent   Freq   %                 Number respondents            102   51.0%     68    34.0%    24    12.0%    194    97.0%                 Skilled health attendant for PC   98   96.1%   49   61.7%    24    100.0%   174    87.0%                 Perinatal and ANC             88    86.3%     29    42.6%    24    100.0%   141    70.5%                 Health facility Delivery      69    67.7%     32    47.0%    24    100.0%   125    62.5%                 Post-natal care delivery      54    52.9%     14    20.5%    16    66.7%     86    42.0%                 Prescriptions                 97    95.0%     48    70.6%    24    100.0%   169    84.5%                Source: Researchers own field survey, 2018.                 3.2 Analysis of inequalities of health care between urban and rural areas in Ghana                      The accessibility and delivery of effective health care is linked to the distance of users to                health  facilities  and  infrastructure,  availability  health  professional  and  the  cost  of  treatment.                However, the health situation in Ghana has been characterised by significant inequality over the                past  years  [4].  Even  though  the  state  is  the  leading  provider  of  healthcare  for  70%  of  the                population due to the NHIS, private sectors facilities ownership accounted for 46.4% of the 336                number of the general hospitals in the country. Also, the private sector is dominant in providing                maternity home, which stood at 379 out of 389 representing 97.4 % of the overall maternity                homes  in  Ghana  [1].  Almost  all  of  them  are  located  in  cities  and  big  towns.  Private  sector                healthcare services are costly due to the high standard of services delivery; therefore, most poor                people could not afford [6]. One of the reasons that prompted ‘health to all policy' is the health                inequality  among  the  populations  as  a  result  of  geographical  accessibility.  Accessing  health                service  remains  poor  in  some  part  of  the  country,  mainly  the  rural  areas  and  notably,  the                northern  part  of  the country.  The  inequality  in  accessing  health  services between  urban  and                rural dwellers is enormous. The data analysed by [10] revealed under-five mortality (deaths per                1,000  live  births)  was  90%  in  rural  areas  and  75%  in  urban  places  of  Ghana  in  2008.  The                inequality  in  the  number  of  deaths  between  the  rural  and  urban  reflected  the  poor  socio-                                                                13","economic status of the population living in the rural, as many poorest people live in these areas                (see table 3).                      Yes, I have the NHIS card, but there is no hospital or clinic anywhere close to my village, the                nearest health post is at Mpohor, we hardly meet a midwife or a doctor… My husband has to put me                in a taxi to travel a distance to get a better hospital in Takoradi. Last year two of my friends in my                village lost their babies and one died with the baby. I am scared, so any time I am about to give                birth my husband brings me to live with his sister here in Takoradi …. so that I can get access to a                doctor when I am in labour. – [Kukuwa, a house wife from Ayiem].                      Though  people  have  the  NHIS  card  which  gives  the  right  to  utilise  the  public  health                services as well as some private providers, it did not necessarily close the gap or ensure equality                in health serves delivery. The availability of the service was skewed to the urban area where                most of the improved population lives. The human resources and the facilities according to some                respondents were not available. The inequality in the distribution of health personnel is vast as                well.  As  of,  2012  ending,  twenty-five  government  general  hospitals  out  93  in  Ghana  were                without a doctor, eight (8) out of the 25 were located in the northern region alone [4]. Greater                Accra  region  which  is  urban  and  the  capital  city  of  Ghana  accounts  for  50  %  of  all  Ghana's                doctors, with one doctor to 3.540 dwellers, the other 20% are for Ashanti Region. The Upper                West region has 11 times fewer doctors than the Greater Accra region [10]. The same pattern of                unequal  distribution of midwives  could  be  seen in  Figure  3. The  analysis  (figure3)  shows  an                evident  inequality  across  Ghana's  health  sector.  The  WR  as  of  2012  has  277  midwives  as                compared to Greater Accra (GAR) which had 812. The disparity in allocation of HRH may have                significantly contributed to the high number of mortalities of the under-five children in some                part of the country.                      Most expectant mothers who are rushed in here from nearby villages have registered NHIS                card, but they come without any basic baby kind of stuffs on them. After delivery, any item you ask                them to buy becomes a problem. The husband or relative who brought her will tell you he/she used                the  last  money  on  him  to  pay  for  the  taxi  or  vehicle  that  commuted  them  to  the  facility.  We                sometimes had to support them from our own resources, but it is becoming unbearable for us too….                [Mrs. Asare a midwife working at Effia-nkwanta regional hospital, June 2018].                      This goes to confirm the argument that NHIS may have increased the number of women                who seek for institutional health but have not necessarily close the inequality gaps among the                population  [14]. This  study  agrees  with other  findings,  which  indicate  a  vast  disparity  of  the                under-five mortality within countries, between the rich and the poor household especially those                living in the rural area [5, 17]. People residing in rural areas do not only spend on the health                service but also transport, feeding and housing cost in the process of trying to get better health                services in the cites. Hence, an effective health goes beyond the health sector but includes other                dimensions of the economy.                            Table 3: Inequalities of health care between urban and rural areas in Ghana 1n 2008                 Indicator                                    Rural   Urban   Poorest 20%   Wealthiest 20%                 Under-five mortality rate (per 1,000 live births)   90   75     102              60                 Births attended by skilled health personnel    43     84         24              95                 DTP3 Immunisation (1-year-olds)                91     87         89              93                Source: Adopted data from MoH, 2015.                                                                               14","Figure 3: Trend of Ghana’s Doctors and Nurses distribution in 2016; Mid-Wives’ distribution for 2011-2014.                              Source: Data from GHS, 2015, Ghana Statistical Service- GDHS, 2016.                 3.3 Discussion                      An understanding of the state of NHIS in Ghana was a meaningful way to reveal how the                state intervention policies, programmes and practices can be aligned to promote better health                for all.. Early child mortality has reduced significantly across the country since the introduction                of the NHIS in 2005.                      The ratio of neonatal morality reduced from 33.4 per 1000 live birth in mid-2005 to 24.4                per 1000 live delivery in mid-2017, whiles under-five mortality per 1000 live birth reduced from                85.7  to  in  mid-2005  to  49.3  in  mid  of  2017.  Infant  mortality  remains  the  same  without  an                additional death, 3.8 death per 1000 live birth from mid-2005 to mid-2017 [15]. Operationally,                the NHIS has a mixed perspective, the progress and the challenges. The quality of service has                improved, due to NHIS accreditation insisted for all providers to prove level of quality using an                outlined institutional quality assessment rules before issued with the NHIS licenses to provide                services [15]. As seen in the field survey (table 2), similar trend in the number of birth cases                attended by skilled professional as of 2014 stood at 74% a significant improvement from 59% in                2003.  Birth  cases  in  health  facilities,  rising  from  57%  in  2003  to  73%  in  2014  (see  [14]).                However, this improvement has been observed (section 3.2) to be unequally distributed across                the country. As children in rural areas and from poor households, an example in the northern                regions are more prompt to diseases and died before their fifth birthday than those living in                Accra, urban. Also, there are implementation challenges of the NHIS. The researcher observed                poor supervision and monitoring of the policy implementation. Indeed, it has been argued that                NHIS is not well supervised and organised due to the centralised system of the NHIA decision-                making  process  and  the  high  political  parties'  interference  [9],  [14].  These  implicate                reimbursement of the service fee to providers.                      I was in the hospital, but they asked me to pay some money even though I have the NHIS                card, so I have decided not to go again as I don’t have the financial resources……. [Mrs, Koomson, a                Fish seller at Shama Taxi station, August 2018].                      It was also revealed from the field survey that some registered NHIS members can access                healthcare,  but  NHIS  policy  intended  to  ensure  the  poor  get  equal  access  to  quality  and                affordable healthcare was not wholly accurate. There were no health facilities in most of the                rural areas visited, in the places where there were health facilities, they were under-equipped.                Some women end up losing their babies or their lives during the journey to seek professional                care. More efforts should be put in the policy implementation process. There should be more                education and health promotion on the need for post-natal healthcare. Programs that focus on                gender  should  be  strengthened  to  empower  women  to  be  financially  independent  to  able  to                access better health care alternative to reduce the gap.                      Moving forward, since financial incentive prompt implementers (both private individuals                and public authorities) to behave certain way desire for the realisation of policy. It is crucial for                every  nation  mostly  developing  country,  particularly  Ghana  policy  decision  makers  and                implementer to mobilised enough financial resources through private-public partnership, and                outsourcing to implement this intervention (free maternal Health Care and fee exemption policy                for children). Risen and allocation of financial resources do not only improve the distribution of                                                               15","policies,  but  it  also  helps  regulatory  or  constitutive  of  programs  or  other  interventions  [8].                ‘Primary healthcare for all’ (Alma-Ata declaration) is still a very significant rule to follow by the                policy implementers.                  3.4 Limitation                      The study did not include men in the field survey, even though fathers play an essential                role as the head of the family in Ghana. It is, therefore, necessary for future research to consider                the role of males as a critical determinant of under-five mortality in Ghana and other parts of the                world. Also, most women were not cooperative, and especially those the researchers met at the                maternity wards of different hospitals. Health providers were also not ready to answer some                questions.                  4  Conclusion                       This  study  presents  selected  examples  of  the  state  of  inequality  in  Ghana,  highlighting                essential  and  relevant  stories  of  the  state  of  RMNCH  (reproductive,  maternal,  new-born  and                child health) programes. It analysed the impact of Ghana's social Insurance on under-five health                outcome. It was shown that women registered with the NHIS are likely to seek primary health                services as well as access professional skilled health service as compared to those without any                form of insurance. Indeed, the NHIS has positively impacted under-five health outcome, since                effective access to health care during pregnancy and after birth is linked to the baby's under-five                survival and children development in general. However, health care delivery improves in urban                but  deteriorates  in  the  rural  areas.  This  trend  is  further  driven  by  the  poverty  distribution,                where there are more poorer mothers living in rural areas than urban areas. More poor and                rural  population  is  likely  to  pay  more  to  access  health  care  due  to  the  poor  and  unequal                distribution of health resources in the health system. The NHIS policy needs to be reformed to                ensure that the rural and the sparse population have a fair share of the national health care                system [8].                  References                 [1.]  AMOAKO, M., NAHANGA VERTER, 2018. The role of institutions in influencing maternal and children                     under-five  health  care  in  Ghana.  Proceedings  of  the  21   International  Scientific  Conference                                                                         st                     “Enterprise and Competitive Environment”. Brno: Mendel University                [2.]  DE-GRAFT, A. A and KORAM K. 2017. Health and Healthcare in Ghana 1957–2017, In the economy of                     Ghana:  sixty  years  after  independence,  (ed.  Ernest  Aryeetey  and  Ravi  Kanbur).  Oxford  University                     Press. Pp 365-384.                [3.]  GHANA HEALTH SERVICE (GHS). 2015. Draft of fact and figure report. Unpublished but in use at the                     national level. Accra, Ghana health Service                [4.]  GHANA STATISTICAL SERVICE (GSS). 2016. Ghana Maternal Health Survey 2016. Accra. Calverton,                     MA: Ghana Health Service, and Macro International                [5.]  HEALTH SECTOR MEDIUM TERM DEVELOPMENT PLAN (HSMTDP). 2014 – 2017. Ministry of Health,                     (1 0ctober, 2014), Accra                [6.]  HOUWELING, T. A., KUNST, A. E. 2009. Socio-economic inequalities in childhood mortality in low-                     and middle-income countries: a review of the international evidence. British Medical Bulletin, 93(1):                     7-26.                 [7.]  JEFFERY D. SACH. 2015 The Age of Sustainable Development, Columbia university Press, New York,                     Chichester, West Sachs, Pp 275 -279                [8.]  KAHNEMAN,  D.  and  A.  TVERSKY.  1979.  \"Prospect  Theory:  An  Analysis  of  Decision  under  Risk,\"                     Econometric, 47, 263-291. Econometric is currently published by The Econometric Society.                                                                 16","[9.]  KNOEPFEL, P., LARRUE, C., VARONE, F., Hill, M. 2011. Public policy analysis: Policy Press, University                     of Bristol, UK Britain Library Publication data                [10.] MINISTRY of HEALTH. 2013. Ghana National Health Accounts 2005 \& 2010. Accra, Ghana:                 [11.] MINISTRY  of  HEALTH.  2015.  Holistic  assessment  of  the  health  sector  programme  of  work  2014.                     Accra: MoH.                [12.] OSEI-AKOTO, I., ADAMBA, C. 2017. Health and healthcare in Ghana 1957 – 2017. In the economy of                     Ghana:  Sixty  Years  after  Independence,  ed.  Ernest  Aryeetey  and  Ravi  Kanbur.  Oxford  University                     Press. Pp 365-384                [13.] THADDEUS, S., MAINE, D. 1990. Too far to walk maternal mortality in context. New York, Columbia                     University Centre for Population and Family Health, 1990                [14.] The NATIONAL HEALTH INSURANCE AUTHORITY (NHIA). 2015. Strategic Plan, 2015. Accra: NHIA.                [15.] UNICEF.  2017.  Monitoring  the  situation  of  children  and  women.  [Online].  Available  at:                     https://data.unicef.org/topic/child-survival/neonatal-mortality/ [Accessed: 5 January 2018].                [16.] VOGEL,  R.J.  1990.  An  Analysis  of  Three  National  Health  Insurance  Proposal  in  SSA.  International                     Journal of Health Planning and management, 5:271-285                [17.] WORLD  BANK.  2015.  World  development  report:  mind,  society  and  behaviour.  Washington,  DC.:                     World Bank.                 [18.] WORLD  HEALTH  ORGANIZATION.  2018.  World  health  statistics  2018:  Monitoring  health  for  the                     SDGs, sustainable development goals. CC BY-NC-SA 3.0 IGO                                                                                                                    17","Industrial Cooperation, Knowledge Sources and                           the Role of Public Sector in Manufacturing Firms:                                           Case of Spain and Portugal                                                         a                                                                            b                                                                                               c                           ANDERSON Henry Junior , GYAMFI Solomon , STEJSKAL Jan                                               University of Pardubice, Czech Republic                                  a                   b                   c                                   henry.anderson@upce.cz,  solomon.gyamfi@upce.cz,  jan.stejskal@upce.cz                Abstract                Public Funding for firms has been argued as a catalyst for firms’ cooperative and knowledge generative                activities  in  contemporary  knowledge-based  economies.  As  innovation  potential  is  widely  poised  as                regional competitive ability, firms’ cooperation with partners have been revered as a preliminary activity                to  establishing  networks  whilst  sharing  diverse  knowledge  from  partners  involved  to  initiate  or  even                mediate  innovation.  Using  data  from  Community  Innovation  Survey  (2012-2014)  and  SEM  analysis  on                Spanish  and  Portuguese  manufacturing  firms,  the  paper  assesses  the  relevance  of  public  funds  on                cooperation tendencies of firms, knowledge sourcing from partners and eventually, the moderator role                played by cooperation in appropriating public funds for knowledge acquisition. It was found that public                funding significantly influences cooperation in Spain than in Portugal whilst cooperation was much more                influential  in  sourcing  for  knowledge  from  partners  in  Portugal  than  in  Spain.  Results  also  revealed  a                slightly  higher  moderator  ability  of  cooperation  in  Spain  than  in  Portugal.  Country-specific                recommendations were further created.                 Keywords: Public funds, Cooperation, Knowledge, Spain, Portugal.                JEL classification: O32, O38, O52                    1  Introduction                       The early 20th century witnessed the strong adoption of public support and interference                in private economic activities of macro and micro regions. Emergence of the new growth theory                also further entrenched government’s interest in supporting and actively engaging in regional                growth  efforts  by  actively  supporting  firms  via  subsidies  and  grants.  Adoption  of  the  open                innovation model not only limited firms to the assistance of governments but also incited an                interactive and knowledge sharing collaborations which opened up firms up to new margins of                innovation now strongly endorsed as a model for contemporary regional growth.                      Literature  on  cooperation  of  firms  with  universities  and  research  centers  have  been                endorsed by most researchers [3], clients [14], [19], and suppliers [2],[12] and have proven to                be viable partners for knowledge generation and acquisition. In Spain, cooperation measures                has  been  realized  by  entrepreneurs  as  having  one  of  the  lowest  cooperation  intensity  in  the                Union, decreasing rapidly from 2012 forward whilst Portugal, from the viewpoint of Universities                and businesses was adjudged to have a weak cooperation as well [28].                       Majority of research have also endorsed the overwhelming relevance of cooperation by                firms [7],[33],[30] knowledge sourced for innovatory needs [7],[29],[33]. Despite the contrary                propositions that public funds are mere interferences in the economy and stifles businesses by                crowding  out  funds  [1],  the  researcher  believes  that  funds  invested  for  research  are  equally                beneficial as privately invested funds and supports the notion cooperation as both an antecedent                and a transformer of resources invested for research collaboration and knowledge generated.                      Owing to the new-found public support for innovation centric activities [4],[23], the below                par cooperation levels in Southern European countries [28], the need for cooperation in creating                intellectual capital for expediting regional knowledge growth and competitive advantage [22]                and also the continuing contemporary public financial interest in supporting knowledge sharing,                the  research  aims  to  assess  the  relevance  of  public  funding  on  cooperation,  on  knowledge                                                               18","acquired and the moderator role cooperation plays in transforming public funds into knowledge                acquired by firms for innovation needs.                      The first section of the paper will give an introductory review of the topic focused, the                second part will discuss the literature on the concept of funding, cooperation and knowledge, the                third part will explain the methodology used and the data sources, followed by analysis of the                results and finally conclusion.                  2  Literature Review                       The  New  growth  theory  has  incited  international  and  national  support  for  knowledge                sharing and co-operative interactions with firms, academic institutions and industrial partners                and even non- governmental organisations (NGO’s). Owing to the regional value created and its                innovation potential, supranational, national and local authorities in recent times, increasingly                inject  public  funds  into  firms’  operational  and  cooperative  interactions  with  other  firms,                academic  institutions,  research  institutes,  suppliers  etc.  with  the  eventual  objective  of  firm                growth, innovation and subsequent regional development [22].                      The circular triple helix model buttresses this adopted responsibility of the government as                a  financier  via  establishment  of  funding  programs  and  subsidies  to  support  industrial                collaborative  research  with  Universities,  other  firms  and  other  relevant  partners  in  the                industrial  and  market  sphere  [13].  Such  financial  support  expended  to  regional  players  is                fundamentally oriented at inter-firm R\&D collaborations, firms and academic collaboration as                well  as  other  external  partners.  Strategic  alliances  created  by  firms  in  lieu  of  this  resource                acquisition  has  its  tenets  on  accessing  new  resources,  acquiring  access  to new  technology  to                innovate or to penetrate new and uncharted markets [25].                      Spike in publicly funded collaborations in industries in recent times have been alluded to                additional  funds  for  innovation  required  within  the  industrial  sphere  owing  to  the  adjudged                inefficient use of the public funds invested for cooperative research among other partners in the                industrial sphere [17]. Previous research also found that federal R\&D stimulates total private                R\&D intensity [6] whilst, it had been thought that private R\&D investment devoted to research                falls as the firm receives more public R\&D funds. It was however, argued to have been caused by                crowding out but it was rebutted that such funds were only an aspect of the entire company                budget  [1]  and  hence  could  not  be  argued  that  federal  funds  significantly  diminished                expenditure of private firms.                      Reliably, such funds expended are ridden on for cooperation by firms with other firms                [24]  and  Universities.  Research  in  the  public  sector  have  revealed  the  significance  of  public                support  on  the  tendency  of  companies  undertaking  R\&D  cooperation  with  public  research                organisations  all  of  which  are  aimed  at  eliminating  market  failures,  [22].  Despite  the  wide                acclaim that public funds supports firm research, some authors denounce the relevance of public                funds to research and development activities of firms as it is believed to be strongly dictated by                firms internally generate funds rather than public investment further entrenching the contrary                [4] which could be chiefly aligned with perceived bureaucracy at the National and supranational                level as well as implementation and transparency inefficiencies.                      Cooperation  with industrial  partners  incites sharing  of  knowledge  from  all  participants                effectively  perpetrating  the  lasting  effects  of  knowledge  spill-overs  from  academic  sector  the                industry  and  its  partners.  Regional  growth  in  a  knowledge-based  economy,  in  contemporary                times, have been hinged on the how easy knowledge is acquired, shared and used for innovatory                purposes  [2]  to  harness  entrepreneurial  opportunities  and  acquire  greater  recognition  for                leveraging.  [23]  undertook  a  case  study  research  to  assess  how  funding  agencies  assisted  in                generating  knowledge  that  spans  various  disciplines.  In  their  cases  studied,  they  concluded                funding needs to be flexible, to allow programmes the time and space to evolve and realise their                full interdisciplinary potential. This funding also needs to include investment in liaison roles and                less visible processes.                                                                 19","Czarnitzki et al. [9] applied a matching estimator in a multiple treatment setting, analyse                the effects of R\&D collaboration and public R\&D funding on R\&D per sales and patent acquired                for Germany and Finland and found that collaboration has positive effects. [8] entrenched the                connection  between  funds  and  knowledge  of  firms  on  a  study  of  how  sources  of  funds  and                diversity  of  knowledge  affected  firms’  new  product  development.  They  found  that  internally                generated funds emboldened the impact of R\&D sources with more diversity of knowledge on                the sale of new products, while external funds strengthened the effect of R\&D sources with more                control of knowledge on the sale of new products.                      Literatures on strategy have also revealed that cooperation and knowledge acquired from                external  agents  are  relevant  resources  of  the  firm  in  the  current  competitive  environment,                especially for innovatory reasons [11]. As it has been touted as “open innovation model”, firms                have  been  encouraged  to  establish  networks  and  relationships  with  other  agents  of  the                innovation  system  such  as  customers,  research  institutes,  Universities  and  others  to                complement their resources and internal capacities with outside ideas [21], [10].                      Sánchez-González  et  al.  [27]  assessed  cooperation  with  customers  and  how  it  affected                firms’ innovation tendencies. Using knowledge generated to represent innovation, they found                that firms cooperating with customers induced firm to increase investments oriented towards                expanding the technological knowledge base within the firm's technological domain effectively                reducing  their  technological investments. Consequently,  they found  that  this cooperation  had                directs effects on firms’ economic returns engineered from the sales of new products new for the                market endowing firms with continued competitive edge. This was concurred by [15], [32].                      Based  on  the  above  discussed  literature,  which  endorses  both  the  relevance  of  public                funding to cooperation of firms [17] even as there are some rejections [4], the author is of the                notion  that  funding  for  industries  does  support  and  eases  the  expenditure  set  aside  for                innovation by firms even as cooperation is believed to generate knowledge for firms quest for a                strong competitive advantage and innovation. On this note it is hypothesised that “Public funds                invested  are  significant  indicators  for  stimulating  cooperation  with  industrial  partners-                competitors and suppliers”-H1.                      Having known the theoretical support and rejection for public funds on cooperation and                cooperation on knowledge [27], which has been represented as knowledge by some authors,                some results of cooperation in research on knowledge have been held as quite uncertain [18].                The  open  innovation model  equally  stresses  the  significant  effect  of  collaboration  with  other                partners of the firm on the knowledge generated and innovation tendencies of firms [22] hence,                second hypothesis [H2] is created such that “Firms’ cooperation with other industrial partners-                competitors and suppliers- is significant to knowledge acquired for innovation”-H2.                      Upon the creation of the previous hypothesis, and the literature on impact of collaboration                on knowledge sourcing [27], [18], essence of knowledge acquired], it is further hypothesised                that  “Public  funding  of  firms  significantly  affects  the  sourcing  of  knowledge  for  innovatory                needs”- H3 whilst “Cooperation as a variable is a significant moderator to knowledge sourced                upon investment of public funds”-H4. The goal of the paper, however, is to reveal the essence of                public  influence  on  cooperation  and  knowledge  sourcing  and  establish  the  moderator  role                played by co-operation in effectively utilising public funds for acquisition of knowledge by firms.                  3  Data and Methodology                       Data from Community Innovation Survey (2012-2014) was resorted to for this analysis.                CIS data represents a survey designed to reveal information on the sectoral innovation activities                by the enterprises involved, activities undertaken, the funding sources and the inherent location                of such firms. This questionnaire was utilised for the purpose of the research as used by [30] and                [11]. The data focused on 15,777 local, national and EU headquartered manufacturing firms in                both Spain and Portugal with a real Gross Domestic Product per capita (PPP) of €24500 and                €11,800  respectively  as  of  2017  as  reported  by  the  European  Commission.  Research  and                Development  intensity  has  largely  been  shown  to  affect  cooperation  in  contemporary  times                                                               20","These countries were selected because of their reported below-par cooperation intensity levels                in  with  Universities  and  industries  [28]  and  innovation  performance  in  recent  years  despite                their  glowing  potential  reported  by  [30]  and  European  Commission  as  of  2017.  It  is  even                imperative because of the strong need for cooperation and research and development intensity                required in generating intellectual capital to expedite regional growth.                      Despite the argued philosophical bias and supposedly weak external validity preached by                critics,  to  reveal  the  moderator  role,  the  study  resorted  to  the  use  of  Structural  Equation                Modelling  (SEM)  analysis  to  develop  a  model  to  analyse,  test  and  confirm  the  above-stated                hypothesis. This model was selected due to its assumptions of free distribution, its analytical                capability of revealing moderating and mediatory roles and its compound of analytical tools that                suited  this  analysis  [20]  as  well  as  its  capacity  to  general  compute  models  in  a  multiple                regression.                                         Figure 1: SEM structure for both Portugal and Spain                                 Source: Authors’ own formation.                                      Table 1: Reliability and internal consistency tests [first part]                                               P_Funds   Knowledge   Co_ent    Co_Supp   Co_Client   Co_Com                                               Spa   Por   Spa   Por   Spa   Por  Spa  Por  Spa  Por  Spa  Por                Composite Reliability         0.8   0.6   1    0.9   1    1    1    1    0.8   0.7   1   1                Cronbach alpha                0.6   0.2   0.9   0.9   1   1    1    1    0.5   0.4   1   1                Average Variance extracted    0.5   0.3   0.6   0.4   1   1    1    1    0.7   0.6   1   1                [AVE]                Full Collinearity VIF         3.1   1.2   1.6   1.2   1   1   1.6   1    1.4   1.2   1.3   1.2                Source: Author’s own.                                    Table 2: Reliability and internal consistency tests [second part]                                                    Co_Rsrch    Co_Uni      Co_op      Co_Cons     Co_op*P                                                   Spa   Por   Spa   Por   Spa   Por   Spa   Por   Spa   Por                Composite Reliability               1     1     1     1    1     1     1     1    0.8   0.6                Cronbach alpha                      1     1     1     1    1     1     1     1    0.6   0.2                Average variance extracted [AVE]    1     1     1     1    1     1     1     1    0.5   0.3                Full Collinearity VIF              1.9   1.3   1.6   1.2   2.8   1.2   1.5   1.2   3.1   1.2                Variables used: P_funds: Local, National, European Union funds and Funding from EU's 7th Framework Programme for                RTD; Co_ent- Cooperation with other enterprises within enterprise group; Co_Supp- Cooperation with Suppliers of                equipment; Co-Clie- Cooperation with clients or customers from the private sector and the public sector; Co_comp-                Cooperation with competitors or other enterprises; Co_cons- Cooperation with consultants and commercial labs; Co_Uni-                Cooperation with Universities; Co_Rsrch- Cooperation with Government, public or private research institutes; Co_op- Co-                operation arrangements or innovation activities. Knowledge- knowledge sourced from within the enterprise or enterprise                group, suppliers of equipment, materials, components, or software, clients or customers from the private sector, clients or                customers from the public sector, competitors or other enterprises in your industry, consultants and commercial labs,                universities or other higher education institutions, government, public or private research institutes, conferences, trade                fairs, exhibitions, scientific journals and trade/technical publications, professional and industry associations. Spa- Spain,                Port- Portugal.                                                               21","4  Results and Analysis                       To  establish  the  fitness,  reliability  and  the  internal  consistency  of  the  model  and  the,                validation analysis was carried out composing of discriminant validity, composite reliability and                Cronbach alpha for the test of construct validity. To measure error and composite weights, the                construct  reliability  uses  the  Cronbach’s  alpha  coefficient  for  estimation.  A  Cronbach’s  alpha                with the value of equal to or greater than 0.7 is acceptable [16]. Convergent validity, the extent                to which the measurement items together explain the construct they represent in the structural                model [16] is assessed with Average Variance Extracted (AVE) and composite reliability (CR)                using  a  minimum  loading  of  0.50  and  maximum  of  0.70  respectively  [16,  20].  The  model                however, satisfied all these conditions.                                              Table 3: Estimates and test of Hypothesis                      Hypothesis    Beta (P-value)    Result        Hypothesis     Beta (P-value)   Result                                   Spain   Portugal                               Spain   Portugal                H1a   P_funds–    0.23     0.04     Accepted  H2a   Co_Sup-      0.10     0.42     Accepted                      Co_Supp     (0.0)***   (0.0)***               Knowledge    (0.0)***   (0.0)***                H1b  P_funds-     0.18     0.05     Accepted  H2b  Co_comp-      0.04     0.09     Accepted                      Co_comp     (0.0)***   (0.0)***               knowledge    (0.0)***   (0.0)***                H3    P_funds-    0.33     0.20     Accepted  H4    P_funds–     0.07     0.05     Accepted                      Knowledge   (0.0)***   (0.0)***               Co_op-       (0.0)***   (0.0)***                                                                    Knowledge                 Source: Authors’ calculation.                Legend: * Significant at p<0.10, **Significant at p< 0.05, ***Significant at p> 0.01                       From  table  3,  it  could  be  observed  that  in  both  Spain  and  Portugal,  public  funding  is                recognised as a significant influencer of cooperation among all partners of firms in the industry.                However, it could be observed that the degree to which public funds affects firm’s cooperation                with  industrial  partners  (both  with  suppliers  and  competitors)  was  higher  in  Spain  than  in                Portugal.  This  implies  that  Portugal  relies  more  on  public  support  in  intensifying  their                cooperation centres initiatives with competitors and suppliers than required in Spain. This could                be held as a preference for potential usage of business expenditure in cooperation initiatives or                an  over-reliance  on  public  support  by  Portugal  which  could  also  be  an  indication  of  market                failure[22]. This effectively accepts H1 concurring the work of [24].                      Furthermore, the significance of cooperation of selected industrial partners on knowledge                acquisition  of  firms  was  also  found  significant  among  all  industrial  partners  considered-                suppliers,  research  centres,  Universities,  consultants  and  laboratories,  competitors  and  other                firms  within  the  same  industry  for  both  countries.  This  points  out  a  very  salient  source  of                information generation in the Manufacturing sector inadvertently highlighting the pillars that                could generate competitive advantage in an intellectual sense in Portugal and Spain even though                is comparatively less potent in Spain. It is even more imperative as intellectual capital has been a                significant driver of regional growth and global competitive strength in the knowledge economy                This effectively accepted H2 in both Spain and Portugal concurring to findings of research with                similar variables [14], [19].                      In table 3, public funding was also found to significantly impact the sourcing of knowledge                for innovatory needs in both Spain and Portugal thereon accepting the above stated H3. This                research closely affirms the research of [26]. Furthermore, cooperation as a moderator of the                relationship between public funding of firms and knowledge sourced by firms for innovation                was  found  to  be  significant  as  well  for  both  countries  considered  as  well,  however,  the  beta                coefficient of 0.07 for Spain and 0.05 for Portugal evidenced a much effective role of cooperation                in  metamorphosing  public  funds  for  knowledge  generation  in  Spain  than  in  Portugal  even                though  it  very  low in significance. These  results  also accepted  H4 stated  above  and  research                direction of [5].                                                                  22","5  Conclusions                       The  study  set  out  to  reveal  the  impact  of  public  funds  on  cooperation  and  knowledge,                cooperation with industrial partners on knowledge generation and how cooperation moderated                the transformation of such funds in to knowledge acquired by firms for innovatory purposes. H1                was accepted in both Spain and Portugal affirming the relevance of public funds in cooperation                with industrial partners in the Manufacturing industry of both countries. However, the weights                of  the  impact  were  higher  in  Portugal  than  in  Spain.  It  is  recommended  that  appropriate                measures of transparency and control are duly endorsed to follow up on the usage vs results                comparison of the funds provided to firms in Spain owing the direct relevance of funding.                      H2 was also accepted confirming the significance of cooperation with industrial partners                on knowledge acquired by firms for innovatory needs. Cooperation with industrial partners has                much  higher  significance  on  knowledge  acquisition  in  Portugal  than  in  Spain.  Owing  to  the                overwhelming evidence of research of cooperation on knowledge generated for innovation, it is                recommended that a deeper focused is placed on expediting and intensifying connections among                firms  via  for  example,  public  science  and  technology  events,  to  appropriate  the  maximum                returns of cooperation. H3 was accepted in both Spain and Portugal even as it was found more                relevant in Spain that in Portugal. This entrenched the relevance of connection between public                funding and knowledge acquired by firms for innovation. It is however recommended that firms                engage  active  ex  ante  measures  to  control  for  the  usage  and  proper  assignment  of  funds  to                assigned knowledge generation sources. Ex post control measures is also recommended to be                pursued  to  ensure  an  even  more  direct  relevance  and  efficient  use  of  funds  for  knowledge                engaging activities. Lastly, H4 was also accepted as cooperation was assessed and found as a                significant moderator of public funding and knowledge acquired by firms for generating product                and process innovations in both countries. Firms in Portugal are recommended to attach higher                importance  to  the  taxpayers’  fund  and  engage  actively  in  cooperation  and  explore  more                platforms  for  engagement  to  intensify  cooperation  within  industries  to  even  higher  effects                whilst the Government and supranational bodies are equally admonished to eliminate red tapes                to financing and even create wider platforms for access to finance whilst supplementing it with                active  ex  post  control  measures  and  redirect  funds  in  line  with  need  and  significance  to  the                sectors in need. Further research could use a panel data to cover a wider range and also provide                a gap period for input variables to transform into the selected output variables.                  References                 [1.]  AERTS, K., \& SCHMIDT, T. (2008). Two for the price of one? 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Technovation, 30(3), 181–194.                                                                                                                            25","Organizational-legal Form of Czech Hospitals –                            Analysis of the 2006 ´Window of Opportunities´                                                    ANGELOVSKÁ Olga                            Faculty of Social Sciences, Charles University, Institute of Sociological Studies, Czech Republic                                                   olga.angelovska@fsv.cuni.cz                 Abstract                 A  key  feature  of  Czech  health  care  reform  after  1989  was  the  principle  of  de-monopolization  and                decentralization.  At  the  same  time,  the  health  care  reforms  focused  on  the  privatization  of  health  care                facilities  and  health  care  providers.  Therefore,  the  paper  deals  with  the  efforts  to  change  the                organizational-legal status of hospitals after 2000, i.e. after a reform of the state administration occurred.                The  paper  uses  the  multiple  streams  framework  to  describe  successful  process  in  giving  a  legislative                anchor  to  the  new  organizational-legal  form  of  hospitals  and  to  identify  the  most  important  policy                entrepreneurs.  It  maps  all  three  streams  (policy,  politics  and  problem  streams)  and  uses  a  broader                concept  including  agenda  setting  as  well  as  decision-making  process.  A  policy  window  opened  and                allowed a policy change in 2006 when 245/2006 Coll., on Public Non-Profit Institutional Medical Facilities                passed. The research adopted a single-case study design. Data were obtained through document analysis                (law  proposals,  resolutions  of  Constitutional  Court,  stenographic  records,  strategic  documents  etc.).                Examined period covered years 2002 – 2006. Findings confirmed the assumption that all three streams                play  a  role  for  agenda  coupling  while  in  case  of  a  decision  coupling,  the  political  stream  is  the  most                important.                 Keywords: multiple streams framework, hospitals, health care system                JEL Classification: H41, I12, I18                    1  Introduction                       Health  systems  have  had  to  cope  with  many  changes  of  socio-economic  and  political                environment such as pressures to contain costs, changes within the welfare state [7, 26]., and                globalization processes [11, 35]. The development of the Czech health care policy after 1989                corresponded to the development in the region of Central and Eastern Europe that experienced                a  major  transformation  of  health  care  as  a  consequence  of  society-wide  changes  [33].  The                original Semashko model (the concept of health care according to the model of the USSR see, for                example  [27])  allowing  the socialist  state  to  legally  and  in fact  dominate healthcare  [31]  has                become the subject of transformation. Its aim was to end the centralized organization of Soviet-                type health services and to reorient towards the Bismarck model [23]. A key feature of Czech                health care reform after 1989 was the principle of de-monopolization and decentralization. At                the same time, the health care reforms focused on the privatization of health care facilities and                health care providers [4]. The Czech health policy became the arena of disputes between the                advocates  of  maximum  use  of  market  principles  in  the  health  sector  and  the  advocates  of  a                concept of health services as public services. [19]                      The  contribution  concentrates  on  efforts  to  change  the  organisational-legal  status  of                hospitals  after  2000  when  a  reform  of  the  Czech  state  administration  occurred.  There  were                several attempts to change the organisational-legal structure of hospitals but only one of them                led  to  the  successful  approval  of  Act,  namely  Act  No.  245/2006  Coll.  on  Public  Non-Profit                Institutional Health Facilities. This law was abolished after five years with the justification that                in  those  five  years  of  its  validity  the  norm  had  never  been  used.  Yet, it  was  the only  agenda                setting that led to a finished decision-making process. The aim of the contribution is to explain                successful process in giving a legislative anchor to the new organisational-legal form of hospitals                                                                 26","and to identify the most important policy entrepreneurs. The paper demonstrates the use of the                multiple streams framework for the case of health policy in the Czech Republic.                  1.1 The Multiple Stream Framework                      There exist different approaches to analyse agenda setting and policy change. Concerning                the topic of the successful policy change we may consider the advocacy coalition framework, the                punctuated  equilibrium  models  or  multiple  streams  framework.  The  advocacy  coalition                framework focuses on competing coalitions which compete for their position within the system                and in the same time they revise their strategic positions. [32] The coalition itself is consistent                due to the “belief system” (for more details see [32]). The advocacy coalition framework suits                better  to  explaining  policy  stability  than  policy  change.  It  also  has  problems  to  explain                temporary  alliances  that  are  based  on  self-interest  and  eliminate  core  beliefs.  [7]  The                punctuated  equilibrium  model  [2]  is  based  on  presumption  of  long  period  of  policy  stability                which  are  punctuated  by  short  intense  periods  of  change.  Those  periods  give  actor  the                possibility to use new ways to frame and solve policy problems. In consequence of the limited                resources the actors are not available to deal the full range of ideas and policy problems and                they tend to promote just small number of them. In their original approach the author didn’t                consider the role of political parties and also the limited universality of the model was criticized.                [8]                      The multiple stream framework (MSF) is more complex in comparison with the previous                two. MSF was originally developed by John Kingdon to explain how different streams (policy,                politics and problem streams) couple and open a policy window that allows a policy change. [22]                Kingdon’s MSF, published in Agendas, alternatives and public policies (1984), is considered as                one  of  the  significant  contributions  to  public  policy  research  [5],  particularly  in  the  field  of                agenda setting. Kingdon used his theory to explain the functionality of the federal-level policy                making  process  of  the  United  States.  His  explanation  of  the  federal-level  agenda  in  the  US  is                based  on  three  categories  of  independent,  albeit  somewhat  interconnected,  variables  whose                interactions can lead to a “window of opportunity” for the agenda setting.                      While being a theory of agenda setting in the US, Kingdon’s theory has been also applied to                implementation processes [1, 18, 21, 25, 36]. Following authors have often applied MSF to other                levels of public policy in different countries and across a range of fields from health, education,                legislation  to  e.g.  telecommunications  or  energy  policy  [10,  16,  20,  28,  30].  Oftentimes,  the                authors agree that the expansion of the studied areas requires adaptation of the MSF as it is                applied to a different area than was originally intended by Kingdon [1, 16, 18, 21, 25, 36]. The                contribution uses modified MSF which broadens the concept by including agenda setting as well                as  decision-making  process  (for  more  see  [16]:36).  In  decision-making  process,  the  three                streams  coupe  again  but  the  decision  window  of  opportunity  usually  opens  within  political                stream.                                                                                        27","Figure 1: The modified multiple streams framework                                           Source: [17]:445.                  2  Methodology                       The methodology reflects qualitative nature of the research. Most studies within MSF are                based  qualitatively  [28].  Examined  period  covers  years  2002  –  April  21,  2006.  In  2002,  the                sector  of  hospitals  experienced  significant  changes  due  to  public  administration  reform.                Therefore,  the  year  2002  was  selected  as  a  starting  point  for  the  analysis  as  the  year  when                agenda  setting  phase  started.  In  April  2006,  Act  No.  245/2006  Coll.  on  Public  Non-Profit                Institutional Health Facilities passed and finished decision-making phase.                      The research adopted a case study design [12] with the aim to gain in-depth insight in the                political processes surrounding the new organisational-legal form of hospitals. The method of                process tracing is applied. [6] Data were obtained through content (thematic) analysis of media                and legislative documents. Media analysis covers five-year period January 2002 to December                2006 and focuses on 17 periodicals (including 6 nationwide dailies, 3 economic and political                titles and 8 health sphere titles). Articles were obtained in the Newton Media Search electronic                archive, and the search was based on two core search terms “hospital” and “non-profit”. There                were 1436 articles choose as relevant to the topic, and so to be researched.                      The direct legislative data were analysed including law proposals (Bill 810/2004 on Public                Non-Profit  Institutional  Health  Facilities,  Act  No.  245/2006  Coll.  on  Public  Non-Profit                Institutional Health Facilities, Act 258/200 Coll. On Public Health Protection, Act No. 250/2000                Coll., on the Municipal Budgetary Rules) and Constitutional Court resolution (Pl.ÚS 51/06 from                27. 9. 2006). The other documents covered stenographic records, strategic documents (mainly                of the Ministry of Health), political documents (e.g. the partisan document “Blue chance” made                by ODS).                      Analysed indicators follow multiple streams theory as defined by Herweg [16]. Within the                problem stream, we work with both, the attention and interpretation (the topic to be stressed                out by the actors to catch attention, in our case hospitals´ debt, risk of privatisation as well as                framing  of  the  change  of  the  new  organisational-legal  form  of  hospitals).  The  policy                entrepreneurs were identified according their attempts to raise attention to the problem or to                change the framing. Within the political stream the main attention is paid to parties and interest                groups  (the  third  indicator,  the  mood  of  electorate  was  excluded  due  to  a  lack  of  data  and                unreliability of pre-election research). Within the policy stream the policy community and policy                primeval  soup  are  important  for  forming  proposals  and  alternatives.  In  this  stream,  policy                                                                 28","entrepreneurs promote their ideas within policy and expert community to gain support for their                alternatives.                      Following Herweg’s [16] distinction between agenda setting and decision-making stages,                in  agenda  setting  stage  the  term  “policy  entrepreneur”  is  replaced  by  term  “political                entrepreneur” to stress the fact that the insider has a higher possibility to couple streams.                   3  Results                       The following section introduces the focusing event and then it is set up according the                categories of Multiple Streams Framework – problems, policies and politics. It covers events and                decisions within each of these streams and maps their contribution to the coupling into window                of opportunity.                  3.1 Focusing event - Czech hospitals within public administration reform                      Transformational changes in health took place very quickly at the beginning of the 1990s.                The  emphasis  was  put  on  the  denationalization  of  health  care,  demonopolisation  and                decentralization, while development of the legal framework of health law was characterized by                provisional  solutions  that  however,  persisted  for  a  long  time.  Already  since  1991,  legal                amendments  have  been  made.  They  should  have  also  allowed  the  privatization  of  medical                facilities and in 1992, intentions of privatization of all hospitals were formulated with exception                of large ones. The expected result of this step was that hospitals became in an organizational                legal form of business companies. Privatization of hospitals was stopped in 1996 because of the                risks of serious consequences. [3] Only a few dozen small hospitals have been transferred to                limited liability companies.                      The process of a non-conceptual approach in relation to the status of hospitals continued                by a reform of public administration. The first two stages of the public administration reform                launched  in  1998,  with  the  aim  of  changing  the  local  government  on  the  principle  of                decentralization  and  subsidiarity  became  a  significant  incentive  for  the  change  in  the                organizational legal status of hospitals. In the first stage 14 regions were established as higher                territorial  administrative  units  which  have  started  their  activities  since  2001.  In  the  second                phase, there was a fundamental change in the functioning of the public administration at the                lowest level, when the municipalities were divided into three levels and, as a result, the district                offices  ceased  to  end  in  2002.  District  authorities  were  at  that  time  owners  and  founders  of                district hospitals, as of 31 December 2002, 82 hospitals (out of a total of 203 hospitals) with                about half of the bed capacity in the Czech Republic [29]. According to the fact that all assets of                state contributory organizations established by district authorities were transferred at the end                of the year 2002 to the regions, all those hospitals became the property of the newly established                regions. It makes regions responsible for accessibility of public service – hospital health care                [13]. The government on the basis of the Czech Constitution (Article 101 (4)) could not interfere                in activities of regions [15]. The legislative preparation for public administration reform was                considerably underestimated in hospital care [14] and the decentralization reform steps have                led to uncertainty and inconsistency of the future development of the organizational legal form                of former district hospitals. Actors of public administration and other health policy actors often                politicized and medialized this issue and use such situations in political rivalry (e.g. the election                campaign in November 2004).                      Regions also took over hospitals’ commitments which at the time included considerable                debts [34]. Prior to the transfer itself, on December 10, 2002, the Chamber of Deputies discussed                the Government's Report on the state of indebtedness of state hospitals, the settlement of these                debts, and the legal transfer of hospitals to the region. The Chamber of Deputies assigned the                task to the Ministry of Health to submit a proposal for a solution within two months. Thus, the                Ministry presented the Thesis Concept of Medium-Term Policy (Thesis 2003) including the plan                of the bill on healthcare facilities and their management. The Chamber of Deputies unlike the                government refused the document.                                                               29","Despite the previous claims, the state only partially eliminated hospitals’ debt, about 60% [24].                The regions themselves could not use other gained \"district\" assets for debt relief because it                could not be used for other purposes. Furthermore, an unused property had to be offered back                to the state ownership. Hence, the regions began looking for other solutions. Act No. 250/2000                Coll.,  On  Budgetary  Rules  of  Territorial  Budgets,  allowed  regions  to  set  up  their  own                organizational units whose legal form ranged from contributory organizations to community-                based companies or business companies. It was in the transformation of hospitals to business                companies that most of the regions (after elections in 2000 under the right-wing party ODS) saw                the solution of the economic problems of the hospitals. The proponents considered the transfer                to  the  joint  stock  company  as  the  most  appropriate  legal  form.  This  approach  was  strongly                criticized  by  the  ruling  CSSD  (left-wing  party).  They  pointed  out  that  the  growth  of  hospital                autonomy goes together with the danger of limiting the link to the public sector, reducing the                role of the state and its ability to influence the development of hospital care.                  3.2 Agenda setting                      The topic of the hospital sector had been returning to the agenda since the late 1990s due                to its repeated indebtedness. In the end of the nineties the problem stream had begun to shape                again  along  with  the  public  sector  reform.  According  to  Multiple  stream  framework  the                community  has  to  be  convinced  that  there  exists  a  problem.  While  at  the  beginning  it  was                framed as a problem of indebted hospitals (till the middle of 2003 this frame prevailed), after                the final stage of the reform and hospitals transfer to the regions, the problem started to be                reframed  and  the  organisational-legal  form  was  brought  to  the  agenda.  It  had  received  a                considerably  larger  attention  as  a  result  of  the  reform  of  the  public  administration  with  the                abolition of districts and the constitution of regions in 2002.                      Although the Ministry of Health already included the bill on Health Care Facilities among                their goals in 2003, media and politicians started to deal with the issue of the organisational-                legal form of hospitals immediately when the regions dominated by right-wing regional council                chairmen  began  transferring  hospitals  to  joint-stock  companies.  That  was  the  focusing  event                that attracted the attention both politicians and the public. Debate had shifted from the issue of                debts to the issue of organisational-legal form. Despite the consensus that the form of budgetary                and contributory organisations was outdated, policy entrepreneurs promoted two significantly                different framings. The first one, advocated by regional council chairmen, presented the join-                stock companies as the best solution. The second one, held by left-wing government, stressed                the risk of privatization and low access to health care and gave preferences to the non-profit                form.  The  debate  was  supported  by  cyclical  events,  concretely  regional  elections  and  Senate                elections in 2004. At the same time, the topic of organisational-legal form of hospitals was used                for  election  struggle.  Prime  Minister  Gross  retrospectively  considered  the  health  issues  as  a                poorly  chosen  topic  for  the  regional  elections.  His  government  as  well  as  latter  Paroubek’s                government emphasized the creation of a law on healthcare facilities in their policy statement of                government.                      The chances of gaining political attention and support rise together with the preparedness                of  the  appropriate  solution.  According  the  multiple  stream  framework  there  may  exist  pre-                formulated policy solutions that are considered by government as appropriate ones and within                the policy stream they may cut short political and experts disputation on the suitable policy.                      In 2004, proposal on Public Non-Profit Institutional Health Facilities was initiated by the                Czech Medical Chamber (CMC). Because CMC cannot propose a law in the Czech Parliament, it                was  subsequently  developed  by  the  Ministry  of  Health  and  proposed  as  the  parliamentary                initiative  (proposed  by  MP  Krákora).  In  that  time  the  proposal  had  been  already  widely                discussed.  However,  in  the  end  of  2004,  the  Minister  of  Health  was  not  satisfied  with  the                proposal and announced an intention to suggest her own version.                      Beside, Julínek (ODS, the right-wing party) presented his idea of the health care system                with  hospitals  as  the  joint-stock  companies  (the  document  Blue  chance).  He  endeavoured  to                bring his ideas to life when he became the Minister of Health in 2008. There was also World                                                                30","Bank  expert  group  invited  (lead  by  Mukesh  Chawla)  but  there  had  not  been  published  any                findings.                      Unlike the policy stream with the dominant role of argumentation, the political stream is                based more on negotiation and power-play. The political stream reflects the political mood and                openness  to  change  that  reflects  the  current  political  climate  in  society  (including  personnel                changes in executive and legislative power, interest group campaigns).                      The  election  of  2002  was  won  by  the  CSSD,  which  had  101  votes  in  the  Chamber  of                Deputies with two other coalition parties. After the elections to the Senate in 2004, the number                of coalition senators decreased. In the same year votes of the parties of the government coalition                also dropped significantly in the regional elections. Due to delay in the preparation of Act on                Public  Non-Profit  Institutional  Health  Facilities  as  well  as  the  efforts  of  the  governors  to                accelerate the transfer of hospitals to the joint-stock companies, the first attempt using blocking                mechanism was made to stop the transfer of hospitals. It was incorporated into so called the Act                on  Noise,  but  it  was  not  approved.  Both  the  Senate  and  the  President  used  their  veto.                Presidential veto was not overvote by Chamber of Deputies.                      All three streams succeeded to couple in December 2004, when the first reading of the bill                took place in the Parliament despite governmental objections.                 3.3 Decision-making                      Decision-making  period  lasted  almost  one  and  half  year.  The  problem  stream  had  not                changed in fact - the key problem laid in unsatisfactory organisational-legal form of hospitals.                The general argumentation started to be stronger than in agenda setting. Moreover, quite often                left-wing  politicians  and  some  of  the  actors  from  the  medical  sphere  stressed  the  risk  of                transformation of hospitals into the form of business companies. They pointed out the risk of                lower access to the medical care and misappropriation on the hospital property. The right-wing                politicians  framed  the  problem  as  a  re-nationalisation  of  property  as  in  the  1950s  when  the                Communists regime started.                      Within the policy stream the parliamentary initiative continued as Bill no. 810 on Public                Non-Profit  Institutional  Health  Facilities.  But  in  2005,  the  new  Minister  of  Health  Rath  (ex-                president of CMC) came up with a new proposal that provoked protests from many actors. The                main reason was the planned compulsory transfer of former district hospitals in a non-profit                form. In addition to that, regional council chairmen claimed their intention to work on their own                proposal in favour of joint-stock companies in January 2006.                      The political stream played the key role in decision-making process thanks to the current                composition  of  parliament.  Unfinished  Act  on  Public  Non-profit  Institutional  Health  Facilities                and ongoing transfer of hospitals evoke another attempt to stop the transfer of hospitals in the                legal form of joint-stock companies. Deputy Chairman of the Chamber of Deputies Filip (KSČM-                communist  party)  proposed  second  blocking  mechanism  as  part  of  the  amendment  to  Act                258/2000 Coll., On Public Health Protection. Despite the Senate veto and Presidential veto, the                Act was passed by the Parliament in August 2005. But it did not have a real effect because most                of  the  hospitals  had  already  been  transformed  into  the  joint-stock  companies.  Also,  regional                council  chairmen  immediately  reacted  with  announcement  that  they  filed  a  complaint  to                Constitutional Court. Some regions were about to use legal loopholes to avoid the concept of                \"change of legal form\" by setting up new business companies.                      In relation to hospitals, both governments (Prime Ministers Gross in 2004 and Paroubek                in 2005) in their program declarations emphasized a creation of a law on healthcare facilities                and  a  creation  of  a  network  of  healthcare  facilities. The  Bill.  810  passed  but  the Chamber of                Deputies had to overvote the Senate veto (April 2006) and the President veto (May 2006).                      After one and half year since its first reading in the Parliament, i.e. since the beginning of                decision-making stage, the three streams succeeded to be coupled in May 2006.                                                                     31","3.4 Discussion                      Despite later attempts to change the organisational-legal status of hospitals and two policy                window openings (in 2008 and 2017) the analysed situation was the only one which led to the                successful  end  of  the  whole  process  including  agenda-setting  as  well  as  policy-making.  The                analysed process of approving the Act on a new organisational-legal form of hospitals confirmed                the usefulness of distinguishing between agenda coupling and decision coupling as Herweg [16]                proposed. In case of agenda-setting phase, all streams played a role for agenda coupling anyway                the  window  of  opportunity  opened  within  the  problem  stream.  The  problem  window  opens                when  the  problem  threatens  the  policy  maker´s  re-election.  The  emphasis  on  framing  the                problem increased from both sides of the political spectrum by upcoming elections (in 2004)                when the new organisational-legal form started to be the subject of sharp discussions in media                and parliament discussions. The policy stream played a significantly lower role because there                did not exist a prepared proposal and it took two years to offer one that was initiated by the                interest group outside the political parties.                      The political stream became the most significant in the decision coupling because of one                vote majority in the parliament. Its importance was obvious when Senate and later President                veto were outvoted. The window of opportunity opened within the political stream, and even                though the Bill within the decision coupling underwent significant changes, it was approved.                      The decision-making and agenda-setting processes differed in the role of entrepreneurs                because policy and political entrepreneurs use different strategies. The whole process took a                long time, so it was possible to identify the entrepreneur who took part in it as both, a political                entrepreneur and a policy entrepreneur. Concretely, the Minister of Health (after 2005) played                this  specific  role  because  he  was  previously  the  Head  of  the  Czech  Medical  Chamber,  the                institution that made an original proposal of Public Non-Profit Institutional Health Facilities.                  4  Conclusion                       In this article, the case study shows how the fields as health care can be explained through                multiple streams framework and how the concepts such as streams, policy windows and policy                entrepreneurs  can  be  useful  for  interpretation  of  the  Czech  case.  It  is  valuable  within  the                framework  to  distinguish  the  agenda-setting,  and  decision-making  process  as  Herweg  [16]                proposed. Although the framework offers a broad and various approach to analysing the policy                change, it is not comprehensive. 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European Journal of Political Research, 54, 412–418.                                                                                                                        34","What Matters in Social Media Engagement?                              Czech Social Service Organizations´ Example                                                     BACHMANN Pavel                                             University of Hradec Králové, Czech Republic                                                     pavel.bachmann@uhk.cz                 Abstract                 The  social  media  effect  is  greatly  affected  by  an  ability  of  organization  to  engage  its  community  and                stakeholders.  Therefore,  the  study  primarily  aims  on  communication  published  on  organization´  social                media and on engagement related to the nature of service, respectively related to the content type of post.                At  the  first  research  phase,  the  research  sample  is  composed  of  185  nonprofit  nongovernmental                organizations  from  the  field  of  social  services  and  located  in  the  Czech  Republic.  At  the  next  research                phases,  an  in-depth  analysis  of  550  Facebook  posts  published  by  55  organizations  is  conducted.  An                engagement rate is measured with a set of metrics, including responsiveness, involvement, and virality.                Results showed that social service organizations use Facebook as their primary social medium. Moreover,                stronger  statistical  differences  in  engagement  were  found  according  to  the  organization´  primary                orientation than according to the content type of posts. Statistically higher engagement rate was recorded                in organizations oriented on children and youth, homeless people, and physical disabilities. Vice versa, the                lower  engagement  was  found  in  organizations  dealing  with  family  problems,  mentally  disabled  or                integration of foreigners.                Key words: Social Media; Facebook; Social Services; Nonprofit Organization; Engagement                 JEL Classification: H20, L31                    1  Introduction                      “Social media are not tools; they are collections of people. People ready to be engaged,                ready to take action, ready to be inspired” [9:13]. Social media (SM) aren’t just a new piece of                technology; they can also be considered as a new form of engagement of nonprofit´ stakeholders.                Harnessing  this  power  can  have  dramatic  effects  on  non-profit  outreach  in  marketing,                communications,  and  fundraising  initiatives  [9].  SM  facilitate  dissemination  and  sharing  of                information  to  organizational  stakeholders;  they  are  mainly  represented  by  platforms  as                Facebook, Instagram, Twitter, or YouTube, communication technologies as Skype or SecondLife,                and professional tools as LinkedIn or ResearchGate [2-4]. These SM are greatly useful to enhance                mutual communication between the organization and its local community including employees,                volunteers, donors, politics, partner organizations and other stakeholders.                 1.1 Current research on social media use in non-profit sector                      SM  have  commonly  begun  to  be  used  in  a  various  field  of  governmental  and  private                nonprofit  sector.  Prior  research  orientated  on  SM  use  by  nonprofit  organizations  started  by                investigation  of  what  organizations  offer  on  their  SM  presentations  in  2009  [13].  In  2012,                Lovejoy and Saxton [10] developed a model for coding content published through SM; this model                classify  content  on  three  main  types:  (a)  information,  (b)  community  (including  giving                recognition  and  thanks,  acknowledgement  of  current  and  local  events,  responses  to  reply                messages, response solicitation), and (c) action (including promoting an event, donation appeal,                selling a product, call for volunteers/employees, lobbying and advocacy, join another site or vote                for organization, learn how to help). In 2014, Cho, Schweickart, Haase [4] identified levels of                community  engagement  where  likes  reflected  a  low  engagement  level,  sharings  reflected                moderate engagement level, and finally comments reflected high engagement. In 2016, Huang,                Lin,  and  Saxton  [6]  criticized  one  way  informational  message  due  to  its  ineffectiveness  and                                                               35","recommended  dialogic  communication  between  nonprofit  organization  and  stakeholders.                Finally,  in  2017,  Kim  and  Yang  [8]  in  their  study  concluded  that  different  communication                (message)  generate  different  behaviour  of  users.  Sensory  and  visual  message  generates  like;                rational and interactive message generates comment, and sensory, visual, and rational generates                sharing.                      Moreover, various conceptual frameworks were designed to capture an engagement on                Facebook page related to the environment of business [7] and public organizations [3]. Jan H.                Kietzmann at al. [7] designed a honeycomb framework to investigate facets of the social media                from  user  experience.  It  dealt  with  following  aspects  (blocks)  of  social  media:  identity,                conversations, sharing,  presence,  relationships,  reputation, and  groups.  Each  block  comprises                (1)  specific  facet  of  social  media  user  experience,  and  (2)  its  implication  for  firms.  The                framework  is  frequently used for  description  of  Facebook  and  Youtube  engagement.  Bonsón,                Royo, and Ratkai [3] developed metrics as popularity, commitment, virality for Facebook page                total engagement measurement in public sector.                      Regarding the geographical location, the highest number of research studies in the field                was conducted in the U.S.A. and Western Europe. However, only a limited amount of studies                concentrated on research in area of engagement by the Facebook sites. Regarding specifically                situation of Central Europe, there were 156 research studies in Web of Science relevant to SM or                social networking sites topic from Central and Eastern European´ (CEE) authors published from                2015 to 2019. Analysis of these studies showed that majority of them are dealing with business                economics, business communication, or educational research. However, only Macek, Mackova,                and  Kotišová´  study  [11]  dealt  with  the  nonprofit  sector,  specifically  with  structure  of  civic                practices with respect to social and political contexts.                      Nowadays,  despite  of  the  high  impact  of  previous  research,  it  should  be  stated  that                frameworks are, at least in some sense, a bit outdated. Application of Kietzmann´ [7] framework                is limited by his main orientation on business sector and an encounter of Bonsón, Royo, and                Ratkai´ [3] metrics is obsolete due the Facebook revision of engagement rate. However, due to                relative proximity of public and nonprofit sectors, Bonsón, Royo, and Ratkai´ framework was                adopted and transformed for the needs of nonprofit field by the author of this study. On one side                there  is  a  communication  content  made  by  organization  and  send  to  the  organization´                community. On the second side there is a community which provides questions, feedback, and                involve in organizational mission by volunteering, donors, etc. Both sides together co-producing                new  values,  ensure  transparency  and  manage  volunteer  and  firms´  involvement.  A  revised                framework is available in Fig. 1.                     Figure 1: The role of SM in mutual communication between local community (C) and organization (O)                           Mission of                                                  Mission of local                          organization                                                   community                                                      Co-production                              O2C                      Transparency                      P2O                                                    Volunteer and firm´                                                       involvement                                    Information sharing                          Questions                                  Voluntary reporting                          Feedback                                   Service delivery                           Involvement                 Source: Author.                      As  the  lack  of  research  studies  on  engagement  in  CEE  countries  as  well  as  on  factors                influencing  engagement rate  was  documented,  following  three main  research  questions  were                defined: (1) How do organizations communicate through social media? Which one do they use?                What do they publish?; (2) How much is engagement of Facebook community affected by the                                                                36","service  orientation  of  organization?;  and  finally  (3)  How  much  is  engagement  of  Facebook                community affected by the content of posts, what actually represents the way of communication                towards to the community.                  2  Material and methods                  2.1 Research design and the sample                      Gathering of research sample was conducted in several steps. At first, the websites of 185                organizations listed in Nadace Neziskovky.cz´ catalogue [12] and the section Social Services and                Health were examined in relation of social media use. For higher consistency of the sample, the                organizations  without  available  Facebook  and  without  employees  were  excluded  from  the                sample.                      At second, the Facebook pages of 109 private social service organizations were analysed.                However,  it  was  found  that  some  organizations,  mainly  with  smaller  number  of  friends  and                followers  are  not  operating  their  pages  properly.  An  incorrect  page  management  consisted                mainly in publishing the same or similar posts repeatedly, publishing of higher number of posts                at the same time period, lacking the use of multimedia in posts (pictures, videos, thumbnails), or                in only its inactivity. As this negative practice could distort results on engagement, organizations                with less than 500 Facebook friends were excluded from the sample.                      At third, the sample of 55 organizations with functional Facebook page were analysed in                detail.  Regarding  the  legal  form  the  registered  associations  (30.9  %),  public  beneficial                organizations (25.5 %), registered institutions (21.8 %), and church organization (21.8 %) were                represented in the sample. Regarding social services, the sampled organizations usually perform                more  than  one  main  service,  thus  a  primary  service  was  identified  for  each  organization.                Unfortunately, it was not possible to do it for all them, organizations without primary service are                labelled as “with multiple services”. In the sample were present mainly organizations providing                services to children and youth incl. children in hospitals, children´s homes and fosters (14.5 %);                family issues incl. family counselling, domestic violence and family housing (14.5 %), physical                disabilities,  incl.  housing,  care  and  working  opportunities  (12.7  %);  multiple  social  services                where  the  primary  orientation  was  not clear  (12.7  %); mental  disabilities,  incl.  early care  or                protected  workshops  (10.9  %);  issues  of  addicted  and  punished  (9.1  %);  elderly  (5.5  %),                homeless (5.5 %); integration of foreigners and other ethnics (5.5 %); and others, incl. social                services  in  hospitals,  humanitarian  aid  in  abroad,  volunteering,  or  social  counselling  online                (9.1 %).                      At fourth, ten posts of each organization with functional and properly managed Facebook                page.  Thus,  550  posts  were  analysed  in  detail.  Following  content  classification  of  posts  was                developed  during  coding  and  with  inspiration  of  a  post  content:  information  on  the  services                provided; event invitations; events passed; presentation of job vacancies; information on finance                donation;  information  on  non-financial  donation;  recognition  and  thanks;  volunteering  and                involvement appeals; and timeline/profile updates.                 2.2 Research method and data gathering and processing                      The research uses a content analysis of Facebook pages as a main method. Such analysis                conducted in an online environment is a part of so-called Internet mediated research [5]. For                measuring of engagement rate, several metrics and frameworks were developed and previously                mentioned. The set of metrics, including responsiveness, involvement and virality, is used in this                study. Responsiveness represents number of the reactions on a specific post. In 2016, set of new                reactions (love, haha, wow, sad, and angry) was introduced by Facebook. Such new reactions                improve quality of communication between an organization and the page visitors as they can                express  more  emotions, including  negative  ones. Involvement,  represented  by  the  number  of                comments, is not only much more time-consuming, but it is also more binding for its writer. The                last metric – virality is determined by the number of posts shared. Such behaviour of the page                                                                37","visitors results in great multiplication of post views. Detailed description of areas for content                analysis and the method of data collection is available in Table 1.                                        Table 1: Description of methods for the data collection                Area               Description of area                            Method of Data Collection                Responsiveness (R)   It is determined by number of reactions. Likes represents   Number of reactions per post                                   lower responsivity than other new types of reactions as   published                                   wow, haha, sad or super                Involvement (I)    It is determined by the number of comments. This kind of   Number of comments (only first                                   reaction is much stronger than simple like or any of other   level comments were counted)                                   new symbols                                    per post published                Virality (V)       It is determined by the number of post sharings. It is   Number of sharings per post                                   considered as the strongest type of reaction.                Engagement (E)     E = R+(2*I)+(3*V)                 Source: Author.                      The data were analysed and coded by one coder to prevent possible distortion of results.                The data were collected during five days from January 19 to January 23, 2019. However, the                posts included in the research were published by organizations from Nov 2018 till Jan 2019 due                to fact that ten posts from January 19 and backwards, were analysed. Data were statistically                processed in SPSS 24.0.                  3  Results                 3.1 Social media communication towards the community                      We have found that social service organizations use primarily Facebook (95.1 %). The rest                of social media is exploited in much less extent: YouTube is used by 35.3 % of organizations,                Twitter by 19.6 % of organizations, and other social media as Instagram, LinkedIn, Google+, and                Pinterest totally in 17.6 % of organizations. Regarding the number of SM, the Facebook as an                exclusive  social  medium,  use  more  than  half  of  organizations  (52.0  %).  Then,  the  Facebook                together with YouTube is used by 14.7 % of organizations. Facebook, YouTube and Twitter are                then available in 12.7 % of organizations.                      As  organizations  communicate  mainly  on  Facebook  the  detailed  analysis  on                communication  was  conducted  on  this  social  medium.  It  was  found  that  social  service                organizations communicate mainly information about their services (27 %), this communication                includes  for  example  new  facilities,  where  the  service  is  provided,  improvements  of  service                quality,  or  testimonials  of  service  users.  Publishing  of  post  with  recognition  and  thanks  to                stakeholders was found in more than one fifth of posts (21 %).                      It is important to remind that data collection was gathered also during a New Year and                Christmas  time  which  could  increase  percentage  of  content  associated  with  future  or  passed                events as well as recognition and thanks type of posts. Interestingly, organizations publish more                invitations for events (14.2 %) than information about events passed (9.6 %). Representation of                other organizational messages communicated is probably relevant to daily operational activities                and its frequency. Detailed results are available in Graph 1.                                                                                38","Graph 1: Structure of communication published on Facebook                                                 Source: Author.                 3.2 Total engagement and service orientation                      The highest engagement was found in organizations working with the children and youth.                There were five organizations with this orientation in the top ten ranked by engagement score.                These  organizations  work  in  foster  care,  general  care  for  children,  actor  visits  to  children                hospitalized,  or  seeking  financial  support  for  the  treatment  of  children.  Each  of  other  five                organizations represented different orientation. Remarkably, all organizations with the highest                engagement dispose of strong local (offline) community. On the other hand, a significantly lower                engagement  –  less  than  a  quarter  compared  to  children  and  youth  category  –  was  found  in                organizations  focused  on  family  problems,  working  with  mentally  disabled  and  focused  on                integration of foreigners.                      Strongly significant differences based on the nature of service were confirmed by analysis                of variance results (F-value = 9.630; Sig. = 0.000). Moreover, post hoc and Tukey HSD testing                showed  that  two  homogenous  groups can  be  classified  in  relations  to  engagement  level. The                first, with high engagement rate, would comprise orientation on children and youth, homeless                people, and physically disabled. The second, mainly on addicted and punished, elderly, family                issues, mental diseases and integration of foreigners.                      Regarding  the  responsivity,  involvement  and  virality,  there  were  not  significant                contradictory results found. The only exceptions might be mainly low involvement of comments                among  children  and  youth  organizations´  community  and  vice  versa  relatively  high  level  of                involvement about organizations working on the field of integration of foreigners.                      Detailed  results  on  responsivity,  involvement,  virality  as  well  as  total  engagement  are                available in Table 2.                                                                           39","Table 2: Responsivity, involvement, virality and total engagement according service orientation                            Orientation              Likes        Comments   *   Sharings     Engagement                                                                                        *                                                                                                        **                                                         *                 Children and youth                   66.6           2.4           11.9          107.1                 Homeless people                      40.5           0.8            8.8           68.6                 Physical diseases                    45.8           0.9            5.3           63.6                 Addicted and punished                23.6           0.7            4.6           38.7                 Other                                22.7           0.4            4.0           35.6                 Multiple services                    13.5           0.3            6.1           32.4                 Elderly                              20.2           0.5            2.8           29.5                 Family issues                        8.3            0.1            4.8           23.0                 Mental diseases                      11.3           0.4            3.5           22.5                 Integration of foreigners            16.6           0.8            1.4           22.3                * Average number of likes/comments/sharings per one post                **  Engagement = (number of likes*1)+(number of comments*2)+(number of sharings*3)                3.3 Total engagement and post content (activity published)                      Relevant  Facebook  community  of  examined  organizations  was  highly  engaged  in  the                content  associated  with  non-financial  collections.  Such  activities  included  the  demand  for                clothing, ceramics furnaces, benefit fairs and more. Most of the post content types – seven out of                nine – obtained score over 40 pts. Remaining two content types as invitations for events and                timeline or profile updates obtained much lower engagement score 20.1, resp. 16.1 pts.                      Statistical  analysis  showed  that  differences  among  types  of  posts  are  statistically                significant (F-value = 2.083; Sig. = 0.036). The analysis has not showed so strong differences as                in the case of organizational orientation. Although according to the score results there are two                remote content types (invitations for events and timeline/profile updates), the post hoc tests                and Tukey HSD testing do not allow to classify results into homogenous groups.                         Table 3: Responsivity, involvement, virality and total engagement according to post content                              Orientation                Likes      Comments       Sharings   *  Engagement                                                                                                        **                                                                            *                                                            *                 Non-financial donation appeal           22.9          0.9           14.2         67.2                 Financial donation appeal               32.0          0.6           7.6          56.1                 Information on services                 35.9          1.1           5.7          55.2                 Events passed                           43.2          0.8           3.4          54.7                 Recognition and thanks                  35.6          1.3           4.8          52.7                 Appeal for involvement                  12.8          0.2           10.2         43.6                 Job offerings                           11.3          0.3           10.3         42.7                 Invitations for events                  12.1          0.2           2.5          20.1                 Timeline/profile updates                11.4          0.1           1.5          16.1                *Average number of likes/comments/sharings per one post                ** Engagement = (number of likes*1)+(number of comments*2)+(number of sharings*3)                  4  Discussion and conclusions                       Various  implications  for  non-profit  social  service  organizations  can  be  raised  over  the                paper findings. Following we consider as pulsating:                      a.  Up-to-date state of art in the field of social media use by social service organizations                         was  identified.  Approximately  half  of  organizations  (50.6  %)  with  employees  is                         communicating  on  social  media,  primarily  they  have  available  functional  Facebook                         (95.1 %) site. Other media as YouTube and Twitter are used in much less extent and                         not on a regular basis.                      b.  Strong  significant  differences  among  engagement  according  to  organization´                         orientation  exist;  the  services  in  favour  and  out  of  favour  of  stakeholders  were                         identified. Highest attention of social media users is paid by organizations with children                         and youth services; on the other hand, the least attention is given to services oriented                         on family issues, mental problems and integration of foreigners.                                                               40","c.  Also,  there  are  statistically  significant  differences  in  engagement  according  to  the                         content type of post published. However, they are not so high as in a preceding case.                         Preferred and not preferred content types of posts represented were identified. The                         highest  engagement  of  users  was  recorded  for  posts  with  non-financial  donation                         appeals.                       Although  presented  study  implications  can  be  successfully  applied  into  managerial                practice of relevant organizations, there are many other research challenges in the field. Firstly,                this  research  can  be  expanded  to  larger  area  of  nonprofit  sector  to  identify  relationships                between and engagement rate and organizational characteristics. Secondly, other social media                platforms  analysis,  namely  Instagram  due  to  its  rapid  increase  of  users,  deserve  research                attention.  Thirdly,  the  next  metrics  including  Facebook  page  speed  of  reaction,  review  and                community  sections  of  the  page  and  others  can  be  analysed.  Finally,  an  in-depth  analysis  of                Facebook fan and follower base can be conducted to obtain better understanding of Facebook                organization´ community.                  References                 [1.]  BACHMANN,  P.  2019.  Citizens´  engagement  on  regional  governments´  Facebook  sites.  Empirical                     research from the Central Europe. Conference proceedings of Hradec Economic Days 2019. Hradec                     Králové: University of Hradec Králové, pp. 5-13.                [2.]  BEST, P, MANKTELOW, R., TAYLOR, B. J. 2016. Social Work and Social Media: Online Help-Seeking                     and the Mental Well-Being of Adolescent Males. The British Journal of Social Work 46(1), 257–276.                [3.]  BONSÓN, E., ROYO, S., RATKAI, M. 2015. Citizens' engagement on local governments' Facebook sites.                     An empirical analysis: The impact of different media and content types in Western Europe.                     Government information quarterly 32(1), 52-62.                [4.]  CHO, M.; SCHWEICKART, T.; HAASE, A. 2014. Public engagement with nonprofit organizations on                     Facebook. Public Relations Review 40 (3), p. 565-567.                [5.]  HEWSON, C. 2007. Gathering data on the Internet. Qualitative approaches and possibilities for mixed                     methods research. The Oxford Handbook of Internet Psychology. Oxford University Press, United                     Kingdom.                [6.]  HUANG, Y. C.; LIN, Y-P.; SAXTON, G. D. 2016. Give Me a Like: How HIV/AIDS Nonprofit Organizations                     Can Engage Their Audience on Facebook. AIDS: Education and Prevention 28 (6), Guilford Press.                [7.]  KIETZMANN J. H., HERMKENS, K., MCCARTHY, I. P., SILVESTRE, B. S. 2011. Social media? Get serious!                     Understanding the functional building blocks of social media. Business Horizons 54(3), 241-251.                [8.]  KIM, C.; YANG, S. U. 2017. Like, comment, and share on Facebook: How each behaviour differs from                     the other. Public Relations Review, 43 (2), p. 441-449.                [9.]  KING, P. 2010. Social Networks: Getting your organization working for them! In: Geier, Jr., Philip H.,                     James M. Greenfield, Ted Hart, and Steve MacLaughlin. Internet Management for Nonprofits:                     Strategies, Tools and Trade Secrets. Hoboken, New Jersey: John Wiley \& Sons, Inc., p. XIII.                [10.] LOVEJOY, K.; SAXTON, G. D. 2012. Information, Community, and Action: How Nonprofit                     Organizations Use Social Media. Journal of computer-mediated communication 17 (3), p. 337-353.                [11.] MACEK, J.; MACKOVÁ, A.; KOTIŠOVÁ, J. 2015. Participation or New Media Use First? Reconsidering                     the Role of New Media In Civic Practices in the Czech Republic. Medijskije Studije-Media Studies 6                     (11), p. 68-83.                [12.] NADACE NEZISKOVKY.CZ. 2019. Katalog neziskovek [Catalogue of Nonprofit Organizations].                     Available online at http://neziskovky.cz/katalog/. Accessed Jan 13, 2019.                [13.] WATERS, R. D.; BURNETT, E.; LAMM, A. et al. 2009. Engaging stakeholders through social                     networking: How nonprofit organizations are using Facebook. Public Relations Review 35 (2), p. 102-                     106.                                                                 41","Project Management Teaching at Czech Public Universities                           in the Context of Project Manager Competencies                   Covered within the National Competence Baseline of Project                                             Management, version 4                                                    a                                                                                              c                                                                    b                            BOČKOVÁ Kateřina ; LAJČIN Daniel ; DOHNANSKÁ Monika                                                     DTI University, Slovakia                                           a            b         c                                            bockova@dti.sk;  lajcin@dti.sk;  dohnanska@dti.sk                Abstract                The aim of presented paper is to synthesize the results obtained by comparison with desk research and                consultations carried out at selected Czech public universities in the academic year 2018/2019 in order to                identify  the  coverage  of  the  project  manager  competencies  mentioned  in  the  National  Competence                Baseline  of  Project  Management,  version  4,  in  lectures,  exercises  or  seminars,  of  course  Project                Management and transdisciplinary in the context of teaching of related managerial and economic courses.                The benchmark was the National Competence Baseline of Project Management (NCB), version 4 issued in                2018. Due to the availability of relevant information resources for the realization of desk research and                consultations,  the  survey  was  conducted  at  VŠE  Praha,  ČVUT  Praha,  VUT  Brno,  UP  Olomouc,  VŠB-TU                Ostrava, as a sample of universities in which some form of project management  is taught. We used an                analysis  of  the  available  documents,  specifically  NCB  ver.  4  with  an  emphasis  on  the  identification  of                project  manager  competencies  in  the  context  of  meeting  the  requirements  for  candidates  for  D  level                certification  of  project  managers.  Further  syllabuses  of  managerial  and  economic  courses  of  individual                analyzed universities were used. Valuable backgrounds were the personal consultations with guarantors                and  teachers  of  relevant  courses  during  the  winter  term  of  the  academic  year  2018/2019.  The                prerequisite for the comparison of the outputs obtained through the desk research and consultations is                the content of the certification exam for the D level certification. Important information is the fact that the                presented paper does not compare the quality of teaching, but only the content of the subject matter in the                analyzed courses.                 Keywords: Project management; teaching; project manager; IPMA; certification.                JEL Classification: A23, I21, L84, M53.                    1  Introduction                       Currently,  project  management  has  become  a  part  of  the  everyday  lives  of  many                individuals and groups - projects are being used to develop new products, technologies, to build                motorways or to provide education. A number of official certifications have also been developed                to record the knowledge of the project manager or members of the project teams, as well as to                broaden  and  to  consolidate  their  outlook  in  this  area  within  the  context  of  the  subsequent                practical  project  actions.  Until  the  1950s,  there  was  no  systematic  theory  of  project                management,  and  individual  complex  projects  were  implemented  more  or  less  on  an  ad  hoc                basis. Since then the experiments to systematize the processes from a variety of disciplines and                to  create  a  coherent  management  theory  whose  principles  would  be  applicable  in  different                situations, have begun. Since that time these companies have begun to offer a comprehensive                theory, education, and exams as a proof of knowledge.                      One  of  the  companies,  IPMA  (International  Project  Management  Association),  was                established in Europe in 1967, merging under the federal framework of national management                associations.  The  branch  for  this  company  in  the  Czech  Republic  is  IPMA  CZ,  which  was                established  to  implement  the  IPMA®  certification  process.  The  Certification  Body  is  a                professionally  independent  component  and  is  responsible  for  ensuring  that  the  certifications                comply  with  the  certification  scheme  described  in  the  IPMA®  Certification  Regulations                                                               42","Guidelines. IPMA certification is graded according to difficulty. D level certification is intended                primarily for project team members. It is also suitable as a proof of theoretical knowledge in                project management. Next services offered by IPMA include National Student Certification. This                certification  is  offered  to  students  interested  in  expanding  and  improving  their  project                management knowledge. The main importance of this certification is to increase the quality of                project management after the students start working. This certificate confirms that the student                is able to work in the conditions of project management with regard to the field of education.                      Despite  the  above-mentioned  the  project  management  teaching  at  Czech universities is                not a condition and a matter of course yet. However, with the growing interest and demand on                project  managers  and  project  team  members,  the  development  of  this  discipline  is  currently                appearing  at  the  universities.  Especially  in  technical  or  economic  fields,  there  is  a  high                probability that the graduate will, at least for some time, become a member of the project team.                      The expected output of the presented paper is therefore the exhaustive identification of                courses taught at Czech universities, which mostly cover the requirements for preparation for                certification of project managers according to IPMA, level D.                  2  Material and Methods                       The aim of presented paper is to synthesize the results obtained by comparison with desk                research and consultations carried out at selected Czech public universities in the academic year                2018/2019 in order to identify the coverage of the project manager competencies mentioned in                the National Competence Baseline of Project Management, version 4, in lectures, exercises or                seminars,  of  course  Project  Management  and  transdisciplinary  in  the  context  of  teaching  of                related  managerial  and  economic  courses.  The  benchmark  was  the  National  Competence                Baseline of Project Management (NCB) [17], version 4 issued in 2018. The desk research was                realized  in  time  period  October  –  November  2018.  We  used  an  analysis  of  the  available                documents, specifically NCB ver. 4 with an emphasis on the identification of project manager                competencies in the context of meeting the requirements for candidates for D level certification                of project managers. The goal of the desk research was to find as much information as possible                on project management teaching at Czech public universities. The research was carried out by                mapping the websites of Czech public universities. On this websites the attention was focused                primarily on study plans and curricula, lists of courses, or syllabuses of individual courses, in                order  to  find  curricular  documents  related  to  project  management  teaching.  Here,  a  major                deficiency related to this type of research was discovered, namely the impossibility of tracing the                curriculum  documents  of  project  management  teaching  at  a  number  of  universities.  Another                identified deficiency was the inconsistency of the information obtained. In cases where a specific                curriculum was found, this document did not always contain all the required information. Often                the timeliness of the document or the information provided was not clear. The universities that                do  not  have  a  published  curriculum  of  the  course  usually  have  a  short  description  in  the                curriculum or in the course information. This description is of a more general nature and serves                as a basic information source for the content of the course, or its goals. These universities have                been excluded from our desk research. Due to the availability of relevant information resources                for the realization of desk research, the survey was conducted at VŠE Praha, ČVUT Praha, VUT                Brno, UP Olomouc, VŠB-TU Ostrava, as a sample of universities in which some form of project                management is taught.                      Valuable  backgrounds  were  personal  consultations  with  guarantors  and  teachers  of                relevant  courses  during  the  winter  semester  (time  period  October  –  November  2018)  of  the                academic  year  2018/2019.  We  realized  9  personal  consultations  (3  consultations  with                guarantors per VŠE Praha: 2 men, 1 woman, 1 consultation per UP Olomouc with the guarantor:                woman, 1 consultation per VŠB-TU Ostrava with the guarantor: man, 2 consultations per ČVUT                Praha with the guarantor of the course, man, and with one teacher, woman, and VUT Brno, with                the guarantor of the course, man, and with one teacher, man. Each consultation lasted 15-20                minutes and the aim of the consultation was to identify the percentage coverage of required                                                               43","curriculum  for  the  certification  with  the  requirements  on  students  in  the  context  of  the                implementation of particular elements into the project management teaching. All evaluations are                based on the subjective evaluation of the respondents.                      The prerequisite for the comparison of the outputs obtained through the desk research                and consultations is the content of the certification exam for the D level certification, which was                divided according to the competency elements identified in the NCB ver. 4, and each competence                set was assigned the appropriate score (see Table 1).                          Table 1: Scoring the inclusion of individual project management elements in the courses                                  Inclusion of    Number of    Scoring of each  Scoring for the area                Competencies    competence areas  elements of each   elements of   of competence in   Total points                                 into tests in %   competencies   competencies    total                Technical             70             20             77            1540                Behavioral            15             15             22             330           2200                Contextual            15             11             30             330                Source: Authors.                       The  result  of  the  desk  research  is  the  authors´  subjective  evaluation  of  the  percentage                coverage of required curriculum and the result of the consultations is the project management                courses  guarantors´  and  teachers´  identification  of  the  percentage  coverage  of  required                curriculum. This paper presents the final percentage coverage of required curriculum for the                IPMA level D certification based on the arithmetic mean of previous results following from the                desk research and consultations. The inclusion of individual elements into the teaching will be                enumerated even if the course will only partially overlap with their contents. The introduction of                students  with  a  particular  issue  will  also  be  taken  into  account.  This  assessment  will  not,                therefore,  compare  the  quality  of  teaching,  which  for  obvious  reasons  is  rather  difficult  and                subjective, but only coverage of the certification requirements for the substance being studied.                  3  Project Management Teaching                       How  to  teach  Project  Management  at  universities?  Such  work  has  not  been  found                regarding  the curriculum  documentation of  universities  with  a  focus  on  project management                teaching. The analysis of project management teaching at Czech universities is dealt in [9] or                [10].  Overall,  however,  this  issue  is  fundamentally  unresolved  and  unspoken  in  the  Czech                environment.                      Foreign information sources are much more saturated in this area. Modern methods of                project management teaching are addressed internationally by [19]. The author identifies the                state of the art related to the use of serious games for understanding, teaching and supporting                education of the standard ISO 21500 with the goal of proposing a simulation-based serious game                that  supports  its  management  processes  in  the  context  of  software  projects. A  multivocal                literature  review  was  conducted  and  a  simulation-based  serious  game,  called  ProDec,  was                proposed.  The  author  analysed  the  coverage  of  the  management  processes,  the  process  and                subject groups of the ISO 21500 that ProDec is able to provide, and they conducted an empirical                evaluation  to  assess  the  educational  effectiveness  of  the  game  in  terms  of  motivation,  user                experience, and learning outcomes. He realized that ProDec is able to cover 7 of the 10 subject                groups  and  almost  75%  of  the  project  management  processes  of  the  ISO  21500  standard.                Moreover,  all  the  participants,  involved  in  the  empirical  evaluation,  expressed  positive                comments  that  ProDec  stimulated  their  motivation,  offered  a  positive  user  experience  and                promoted the learning of the management processes involved in these 7 subject groups.                      The importance of practical experience in the project management teaching at the colleges                and universities is mentioned in [14]. In this paper is presented the insights into the importance                of  practical  experience  in  project  management  success  and  discussed  how  well  university                education prepares future project managers in terms of practical project learning approaches.                The paper provides an example of a multidisciplinary collaboration experience between courses,                                                               44","applied  at  Qatar  University.  The  initial  results  of  students'  assessment  suggest  that                multidisciplinary  collaboration  can  provide  a  unique  learning  experience  to  develop  the                students' managerial skills by integrating learning outcomes and performances.                      The justifiability of the use of information technology in project management teaching is                documented  in  [4]  and  [28].  Other  case  studies  providing  relevant  information  on  project                management teaching at and universities have been published in [27], [13], [15], [11], [2] or [3].                      The development of soft skills in project management teaching at the University of Vienna                is described in [8], developing the project managers' competencies in India is described in [6],                and [7] describes the teaching of teamwork for project management. [16] designed a university                education and training project management project that takes into account the diversity of the                basic characteristics, needs and expectations of the Millennials and Baby Boomers. [18] defines                the necessity to create a European way of Master education in project management. In this case                already was developed a portfolio of six Master programmes at different European universities.                These programmes are closely interlinked with exchange formats for students, scientists and                lecturers,  double  degrees  and  a  joint  research  community.  The  programmes  follow  a  similar                philosophy and didactic model. They have a synchronized and aligned curriculum. The intended                competence  profile  for  the  graduates  is  aligned,  too,  while  still  being  differentiated  by  local                specialization modules and different target groups.                   4  Results and Discussion                       VŠE  Praha  offers several  courses  related  to  Project  Management:  Project Management,                Project  Manager  Competencies,  Project  Management  Methods  and  Standards.  The  aim  of  the                Project Management course is to introduce students to basic techniques, models and methods                of project management (VSE©2018a). Students will learn how to use MS Project as standard                project management software. The objective of the Project Manager Competencies course is to                orientate the student in the socio-psychological context of the management and functioning of                the project team. The course focuses on the development of managerial competencies of project                managers,  including  management  of  the  project  team,  as  well  as  the  principles  of  effective                project  team  work  from  the  point  of  view  of  its  members.  The  course  is  based  on  the                consideration that the effective functioning of the project team is not only conditional on the                knowledge of technical procedures and methods, but also of team leadership skills. This course                is taught at the Faculty of Business Administration and is recommended for the first year of the                Master's  degree  course  (VSE©2018b). The  course  titled  Project Management  Methods  and                Standards  aims  to  prepare  students  for  professional  certification  exams.  This  is  not  IPMA                certification  but  PMI  certification,  specifically  Certified  Associate  in  Project  Management                (CAPM®).  Students  will  get  acquainted  with  the  methodologies  and  standards  of  project                management  and  will meet  the  actual  practices  in  the  field,  which  discuss  the success  of  the                implementation, the management of the change projects, the specifics of the given branches, etc.                In order to fulfill the course aim the students are supposed to have passive knowledge of English                (VSE©2018c), because they have to work with origin material and tests. Students learn about                existing international standards, such as PRINCE2 and OGC, CzNCB, while focusing in detail on a                single PMBoK Guide [1].                      The  course  entitled  Project  Management  taught  at  the  Department  of  Project                Engineering (at the Faculty of Information Technology of ČVUT Praha) aims to prepare students                for  the  IPMA  Grade  \"D\"  International  Exam. During  the  semester,  students  will  learn  how  to                understand the philosophy of project management, get an overview of the project management                terminology, and gain insight into project management methods and procedures, which they will                gradually acquire and learn to apply them effectively. Other important components of the course                are so much appreciated \"soft skills\", the ability to ask the right questions and to formulate own                insights (CVUT©2018).                      The course entitled Project Management taught as compulsory at the Bachelor's program                of the Faculty of Business at VUT Brno is the third year accredited by IPMA Czech Republic and                                                               45","is taught in close connection with the IPMA methodology. According to VUT (VUT©2018), the                course clarifies the current trends and international standards of project management. It mainly                deals with project planning and management so that projects can be completed in time, in the                required  quality  and  within  the  budget.  This  course  aims  to  prepare  students  for  the  IPMA                certification exam.                      The course Project Management 1 at the Faculty of Philosophy of the Palacký University                in Olomouc is intended as compulsory for students of Master's degree program in Psychology.                The  aim  of  the  course  is  to  familiarize  the  students  with  the  basics  of  project  management,                presentation  of  individual  methods  and  principles  of  this  form  of  management  and  practical                training.                      Course Project Management A is designed for students of bachelor's study at the Faculty                of Economics, VŠB-TU Ostrava. The main part of the course deals with project planning using                MS Project software support. Students learn to practice the theoretical knowledge on a practical                project using software technology. Practical lectures of experts are also a part of the seminars,                where students can deepen their knowledge of project management with the approaches and                problems of the given field in different fields and different professions. The aim of the course is                to  acquaint  students  with  basic  approaches  and  methods  in  project  management  (VSBTU                ©2018).                  4.1 Results comparison                      The results and comparison of the individual courses are described in Table 2 bellow.                                                  Table 2: Results comparison                                         Number of elements of the                                                                   Preparation of                  University   Course   individual competencies included   certification %   Course specification                                             in the teaching                                     Technical           10                     The course provides students a                            4EK411   Behavioral          1            38,7      good theoretical background for                                                                                possible deeper study of technical                                     Contextual          2                      specifications.                                     Technical           4                      The course focuses primarily on                    VŠE     3PS532   Behavioral          7             21       teaching of behavioral                                     Contextual          0                      competencies.                                     Technical           20                     The aim of the course is to prepare                            3MA534   Behavioral          15            100      students for a certification exam                                     Contextual          11                     according to PMI, not IPMA.                                     Technical           20                     The aim of the course is to prepare                    ČVUT    BU - PRR   Behavioral        4             74       the students for the certification                                     Contextual          0                      exam according to IPMA, level D.                                     Technical           17                     The course is accredited by IPMA                    VUT     FP - BrpP   Behavioral       4             68       CZ and is taught in close                                                                                connection with the IPMA                                     Contextual          3                      methodology.                                     Technical           13                     The course is focused on the                                     Behavioral          1                      teaching of technical competencies                    UPOL    PCH/PROM                                   48       and the subsequent practical                                     Contextual          1                      training of individual methods and                                                                                principles.                                     Technical           12                     The course is focused on practical                            157 -                  VŠB - TUO          Behavioral          1             48       training of methods and principles                            0361/01                                     Contextual          4                      of technical competencies.                Source: Authors.                                                                   46","The  best  assessment  was  achieved  by  course  3MA534  Methods  and  standards  of                project  management  (VŠE  Praha).  All  elements  of  project  management  competencies  are                formally included in the course, but the learning of these elements is, of course, done in a very                timely manner, and the student would have to deepen the knowledge of the individual elements                in the actual IPMA certification level D. However, the PMBoK [1] and NCB standards are closely                interconnected in some parts as is cited in [12].                      The course BU - PRR Project Management (ČVUT Praha), reached high assessment as                well, and prepares students for certification examinations according to IPMA from seventy - four                percent.  All  the elements  of  technical competencies  that  are most  focused  on  IPMA  level  \"D\"                certification  are  reflected  in  the  course.  Elements  of  behavioural  competencies  are  discussed                here in a very marginal way, contextual competencies are not related to the teaching at all. This                course  is  intended  primarily  for  students  who  are  interested  in  deepening  their  knowledge                outside of IT, gaining new knowledge of project management and, if possible, extras. The fact                that the dominant component is a field of technical competencies is in perfect harmony with the                intuitive image that we have about CVUT Praha.                      The  FP  -  BrpP  Project  Management  course  (VUT  Brno),  which  will  provide  the                preparation required for passing the certification examination from sixty-eight percent, was also                excellent.  Teaching  is  most  focused  on  the  area  of  technical  competencies  elements.  It                complements the content of other compulsory courses of the Bachelor's degree program so that                the students are able to pass the \"D\" level IPMA certification exam. Four key areas of project                management  are  being  trained  in  the  course:  designing  a  project  strategy,  effective  project                planning, project management principles, and project termination. Part of the training is also                software support for project planning and monitoring. Students will learn how to work with MS                Project during the semester, where the output will be created by the project plan. The aim of the                course  is  to  acquaint  students  with  the  internationally  recognized  principles,  trends  and                procedures  of  project  management  and  to  teach  them  effective  use  of  information  and                communication technologies in the given field.                  5  Conclusion                       The  best  assessment  of  analysed  courses  at  selected  universities  was  achieved  by  the                course  Methodology  and  standards  of  project  management  taught  at  VŠE  Praha.  However,  it                should be recalled that this course prepares mainly for the PMI certification exam and that the                individual elements of competency needed for the IPMA exam are all mentioned in the course,                but in no way can it be said that this preparation would be sufficient for the IPMA candidates.                That is why we would like to mention the course Project Management, which is taught at ČVUT                Praha. The aim of the course is the preparation for the given certification exam itself and, in                terms of requirements for the candidates, the course covers approximately seventy-four percent                of the required knowledge.                      From available information, it can be assumed that a number of universities in teaching                are based on world-class project management standards, and also teach the tools and methods                that are based on these standards. A significant part of the primary literature also comes out of                the world's standards. Another gained knowledge is that the courses are taught mainly at the                Master's  degree,  where it  is  part of  the specialization,  and  the  signing  of  this  course is  often                optional. Regarding the time subsidy of the course, it was most often quoted 1,5 hours per week                during one semester. It has also been found that the course is partially focused, so it is taught on                a full-time basis and in addition to completing a written test, completion of the team project is                required. Due to the practicality of the course, compulsory attendance is required. Part of the                universities  also  offers  their  students  the  opportunity  to  obtain  certification  in  project                management. Here, it is necessary to draw attention to the fact that in this case the reliability                and,  therefore,  the  validity  was  not  ensured.  An  unambiguous  knowledge  of  all  the  elements                needed  to  obtain  IPMA  level  D  certification  will  be  obtained  in  the  context  of  the  IMPA  CZ                recommendation by a candidate within the discharge of one of several accredited educational                                                               47","programs available within the Czech Republic. As reported in recent statistics [5], accredited                educational  organizations  have  already  trained  seventy-three  percent  of  the  candidates  for                certification,  and  these  candidates  have  been  more  successful  in  certification.  Accredited                educational  programs  include:  ACSA,  Academic  Learning  Activities  Center,  Bohemia  Training                Institute s.r.o., HM Partners s.r.o., Institute of Lifelong Learning of Mendel University in Brno,                LBMS,  s.r.o.,  PM  Consulting,  s.r.o.,  SHINE  Consulting,  s.r.o.,  Brno  University  of  Technology,                Faculty  of  Information  Technology,  Brno  University  of  Technology,  Faculty  of  Business                Administration.                      Presented  paper  can  be  beneficial  not  only  for  other  universities  or  other  educational                institutions that can use the acquired knowledge as inspiration or recommendation in compiling                the curriculum of Project Management, both in content and formal. However, since similar work                has  not  been  found  regarding  the  curriculum  documentation  of  universities  with  a  focus  on                project management teaching, this work can be understood as an initial insight into the subject,                which can be followed by further research work. Follow-up work may consist, for example, of an                analysis  of  curriculum  documents  focusing  on  the  teaching  of  specific  areas  of  project                management, thus forming a more detailed description of the content structure of the course. Or,                other follow-up work can focus, for example, on the applicability of graduates with knowledge of                project management in different areas of the national economy.                   References                 [1.]  A guide to the project management body of knowledge (PMBoK® guide). 2013. Newtown Square,                     Pennsylvania: Project Management Institute.                [2.]  ARMSTRONG, P. 2018. School business managers in England: negotiating identity. International                     journal of educational management. 32(7), p. 1266-1277.                 [3.]  BALCO, P. 2017. The Use of Web 2.0 Platforms in Education of Project Management. In: 10th                     International Conference Of Education, Research And Innovation (ICERI2017). p. 4464-4469.                [4.]  CAPATINA, A. 2018. Information Technology – the key enabler of multiple project management in                     higher education institutions. In: Proceedings of the International Conference on Business Excellence.                     12(1), p. 1002-1011.                [5.]  Certifikační orgán: Akreditované studijní programy. 2019. [online]. Dostupné z                     <http://www.ipma.cz/web/vzdelavani/akreditovane-vzdelavaci- programy.php>                [6.]  CRAWFORD, R. 2018. Feeling part of a team” a mixed method evaluation of a dedicated education                     unit pilot programme. Nurse Education Today. 68, p. 165-171                [7.]  DATTA, P. 2018. Developing competencies to lead innovation in Indian manufacturing: an education                     model. International Journal of Innovation Science . 10(4), p. 475-494.                [8.]  GUEVER, S. 2017. Improving Communication in Multicultural Teams - A Web-Based Model and its                     Application in Project Management Education. In: 2017 IEEE Frontiers In Education Conference (FIE).                 [9.]  HORÁK, J. 2016. Analýza kurikul iSchools v segmentu projektové výuky se zaměřením na projektový                     management. Masarykova univerzita. Diplomová práce.                [10.] JANICZKOVÁ, L. 2014. Řízení projektů – srovnání výuky na VŠ s ohledem na certifikaci IPMA.. VŠE                     Praha. Bakalářská práce.                [11.] LUTSENKO, G. 2018.Case study of a problem-based learning course of project management for                     senior engineering students. European Journal of Engineering Education. 43(6), p. 895-910.                [12.] MÁCHAL, P., KOPEČKOVÁ, M., PRESOVÁ, R. 2015. Světové standardy projektového řízení: pro malé a                     střední firmy: IPMA, PMI, PRINCE2. Praha: Grada.                [13.] MACHERIDIS, N. 2018. Balancing authority and autonomy in higher education by implementing an                     agile project management approach. Tertiary education and management. 24(2), p.128-143.                [14.] MAZZETTO, S. 2018. Multidisciplinary Collaboration in Project Management Education: Practical                     Approach. 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Master Level Education in Project Management - the EuroMPM Model.                     In: Proceedings of the 2017 9th Ieee International Conference on Intelligent Data Acquisition and                     Advanced Computing Systems: Technology and Applications (IDAACS), Vol. 2. p. 836-842.                [19.] RUIZ, M. 2018. A serious game to support the ISO 21500 standard education in the context of                     software project management. Computer standards \& interfaces. 60, p. 80-92.                [20.] Sylabus předmětu 157-0361/01 - Projektové řízení A, Vysoká škola Báňská – technická univerzita v                     Ostravě 2018. [online]. Dostupné z http://goo.gl/oRjMYk>                [21.] Sylabus předmětu 4EK411 - Řízení projektů, Vysoká škola ekonomická v Praze. 2018a. [online].                     Dostupné z <http://isis.vse.cz/katalog/syllabus.pl?predmet=85273;lang=cz>                [22.] Sylabus předmětu 3PS532 - Kompetence projektového manažera, Vysoká škola ekonomická v Praze.                     2018b. [online]. Dostupné z http://isis.vse.cz/katalog/syllabus.pl?predmet=95955;lang=cz>                [23.] Sylabus předmětu 3MA534 - Metody a standardy projektového management, Vysoká škola ekonomická                     v Praze. 2018c. [online]. Dostupné z                     <http://www.isis.vse.cz/katalog/syllabus.pl?jazyk=1;predmet=88446>                [24.] Sylabus předmětu BI-PRR - Projektové řízení, České vysoké učení technické v Praze. 2018. [online].                     2017.Dostupné z                     http://bk.fit.cvut.cz/cz/predmety/00/00/00/00/00/00/01/80/90/p1809006.html>                [25.] Sylabus předmětu FP-BrpP - Řízení projektů, Vysoké učení technické v Brně. 2018. [online]. 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International journal of information                     technology project management. 9(4), p. 1-16.                                                                                             49","The Role of Fiscal Considerations in Business Capital Structure:                                    Evidence from Innovative Start-ups                                                        BUCCI Valeria                                                  SOSE Spa* and Unisalento, Italy                                              vbucci@sose.it; valeria.bucci@unisalento.it                * Disclaimer: The views expressed in this paper are those of the author and do not necessarily reflect the opinion of SOSE Spa.                 Abstract                 A central debate in public policy finance is the role of fiscal considerations in companies’ capital structure.                In a fiscal system allowing interest-expenses deductibility, the disparity in the tax treatment of equity and                debt  could  affect  financing  choices.  In  order  to  solve  welfare  losses,  public  action  should  intervene  by                aligning the fiscal treatment of debt and equity, achieving tax neutrality. Otherwise, public action can be                designed  in  order  to  affect  financing  choices  indirectly,  increasing  companies’  attractiveness  for  new                outsider investors. An example of such policies is provided by the Italian Growth Decree, which introduced                fiscal  incentives  for  individuals  or  legal  entities  investing  in  innovative  start-ups.  Using  data  on  young                Italian companies, this paper investigates if corporate financing choices have been affected, by one side, by                the fiscal benefits due to interest expenses deductibility and, by the other side, by the attractiveness of                innovative start-ups for outside investors. The empirical results show that companies decrease the level of                equity ratio when the marginal tax rate increases; moreover, due to the possibility for outside investors to                obtain fiscal saving, innovative start-ups result more incline to prefer equity financing.                Keywords: Public Policies; Companies’ Capital Structure; Equity Financing; Innovation; Innovative Start-ups.                 JEL Classification: H25; H32; O00; O32; O38                    1  Introduction                      A central debate in public policy is the role of fiscal considerations in companies’ capital                structure. When interest expenses are tax-deductible, while the same benefit is not allowed to                the opportunity cost of equity finance, the disparity in the tax treatment provides an incentive                for companies to prefer debt to equity [29, 30].                      A  wide  number of empirical studies  analyses  the effect  of  taxes on corporate  financing                decisions (for through review see [18, 20, 26, 37]). The focal point of the most of the studies in                the ‘80s and ‘90s was to find an adequate proxy for company-specific tax status. These studies                are often based on observed statutory tax rates, usually uniform across firms and constant for                long periods, which makes it difficult to find sufficient cross-sectional and time-series variations                to identify tax effects. To overcome this weakness of literature, several recent studies proxy the                fiscal variable with simulated company-specific marginal tax rates (MTRs), in line with [15, 16,                17, 38], and find convincing evidence on the role of taxes on corporate financing choices [19].                      If  the  disparity  in  the  fiscal  treatment  of  equity  and  debt  affects  companies’  financing                choices, welfare losses may arise. In order to solve such losses, public action should intervene by                aligning the fiscal treatment of debt and equity, achieving tax neutrality. Otherwise, public action                could  be  designed  in  order  to  affect  financing  choices  indirectly,  increasing  companies’                attractiveness for new outsider investors. An example of such policies is provided by the Italian                Growth Decree, which introduced fiscal incentives for individuals or legal entities investing in                innovative start-ups. The policy has been introduced by the Italian government in 2012, with the                aim to increase economic growth and employment. The belief that innovation is a key driver for                economic  growth  and  competitiveness  of  national  economies  is  strongly  supported  by  both                economic theory and empirical evidence [1, 22, 23, 36]. However, according to economic theory,                markets fail to provide the “socially” optimal level of innovation and technological development,                making public intervention necessary to rise the social welfare [7].                                                               50","For  long  time  public  intervention  has  been  aimed  exclusively  at  encouraging  all  the                companies  to  invest  in  innovative  activities,  solving  market  failures  generated  by  innovation                (such as knowledge spillovers). During the last years, innovative companies drew the interest of                policy makers. Mostly in the European context, several policy interventions have been designed                to  promote  their  development,  by  solving  the  difficulty  in  finding  the  necessary  financial                support. A common limit for the development of innovative companies is the difficulty to attract                outside investors. The difficult screening activity for outsiders associated to the high risk and                uncertainty of the outcome could affect the willingness of investors to finance such companies.                      Economic  literature  has  long  investigated  the  effectiveness  of  technology  policies  to                stimulate  R\&D  private  expenditure,  finding  convincing  evidence  that  public  R\&D  policies                stimulate private R\&D expenditure [2, 4, 10, 35]. On the contrary, to the best of my knowledge,                scant empirical evidence exists on the effectiveness of public policies in fostering investments in                innovative companies. [11] provides a recent example in such a field. Based on a panel data set                of Italian companies covering the years 2010-2014, this paper analyses the effects of the above-                mentioned Growth Decree. The empirical result show that the fiscal incentives admitted by the                Italian  fiscal  system  have  been  effective  in  stimulating  investments  in  innovative  start-ups.                However, the main limit of [11] is the too short observation period of innovative start-ups.                      This paper provides further evidence on the role of fiscal considerations on companies’                financing  choices.  In  particular,  it  investigates  if  companies’  capital  structure  responds  to                changes  in  company-specific  marginal  tax  rates,  simulated  following  the  Graham-Shevlin                methodology. Second, the paper examines how companies’ equity ratio reacts when the fiscal                system allows fiscal incentives for outside investors.                      The contributions to the existing literature are several. First, this paper implements a new                identification strategy based on accurate, company-specific marginal tax rates (MTRs), used as                proxy  for  the  fiscal  advantage  of  debt-financing.  Following  [6],  I  develop  a  microsimulation                model using for a sample of Italian companies in the period 2013–2016. The simulated MTRs                display considerable cross-sectional and time-series variation due to the extremely nonlinear                structure of Italian corporate income. Second, the most of the existing literature on corporate                capital  structure  is  focused  on  debt  ratio,  investigating  which  are  the  important  factors  in                determining the optimal leverage of a firm. On the contrary, this paper is focused on the analysis                of the determinants of equity ratio. My identification strategy, exploiting the introduction of the                Growth Decree, allows to investigate whether innovative start-ups are more incline to use equity                financing rather than debt, resulting more likely to attract new investments. The fiscal benefits                restricted to a well-defined group of companies (i.e. outside investors in innovative start-ups),                provides a quasi-natural experiment by which to test my hypothesis empirically.                      The empirical analysis provides significant evidence on the role of fiscal considerations on                companies’ capital structure. It emerges that the higher the marginal tax rate (i.e. the higher the                fiscal benefits of debt financing, due to interest expenses deductibility), the lower companies’                likelihood to finance through equity. Moreover, the empirical results show that innovative start-                ups are more likely to use equity financing, confirming the effectiveness of the Growth Decree in                making innovative start-ups more attractive for outsider investors.                      The remainder of the paper is organized as follows. Section 2 discusses the Growth Decree,                whereas, section 3 explains the research design and defines the variables used in the empirical                analysis. Section 4 describes sample construction and presents data description. The estimations                and the results are discussed in section 5. The final section provides some concluding remarks.                  2  Institutional background                       In the last years, innovative companies gained increasing attention from governments, due                to their expected high innovative performance and productivity growth [12, 34].                      The development of innovative companies is get more difficult by the difficulty in finding                the  financial  support  necessary  to  help  and  enhance  their  growth.  From  the  perspective  of                investment theory, the high degree of risk and uncertainty associated with their outcome makes                                                               51","innovative companies different from traditional ones [14, 24]. Adopting new technologies and                methodologies,  innovative  companies  are  exposed  to  high  risks  of  failure  combined  with  the                possibility of achieving high returns, and for outsiders it is very hard to evaluate which will be                the most probable scenario. Innovative companies are often young, and the absence of a track                record makes it more difficult to evaluate the probability of being successful. The high risk and                uncertainty  associated  with  their  outcome  makes  the  screening  activity  for  the  outsider                investors very difficult [27]. Moreover, the presence of asymmetric information problems makes                harder the evaluation of the quality of innovative projects. An innovative company has better                information  about  the  likelihood  of  success  and  the  nature  of  the  contemplated  innovation                project  than  potential  investors,  but  it  has  no  incentive  to  publicize  information  about  the                innovative project, in order to maintain its competitive advantage.                      The financial requirement and the degree of risk and uncertainty depend on the phase of                innovative  activity  [25].  At  the  beginning,  during  the  formulation  of  the  innovative  project,                uncertainty  and  the  risk  of  failure  are  very  high,  but  the  financial  requirement  is  very  low,                limited to the expense of the studies of the feasibility of the project. In the start-up phase, the                degree of risk and uncertainty is high and huge financial resources are necessary to realize a                prototype,  to  sustain  marketing  activity  and  to  support  the  product.  The  development  and                growth phase needs great financial resources, but it has a low degree of risk and uncertainty.                      The difficult screening activity for outsiders associated to the high risk and uncertainty of                the outcome could affect the willingness of investors to finance innovative companies, especially                at the beginning of the innovative activity and during the start-up phase. Therefore, public action                could  intervene  to  help  and  enhance  the  creation  and  growth  of  innovative  companies,  by                favouring indirectly investor in innovative companies, for example through the recognition of                fiscal incentives. An example in such field comes from the public policy introduced by the Italian                Government in 2012, the Growth Decree (Law Decree No. 179/2012).                      With the aim to foster sustainable growth, technological development and employment, in                particular youth employment [Article No. 25], the Growth Decree introduced a comprehensive                new framework promoting the creation and development of innovative start-ups. The recipients                of the policy are private stock companies, not listed on a regulated market, set up no more than                48  months  ago  and  having  as  exclusive  or  core  business  the  development,  production  and                commercialization of innovative products or services, with high technological value.                      The Growth Decree introduced tax incentives for individuals or legal entities investing in                innovative start-ups. Taxpayers subject to personal income tax investing in innovative start-ups                may benefit from a tax credit equal to 19% of the investment, up to a maximum of € 500,000 for                each  fiscal  year.  Companies  and  other  entities  subject  to  corporate  income  tax  (other  than                innovative start-ups) may benefit from a deduction from the corporate taxable income equal to                20% of the amount invested, up to a maximum of € 1.8m for each fiscal year.                      The  possibility  for  innovative  start-ups  to  raise  equity  capital  through  equity                crowdfunding  is  admitted.  Innovative  start-ups  could  make  an  open  call  for  funding  on  a                crowdfunding platform, providing a detailed description of their project. Investors make their                decision based on the information provided by the innovative start-up. The effective realization                of  the  project  is  subject  to  the  obtainment  of  a  minimum  level  of  funding  necessary  for  the                goodwill.  The  crowdfunding  platform  facilitates  the  transaction  by  providing  a  standardized                investment contract and settling the payments [8]. Equity crowdfunding has not been designed                to  replace  traditional  capital  raising  instruments,  but  rather  is  a  complementary  instrument                aimed at providing funding for innovative and promising entrepreneurial projects.                  3  Research design                       The  main  purpose  of  this  paper  is  to  verify  if  Italian  young  companies  confirm  the                existence of an interaction between fiscal considerations and companies’ financing choices. First,                this study investigates if companies’ capital structure responds to changes in company-specific                                                                 52","marginal  tax  rates.  Second,  it  examines  how  companies’  equity  ratio  reacts  when  the  fiscal                system allows fiscal incentives for outside investors. The baseline specification is the following:                                                                                              (1)                where               is defined as the equity expressed as a proportion of total liabilities. The                principal  control  variables  are  the  marginal  tax  rate  (MTR)  and  the  dummy  identifying                innovative start-ups ( ). MTR is the marginal tax rate computed developing a microsimulation                model following the Graham-Shevlin methodology. The parameter   is expected to be negative                and significantly linked to financing choice: the higher the marginal tax rate (i.e. the higher the                fiscal  saving  due  to  interest  expenses  deductibility)  the  lower  the  equity  ratio.  Another                parameter of interest is  , which captures the difference in equity value between innovative                start-ups and  traditional young  companies.  A  positive  and  significant  coefficient implies  that,                innovative  start-ups  are  more  inclined  to  use  equity  financing,  compared  to  traditional                companies, confirming the effective of the Growth Decree in making innovative start-ups more                attractive for outsider investors.                       The vector   contains several factors identified by the theories of capital structure as                significant  variables  in  affecting  companies’  financing  decisions.  The  pecking-order  theory                sustains, for example, that a company’s profitability has a negative effect on the choice to use                debt financing [32, 33]. By the other side, the trade-off theory predicts a positive relationship                between profitability and debt financing: profitable companies usually face high tax rates and,                therefore, they should use more debt, lowering the level of equity financing [18]. In addition, the                trade-off  theory  sustains  a  greater  use  of  debt  by  larger  and  more  tangible  companies  [9].                Experience  a  period  of  financial  distress  could  influence  companies’  financing  choices:  a                company with a high probability of bankruptcy should be less inclined to use debt [5, 21, 28].                Therefore, I control for profitability, tangibility, size and bankruptcy probability. Profitability is                defined as the ratio of net income (profit/loss) for the fiscal year expressed as a proportion of                total assets. Tangibility is the ratio of tangible assets to total assets. Size is the logarithm of a                company’ total sales. In line with [6], I proxy financial distress using a revised version of the Z-                score proposed by Altman [3], given that no listed companies are included in the sample.                  4  Sample construction and data description                       Sample data has been provided by AIDA data set, which contains balance sheet data of                Italian stock companies and provides detailed information about innovative start-ups.                      The  empirical  analysis  is  based  on  a  panel  data  set  covering  the  years  2013-2016,                composed  of  Italian  companies  founded  from  01.01.2013  on.  Companies  founded  before                01.01.2013  have  been  excluded  from  the  sample  because  only  a  scant  number  of  innovative                start-ups  results  founded  before  2013.  This  restriction  is  due  to  the  necessity  to  base  the                empirical analysis on a homogeneous sample, composed of young companies, facing the same                financing constraints. In contrast to old companies, for the younger ones debt financing could be                especially expensive or those companies might not have access to it. Moreover, young companies                may have not yet increased their equity base by accumulating earnings [31].                      The AIDA data-set includes 350,817 companies founded starting from 01.01.2013 on. In                order to obtain a panel data set balanced for year of companies’ foundation, companies having                missing data for some of the relevant balance sheet numbers have been dropped. Moreover the                sample do not include companies having inconsistent data (i.e. negative values of total assets,                debt,  tangible  assets  or  sales),  and  companies  belonging  to  financial  sectors  or  to  industries                having  no  innovative  start-ups.  Finally,  by  excluding  outliers  (identifies  applying  Tukey’s                method [40], based on a boxplot displaying upper extreme values of data set) the final sample                has been obtained, consisting of 300,771 firm-year observations for 107,281 companies. Sample                construction and composition is presented in Panel A of Table 1.                      The group of innovative start-ups is composed of 2,143 companies and 5,593 firm-year                observations. Among the innovative start-ups, only 256 have balance sheet data available for                2013 fiscal year (i.e. companies founded in 2013). The number of observation for the following                                                               53","years  increases  strongly,  reaching  the  value  of  2,143  in  2015.  The  distribution  of  profitable                companies, shows that on average, 67.82% of sample observation refers to companies paying                taxes and having an incentive to use debt financing (due to interest expenses deductibility) in                order  to  benefit  from  tax  savings.  The  share  of  profitable  companies  increased  continuously                from 2013 to 2016, going from 57.43% to 67.82%.                      Panel C of Table 2 provides summary statistics of the variables included in the empirical                model. The equity ratio ranges between 0 and 1, reaching a mean value of 0.314. On average, 2%                of sample observations come from innovative start-ups. The marginal tax rate ranges from 0 to                27.5% and has a mean value equal to 18.6%.                                           Table 1: Sample formation and descriptive statistics                 Panel A: Sample formation                                                                         All Companies      Innovative Start-ups                 Companies founded starting from 01.01.2013                 350,817              5,144                 Companies having missing data                              203,040              2,303                 Financial companies                                         3,227                 7                 Companies having inconsistent data                         28,714                551                 Companies in sectors without innovative start-ups           4,368                 0                 Outliers                                                    4,187                140                 Final Sample – Number of Companies                         107,281              2,143                 Final Sample – Observations                                300,771              5,593                  Panel B: Final Sample and Status of Companies                 Fiscal   All companies       Innovative start-ups                Profitable companies                 Year     Observations   Observations   Share of Total    Observations        Share of Total                 2013       24,384           256           1.05%            14,003               57.43%                 2014       61,825          1,051          1.7%             40,004               64.71%                 2015       107,281         2,143           2%              72,939               67.99%                 2016       107,281         2,143           2%              77,040               71.81%                 Total      300,771         5,593         1.86%             203,986              67.82%                  Panel C: Descriptive statistics, pooled for year 2010-2014 (171,425 observations)                        Equity ratio   Innovative start-ups   MTR   Profitability   Tangibility   Size   Z-score                 Mean     0.314           0.019         0.187      0.034         0.143       2.445     2.107                 SD       0.291           0.135         0.128      0.166         0.229       2.326     1.716                 Min        0              0              0          -1           0           0        -9.615                 Max        1              1            0.275        1            1         11.110     9.998                 Note: Panel A shows the sample formation. Panel B shows the yearly distribution of observations, respectively for all                 companies included in the sample and for innovative start-ups only. Panel C presents the descriptive statistics for all the                 variables included in the empirical model.                 Equity Ratio is the value of equity expressed as proportion of total liabilities; MTR is the company-specific marginal tax                 rate; Innovative start-ups is the dummy variable identifying innovative start-ups; Profitability is the ratio of net income                 (profit/loss) expressed as a proportion of total assets; Tangibility is the ratio of tangible assets to total assets; Size is the                 logarithm of companies’ total sales; Z-score is a variant of the Altman’s [3] bankruptcy probability.                   5  Estimation results                       Strong  evidence  that  fiscal  considerations  affect  companies’  capital  structure  has  been                provided by the empirical analysis performed through ordinary least square estimations, with                robust standard errors adjusted for heteroscedasticity.                      The first regression has been performed excluding the companies’ characteristics from the                model and focusing exclusively on the link between equity ratio and fiscal variables. The results                (Column 1 of Table 2) show that the marginal tax rate has a significant negative impact on equity                ratio, confirming that the higher is the marginal tax saving due to interest expenses deductibility                the lower is company’s likelihood to finance through debt. By the other side, it emerges that                                                               54","innovative start-ups have an equity ratio significantly higher than traditional companies. This                result confirms the hypothesis that innovative start-ups are more likely to attract new private                investments, resulting more incline to use equity financing rather than debt.                      When I control for companies’ characteristics, the estimation results (Column 2 of Table 2)                confirm strongly the predictions of the trade-off theory. First, company’s profitability negatively                affects the value of equity financing, confirming that more profitable companies are more likely                to  prefer  debt  financing. Second,  the  results show  that  the  higher is  the companies’  size,  the                lower is the use of equity financing, confirming that larger companies are more likely to increase                debt financing [17]. Third, it emerges that the use of equity financing is negatively linked to the                value of tangible assets: companies having higher tangible assets display a higher propensity to                use debt financing, because these assets can be used as collateral in a debt contract and they are                promptly  marketable  in  the  case  of  short-notice  liquidation  (see,  for  example,  [5]).  Finally,                contrary to expectations, I find that companies having higher bankruptcy probability (a lower Z-                score) are less likely to finance through equity.                      To control for common business cycle effects I add to control variables yearly dummies                (Column 3 of Table 2); to take into account possible sectorial differences in financing choices, I                add sectorial dummies (Column 4 of Table 2); to account for both these effects I insert both                yearly  and  sectorial  dummies  (Column  5  of  Table  2).  The  inclusion  of  yearly  and  sectorial                dummies does not change the main results: the estimated coefficients for innovative start-ups                are still positive in all the regressions and highly statistically significant. The strongly negative                effect of the fiscal variable on equity financing persists after the inclusion of additional dummies.                      Considered that the value of the dependent variable is only observed when it is greater                than  zero,  a  truncated  estimation  procedure  is  used  to  test  the  robustness  of  the  OLS                estimations. The empirical results (Column 6 of Table 2) confirm that fiscal considerations affect                significantly companies’ financing decisions. The MTR keeps its negative effect on equity ratio,                such as the dummy for innovative start-ups keeps its positive effect.                                                    Table 2: Estimation results                                                  (1)       (2)       (3)       (4)       (5)        (6)                                                -0.290***   -0.348***   -0.337***   -0.344***   -0.332***   -1.806***                 MTR                                                (0.005)   (0.006)   (0.006)   (0.006)    (0.006)   (0.014)                                                0.116***   0.100***   0.105***   0.062***   0.067***   0.140***                 Innovative start-ups                                                (0.006)   (0.005)   (0.005)   (0.005)    (0.005)   (0.008)                                                          -0.093***   -0.105***   -0.101***   -0.115***   -0.034*                 Profitability                                                          (0.005)   (0.005)   (0.005)    (0.005)   (0.012)                                                          -0.090***   -0.082***   -0.113   -0.106   -0.095***                 Tangibility                                                          (0.003)   (0.003)   (0.003)    (0.003)   (0.007)                                                          -0.048***   -0.046***   -0.047***   -0.044***   -0.140***                 Size                                                          (0.000)   (0.000)   (0.000)    (0.000)   (0.001)                                                          0.066***   0.067***   0.066***   0.068***   0.197***                 Z-score                                                          (0.001)   (0.001)   (0.001)    (0.001)   (0.001)                 Yearly dummies                   NO        NO        YES       NO        YES        YES                 Sectorial dummies                NO        NO        NO        YES       YES        YES                 Observations                   300,771   300,771   300,771   300,771   300,771    300,771                 Innovative start-ups (observations)   5,593   5,593   5,593   5,593     5,593      5,593                  Note: Columns (1) – (5) have been estimated using the pooled OLS Estimator; column (6) has been estimated using the truncated                 regression. The dependent variable is Equity Ratio, the share of equity to total liabilities; MTR is the company-specific marginal tax                 rate; the dummy Innovative start-ups identifies innovative start-ups; Profitability is the ratio of net income expressed as a proportion of                 total assets; Tangibility is the ratio of tangible assets to total assets; Size is the logarithm of companies’ total sales; Z-score measures                 bankruptcy probability [3]. Column (1) controls exclusively for the effect of fiscal variables; in (2) I add companies’ characteristics; in                 (3) I control for yearly dummies; in (4) I control for sectorial dummies; in (5) and (6) I control for yearly and sectorial dummies.                 Superscript asterisks indicate statistical significance at 0.01 (***), 0.05 (**) and 0.10 (*).                                                                55","6  Conclusions                       This  paper  provides  convincing  evidence  that  fiscal  considerations  affect  companies’                capital structure. In line with the theory of corporate finance, which predicts that taxes could                affect companies’ capital structure, the empirical analysis shows that, due to interest expenses                deductibility, companies prefer debt to equity financing. Accurate company-specific marginal tax                rates proxy for the fiscal advantage of debt-financing.                      Moreover, this paper tests the effects of the Italian Growth Decree, which introduced fiscal                incentives for individuals or legal entities investing in innovative start-ups. The empirical results                show  that  innovative  start-ups  are  more  likely  to  prefer  equity  finance,  confirming  the                effectiveness  of  the  public  action  in  affecting  companies’  financing  choices  indirectly,  making                innovative start-ups more attractive for outsider investors.                   Acknowledgements                       I am very grateful to Robert Jahoda, Tommaso Reggiani, and the participants at the 23                                                                                                          rd                International Conference “Current Trends in Public Sector Research”, Masaryk University (Brno,                24-25 January, 2019), for helpful comments. I thank two anonymous referees for constructive                comments that have helped me to improve the quality of this paper.                   References                 [1.]  AGHION, P., HOWITT, P. 1998. Endogenous Growth Theory. 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Addison-Wesley.                                                                       57","The Nostalgianomics of Living Preferences:                                        Where Would You Like to Live?                                                                                             c                                           a                                                                  b                             COLE David ; GUBALOVÁ Jolana , KUBIŠOVÁ Ľuboslava ,                                                                              d                                            MURRAY SVIDROŇOVÁ Mária                                           Faculty of Economics, Matej Bel University, Slovakia                     a              b                   c                     d                      david.cole@umb.sk;  jolana.gubalova@umb.sk;  luboslava.kubisova@umb.sk,  maria.murraysvidronova@umb.sk                Abstract                 In this paper,  we argue that a counter-balance is needed to metropolises, especially in small European                countries. Rural areas and small towns are necessary and must remain economically viable from the point                of  view  of  public  administration.  The  objective  of  the  paper  is  to  investigate  the  concept  of                nostalgianomics  from  the  point  of  view  of  living  preference  in  Slovakia.  Using  a  new  measurement                scheme,  we  analysed  the  preferences  of  where  people  would  like  to  live  with  a  sample  of  almost  500                individuals and introduce a new term of nostalgianomics – a concept that nostalgic sentiment can be used                as an economic and creative force as an incentive for investment and housing. In  this paper, we  focus                especially  on  the  area  of  living  preferences  and  urban  planning.  Among  the  methods  employed  are                questionnaire survey and basic statistical analysis. The main findings indicate that Slovaks prefer to live in                smaller  municipalities  and  in  areas  outside  of  large  metropolitan  areas  –  the  attraction  is  driven  by  a                nostalgic sentiment.                Keywords: Metropolises verzus Small towns; Living preferences; Nostalgianomics; Slovakia.                 JEL Classification: R21, R23                   1  Introduction                       Around the world, cities have grown to mega-proportions with currently 512 cities having                a population of over 1 million. It would seem that concentrated agglomeration is an economic                necessity and a continuation of the urban evolution based on Marshall’s concept of proximity                reducing transport cost [13]. Firstly, firms need to locate near suppliers or customers to save                shipping  costs;  secondly,  clustering  of  like-minded  businesses  help  to  stimulate  innovation                within a specific field; and finally the intellectual spill over helps create new businesses, thus                adding  to  the  agglomeration.  As  such,  in  modern  society,  agglomeration  becomes  economic                destiny with all other territories relegated to insignificance or whose only purpose is focused on                the primary sector and basic commodity production.                      Giannone research on American cities has found that regional convergence, where poorer                areas become wealthier, began to stall in the 1980s. She attributed this to a skills based technical                changes  giving  an  advantage  to  agglomerated  areas,  thus  smaller  towns  and  villages  will                continue to suffer [8].                      Even though there is an accumulative advantage to size, the will of the individual needs to                be considered. Giddens [10] asserts that each individual is continuously in search for his own life                narrative in which living space plays an important role. He states “A person's identity is not to be                found  in  behaviour,  nor  -  important  though  as  this  is  -  in  the  reactions  of  others,  but  in  the                capacity to keep a particular narrative going.” He refers to this as the “ongoing 'story' about the                self.” Individuals strive to complete their ‘life story’ by choosing options that will leave them                with  a  respectable  legacy  that  can  be  expressed  in  terms  of  both  material  attainment  and                societal status. The rural counter-parts to the urban centre must also be able to provide this                important narrative.                      City  planning  and  design  firm  Sasaki  Associates  [17]  conducted  a  survey  with  1,000                respondents in six “progressive” American cities. They found that city dwellers are drawn to                admiration of historic buildings (58%) and find their fondest memories in outdoor setting such                                                               58","as a park or on the street (65%). In a paradox, however, 58% of the respondents use their cars                most frequently for transportation and 41% complained of traffic and 23% for lack of parking.                Like it or not, cars are a dominant feature of city living and an antithesis for the creative city.                This survey suggests that cities have a shortage of more historic and humanistic markers that                define us as a society. As such, the city is a great place for opportunity but it is also a place that is                cold and brutal; hence, many individuals seek to find their refuge in the suburbs and exurbs that                surround the city core. It suggests difficulties for the more marginalized people in obtaining the                higher goals.                      It  also  ignores  some  basic  realities  for  Europe.  A  decline  in  population  is  leading  to  a                hollowing  out  of  the  countryside,  causing  depopulation  in  large  areas  of  many  countries,                especially in Central Europe. Work that can be described as “computer gazing” can be performed                from anywhere and calls into question the need for a mass gathering in a city centre on a daily                basis. Dumont [5] states that because of the high density of population and activities, large urban                areas also suffer from diseconomies of scale: higher property prices, time lost in transports, etc.                This begs the question: is there now a viable alternative to agglomerated living and is this the                only true model going forward?                      Small towns and their idyllic settings are looked upon nostalgically, but are forgotten in                the  grand  scheme  of  economic  progress.  A  German  study  [6]  shows  that  city  regions  are                growing, in Central and Eastern Europe (CEE) as well yet half of Europeans live in shrinking                mostly  rural  regions.  Even  with  the  above-mentioned  problems,  the  siren  song  of  mass                agglomeration  as  economic  necessity  continues  unabated,  especially  due  to  the  preferred                concepts of modernity and its focus on future economic progress. To add a needed antithesis to                this  view,  we  introduce  a  concept  of  nostalgianomics  and  its  focus  on  individuals  and  their                historical identity. This sentiment could be used as a solution to the problem of depopulation of                more rural areas.                 1.1 Nostalgianomics versus Modernity in Terms of Living Preference                      In a pure neoclassic concept, cost would dictate that as one area becomes too expensive or                too inconvenient to live in, people would migrate to a more inexpensive locations looking for                better opportunities and a different style of life. Spatially, this rebalancing does exist outside of                metropolitan  areas,  where  cheaper  suburbs  and  exurbs  spring  up  to  meet  the  demands  for                appropriate  living  space.  An  even  more  profound  cost  advantage  would  be  to  move  further                afield, to the less populated rural areas outside of the influence of a metropolitan area. The cost                advantage of the rural area needs to be viewed from both an economic and social point of view.                      The urban area is the experimental ground for new concepts in modernity and economic                progress  often  necessitated  by  its  growth.  CEE  nations  under  the  auspice  of  a  command                economy focused myopically on the future with their profound adherence to high modernity – a                concept with strong confidence in scientific and technological progress; a reliance on experts                (scientists,  engineers,  and  bureaucrats);  an  attempt  to  master  nature  to  meet  human  needs;                spatial  ordering  (city  planning,  housing,  and  transportation);  and  a  general  disregard  for                historical, geographical, and social context in development [18]. The result was a cityscape of                concrete and cold-grey tedium. This was especially true for the larger cities of Central Europe                where  blocks  of  flats  (so-called  “paneláky”)  visually  dominate  the  living  areas  and                neighbourhoods of a city.                      The post-cold-war period saw a change in CEE countries from high modernity to a unique                form of post-modernity. This new form of modernism can be described as a hyper-technological                version  of  modernism  [1].  The  unenviable  position  of  having  to  play  catch-up  to  western                countries  led  to  a  more  distinct  worship  of  technological-led  post-modernism.  In  terms  of                geographical  development,  the  urban  centres  become  the  launching  point  for  this  new                modernity, especially the capital city often at the expense of their rural counterpart [3].                      Modernity, and especially high-modernity, disregards the past, overlooking the historical                markers  that  gives  us  our  identity.  This  historical  desire  could  be  described  as  a  state  of                nostalgia  –  a  sentimentality  for  a  past  time  or  place  associated  with  happiness.  In  terms  of                demographic  spatial  relationship,  the  small  town  is  rooted  in  nostalgia  and  urban  centres  in                                                              59","modernity.  Our  focus  is  on  how  nostalgic  sentiment  can  influence  the  living  preferences  of                people, i.e. how nostalgia can “beat” modernity.                      Batcho [2] found that even though nostalgia can be triggered by negative stressors in the                environment,  it  could  result  in  successful  development  of  methods  for  coping,  planning,  and                implementing strategies for a more positive outcome. Zhou et al. [21] found that nostalgia leads                to a sense of social support and connections and a way to cope with loneliness. In a study by                Vess et al. [20], subjects who thought of nostalgic memories had better coping mechanisms than                subjects whose thoughts were of exciting future experiences. Nostalgia has a place in modern                society and as such, we feel the need to establish the term nostalgianomics as a behavioural                influence with living preferences.                      Nostalgia has an advantage over modernity in that historical markers are forever open to                reinterpretation. As individuals engage in nostalgic sentiment, a choice-supportive bias will find                the positive in the past while minimizing the negatives. This means that an investor looking for a                nostalgic connection might be willing to overlook negative aspects of that choice, even when                there is little economic advantage. Nostalgia can have a fatalistic flaw if it holds too ideologically                to past concepts that are unlikely to return, i.e. the exclusion of innovation.                      Moreover,  the  smaller  towns  and  village  have  a  unique  form  of  bonding  with  a  social                capital based on strong relations with family, friends and neighbours that feature a high level of                loyalty,  homogeneity  and  trust.  Communities  with  a  strong  local  institutional  infrastructure                allowing local people to interact with each other help build bridges to social capital [19]. When                viewing social capital that outside of mere economic considerations, it is the smaller community                that could have an advantage with a well-organized and established local support system.                      Giddens [10] suggests that we live in an era of disembeddedness of time and space, where                individuals no longer need to be in physical presence with each other in order to interact in what                he refers to as time-space distanciation. Modern information and communication technology is                continuously allowing for the untethering of work to a specific location. This makes alternatives                to  urban,  suburban,  and  exurban  living  possible.  One  of  the  “attractions”  of  living  outside                metropoles can be nostalgia.                      A nostalgic sentiment is in short supply in the metropolitan centre but can be found in                abundance  in  the  rural  region,  e.g.  the  non-economic  social  institutions.  This  presents  a                competitive advantage based on the abundance of nostalgic elements found in rural areas and                small towns. Authors [11, 14, 15] insist that regional competitive advantage needs to include not                only  \"hard\"  productivity  but  also  take  into  consideration  \"softer\"  dimensions  of  the  social                economy.  When  applying  the  softer  dimensions  to  regional  development,  it  is  the  specific                feature, attraction or uniqueness which has a certain value for customers/consumers in a region                (residents, tourists, businessmen, and investors), and these customers prefer this value over the                offerings of competing regions [4]. For the more rural setting, the competitive advantages are                “soft resources” (landscape, historical, cultural heritage). These soft resources can be utilized by                the small town community for the nostalgic sentiment they embody.                      In our research, we wanted to investigate the concept of nostalgianomics from the point of                view of living preference by focusing on a country where the notion of modernity (represented                by cities) are in stark contrast to nostalgic sentiment (represented by smaller towns). Slovakia,                the focus of our research, contains two larger cities on opposite ends of the country. The capital                city, Bratislava, plays the role of governmental, financial, and gateway centre to the rest of the                country. In addition, with two major car companies located within the commuter zone, it also                plays host to automobile manufacturing. As such, Bratislava has 11% of the population and a                GDP that is 2.4 times the national average [6]. Add to this, the near convergence of the Trnava                and Nitra commuter zone, you have a population containing almost a fifth of the country (fig. 1).                Slovakia can only claim to have one metropolitan area as its other cities are considered to be                medium and small urban areas. Still, 63% of the population live outside these urban commuter                zones [16].                                                                   60","Figure 1: Slovakia’s urban centres with surrounding commuter core                               Source: Organization for Economic Co-operation and Development.                       The cost  burden  of  proximity  to  urban  or even  suburban  living  creates a need  to  limit                one’s tangible assets (cars, home size, yards, etc.) due to affordability. If economic benefits of                living were measured through tangible accumulation rather than the intangible experiences of                city life, then rural communities could be seen as having a higher utility.                  2  Methodology for gauging living preferences                       Slovakia, because of the aforementioned conditions, presents us with a unique condition                for  the  study  of  living  preferences  and  thus  fulfil  the  objective  of  the  paper,  which  is  to                investigate the concept of nostalgianomics from the point of view of living preference. To gauge                the preference for living conditions, we have engaged a method of a survey distributed widely                through social media and through mass e-mail, i.e. there was no sample selection, we spread the                link on the questionnaire and by the snow-ball method it was shared among other respondents.                The  survey  was  conducted  in  months  September  –  November  2018,  the  total  number  of                respondents  was  496.  The  survey  is  not  representative  (and  as  such  it  is  presented  in  the                results), yet it provides interesting insights into this topic. Respondents were asked 1) to rank                hand-drawn pictures of streets and 2) historic micro-regions of Slovakia in order to answer our                research  question:  Where  would  Slovak  citizens  like  to  live  and  how  it  can  be  linked  to  the                concept of nostalgianomics?                      To get a better idea of living sentiment, we chose to use 6 hand-drawn pictures of street                settings together with a graphical representation of location (fig. 2). The choice for hand-drawn                illustrations was an attempt to “alienate” the viewer from the reality of what might be felt if the                images were actual photos. Creating penned black and white images created the illusions of the                reality of living preferences without the emotional involvement of real photos, only indicating                sentimental feeling of bucolic villages and smaller municipalities. The respondents were asked                to rank all images in terms of preference with a 1  choice, 2  choice, 3  choice and so on.                                                              st                                                                        nd                                                                                  rd                                          Figure 2: Illustrations used in living preferences                Picture A- A Bratislava street scene with “panelák” - urban setting                                                                                61","Picture B- Suburb setting with new small homes just outside of Bratislava- suburban setting                        Picture C- The Smaller cities of Slovakia- smaller urban setting                          Picture D- Suburb of smaller Slovak cities- smaller city suburbs                        Picture E- Small Slovak Town- Population 10-20 thousands                          Picture F- Village living at least 60km from a city.                          Source: Illustration by David Cole.                       With  the  second  question,  we  wanted  to  find  out  which  region  of  Slovakia  holds  any                special interest to the respondents. The question was how to divide the regions in a logical way.                Modern day Slovakia is divided into 8 different regions (kraj) named after the major city of each                region.  All  regions  contain  too  many  different  varieties  to  hold  any  real  distinction  for  the                respondents. Likewise, dividing the country based on counties (okres) would be too unwieldy as                there  are  79  counties  to  choose  from.  To  form  a  more  recognizable  region,  we  used  an  old                historical  map  of  Slovakia  with  25  distinct  regions  each  with  a  historical  cultural  (nostalgic)                identity. The respondents were asked to choose and rank the top 6 regions they found to be                most interesting for them. As the data set for 25 areas is too large and nebulous, we grouped the                regions  together  to  form  8  relatively  homogenous  regions  (fig.  3).  The  combining  of  areas                created  some  statistical  anomalies  with  calculation  such  as  the  Trenčin-Žilina  area  having  5                combined historical areas and the Schengen border area having only two. The figures should                therefore be viewed in qualitative terms rather than absolute numerical terms.                                                                    62","Figure 3: Combined distinctive areas created from the historical areas                                   Source: Authors.                  3  Results and Discussion                       As already mentioned our e-mail listing was rather limited to the local region and did not                include as many individuals from Western Slovakia as we would have liked, i.e. from Bratislava.                This  is  a  limit  of  our  research,  yet  the  results  are  interesting  and  bring  new  and  surprising                insights. In tab. 1, the results can be seen by age and preferences with a scale between 1 (low                favourability) to 6 (high favourability).                            Table 1: Ranked preference of living space according to the pictures and location                   Age        # of    A Bratislava   B Bratislava   C Regional   D Regional   E Towns-   F Villages                            response     Urban     Suburban   cities of SK   cities/suburb   pop. 10-20k                 under 20     35         1.74        3.14        3.83        4.31        4.00        3.97                 20-30        270        1.80        3.14        3.82        4.39        4.09        3.86                 30-40        69         2.06        3.09        3.99        4.67        3.86        3.48                 40-50        57         1.75        2.93        3.93        4.88        3.75        3.67                 Over 50      47         1.43        2.85        3.81        4.81        4.13        3.98                 Tot. avg.    478        1.79        3.08        3.86        4.52        4.01        3.80                 # response in each area   43         12         160          57          69         154                Source: Authors.                       The results are rather consistent across all age groups. The highest utility can be found in                the suburbs of regional cities, followed by towns, then villages. Bratislava and its surrounding                commuter zone are much less popular. It is interesting that the younger generation is not so                eager to go to the big cities and they have a high affinity to the small towns and villages, i.e. the                nostalgic sentiment can be noted also at the younger generation.                      We  also  asked  the  respondents  which  picture  closely  resembles  the  place  where  they                lived, i.e. about which pictures they feel nostalgic the most. If the respondent stated that their                current place of residence was either their first or second choice of living, we could state that                they were generally happy about their current living situation (results in tab. 2). Again, the area                around  Bratislava  has  low  favourability,  yet  villages  score  highly.  Suburb  living  around  a                regional city (in Slovakia, this means a population between 70 and 80 thousand) are also seen as                having the highest utility.                                                                         63","Table 2: Satisfaction with current place of residence                 Respondents who voted   A Bratislava   B Bratislava   C Regional   D Regional   E Towns-   F Villages                 1 /2  place in their   Urban      Suburban   cities of SK   cities/suburb   pop. 10-20k                  st                     nd                 current residence       43%         54%         66%         79%         66%        76%                Source: Authors.                      In the second question, the 8 aggregated areas of the country found the mountainous area                of  Slovakia  to  be  the  most  interesting  which  is  what  was  expected  as  these  areas  could  be                considered  the  playground  regions  of  Slovakia  (tab.  3).  The  economic  regions  of  the  country                (Bratislava,  Nitra  –  see  Fig.  1)  ranked  quite  low.  455  respondents  identified  were  they  were                currently living. Of these individuals, the High Tatra and Prešov Košice regional had the highest                ranked satisfaction as judge by the voting of 1  or 2  place for their own areas. Nitra is the                                                                    nd                                                              st                current economic hot spot of Slovakia with Amazon and Land-Rover Jaguar setting up shop in                this region; however, it has the lowest score of interest (10%).                    Table 3: Ranked preference of areas of the country found to be most interesting (on a scale of 0 to 6)                                                       Trenčin-  High-  Banská B.   SC     Prešov-  Schengen                                       Bratislava   Nitra   Žilina   Tatras   Zvolen   Slovakia   Košice   Border                 Ranked score            1.75    1.35    3.62    5.89     3.28      1.2     3.41     0.51                 # of res. in each area   17      20      77      66      158       50       55       12                       st                          nd                 Voted 1 /2  in own      41%     10%     29%     77%     35%       38%      56%      33%                 area                Source: Authors.                      During socialism, small towns of CEE were supported by decree, i.e. all regions had jobs                and a purpose under a command system [9]. Despite all of its failures, the communist regime did                provide  a  certain  level  of  social  support  to  smaller  towns  not  found  today.  After  1989,  the                ensuing  decade  of  the  nineties  meant  a  period  of  disorganization  when  local  firms  lost  old                customers and even if they found new customers, they lost old suppliers [12]. This period lasted                longer than expected and led to the notion that continuous decline is inevitable. As such, there is                a reflexive response of futility towards development in small towns and regions outside of a                commuter zone thus overlooking potential opportunities based on nostalgic sentiment. Despite                this long period of economic decline, this survey demonstrates a desire to live (or to stay) in the                rural towns and villages that is not being reflected in current economic thought.                  4  Conclusion                       This research contained 496 responses and had some limitations especially with regional                distribution, regional variation, and age distribution. Though it is not thoroughly conclusive, it                could  be  viewed  as  a  snapshot  highlighting  some  important  motivations  in  terms  of  living                preferences in Slovakia. In general, we can say that the respondents had a preference for less                crowded and less urban settings, mostly driven by nostalgic sentiment. It is a common thought                that young people would jump at the chance to leave a “dead-end town” that has little in the                ways of excitement. This research indicates that this is not necessarily the case as small towns                score highly also among those under the age of 30.                      From  our  research,  we  have  found  a  strong  desire  for  smaller  community  living                arrangements that extend even down to the level of village living. As much of CEE urban areas                were built under a high-modernity philosophical mindset (e.g. large blocks of flats), the towns                and villages retain a more historical atmosphere, with detached homes and historical buildings.                As  such,  we  established  a  term  for  nostalgic  influence  -  nostalgianomics.  In  the  urban,  core,                historic preservation has gained high importance as new construction cannot mimic the style of                the past. Unfortunately, in the rural settings, many historic structures are allowed to rot. These                towns  and  their  existing  structure  have  an  emotional  appeal  that  could  be  used  for  rural                                                               64","revitalization  which  is  further  object  of  our  current  VEGA  research  project  (V-18-101-07-                101312: Abandoned Slovakia: Effective solutions to the creative reuse of abandoned properties                in non-urban areas).                  References                 [1.]  APPIGNANESI R., SARDAR Z., CURRY P. 1995. Post-modernism for beginners. Icon Books, Cambridge.                 [2.]  BATCHO 2013. Nostalgia: Retreat or support in difficult times? The American Journal of Psychology;                     126(3):355-367.                [3.]  BORSEKOVA, K. et al. 2015. Nostalgic Sentiment and Cultural and Creative Industries in Regional                     Development: A Slovak Case Study. Quaestiones Geographicae; 34(2):53-65.                 [4.]  BORSEKOVÁ, K.; VAŇOVá, A. 2011. Competitive Advantage of Slovak Republic. International Journal                     of Multidisciplinary Thought; 1(4):237-257.                [5.]  DUMONT G., 2015. [Online] Une idéologie de la métropolisation? Available on                     https://www.cairn.info/revue-population-et-avenir-2015-2-page-3.htm                [6.]  BBSR, 2013. [online] Local forces, criteria and success factors for steering sustainable urban                     development in smaller cities. Available on                     https://www.bbsr.bund.de/BBSR/EN/Publications/BMVBS/SpecialPublication/2013/Cittaslow.ht                     ml?nn=395434                [7.]  Eurostat, 2016. Urban Europe, Statistics on cities, towns and suburbs. Luxembourg: Publications office                     of the European Union.                [8.]  GIANNONE, E., 2017. Skill-Biased Technical Change and Regional Convergence. Society for Economic                     Dynamics, Meeting Papers 190.                [9.]  GAWDIAK, I.Y., 1989. Area Handbook Series: Czechoslovakia: A Country Study. Washington, D.C.:                     Federal Research Division, Library of Congress.                [10.] GIDDENS, A., 1991. Modernity and Self-Identity. Stanford: Stanford University Press.                [11.] KITSON, M., MARTIN, R., TYLER, P. 2004. Regional Competitiveness: An Elusive yet Key Concept?                     Regional Studies; 38(9):991 – 999.                [12.] MARIN D., SCHNITZER, M. 2005. Disorganization and financial collapse. European Economic Review;                     49(2):387-408.                [13.] MARSHALL, A., 1920. Principles of Economics. London: MacMillan.                [14.] MARTIN R., 2002. [online] A study on the factors of regional competitiveness. Available on                     https://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/3cr/competitiveness.pdf                [15.] MARTIN R., 2005. Thinking about regional competitiveness: Critical issues. East Midlands                     Development Agency, Nottingham, UK.                [16.] OECD, 2012. [online] Functional urban areas in OECD countries: Slovak Republic. Available on                     http://www.oecd.org/cfe/regional-policy/functionalurbanareasbycountry.htm                [17.] Sasaki Associates, [online] The state of the city experience. Available on                     http://www.sasaki.com/blog/view/487/                [18.] SCOTT, 1998. Seeing like a state: How certain schemes to improve the human condition have failed.                     New Haven: Yale University Press.                [19.] ŠVIHLOVÁ D., KUBIŠOVÁ Ľ., 2016. Social capital in territorial development planning. In: 19                                                                                                  th                     international colloquium on regional sciences: conference proceedings. Brno: Masaryk University, 402-                     409.                [20.] VESS, M. et al. 2012. Nostalgia as a resource for the self. Self and Identity; 11(3):273-284.                [21.] ZHOU, X., SEDIKIDES C., WILDSCHUTT T, GAO D. 2008. Counteracting loneliness, On the restorative                     function of nostalgia. Psychological Science; 19(10):1023-1029.                                                                   65","Administrative Fragmentation and Productivity of Firms.                                               Case Study: Slovakia                                                             1,a                                      ČERNĚNKO Tomáš  ; PECIAR Vladimír            2, b                                  1                                   Faculty of National Economy, University of Economics in Bratislava, Slovakia                 2                  Institute for Financial Policy, Ministry of Finance of the Slovak Republic, Slovakia; Faculty of Economics and Administration,                                                 Masaryk University, Czech Republic                                            a                   b                                             tomas.cernenko@euba.sk;  v.peciar@gmail.com                Abstract                The administrative structure of Slovakia belongs to the most fragmented in Europe. Several scholars argue                that  administrative  fragmentation  leads  to  weak  institutional  environment  and  therefore  retards                economic  development  on  local  level.  The  aim  of  our  paper  is  to  find  out  whether  the  fragmented                administration  structure  in  Slovak  functional  economic  regions  has  an  impact  on  productivity  of  firms                based in these regions. To prove the assumption, we use regression model and try to explain the change of                firm productivity across FURs by indicators on the FUR structure. First, we calculate the productivity of                firms (TFPR – total factor productivity of revenue) based on data of almost all enterprises in Slovakia. To                describe the structure of FUR we use indicators such as administration effectiveness, fragmentation rate,                concentration of population in the core and the share of built-up area as a proxy for infrastructure. These                are based on data on local government units aggregated to FUR. The results show, that the indicators on                the inner structure of FUR (in the manner of settlements) do not significantly affect the productivity of                firms located in the region. Indicators, that do are those on politico-administrative structure (effectiveness                of local government units and fragmentation rate) and infrastructure (the share of built-up area).                 Keywords: administrative structure; fragmentation; functional urban regions; productivity                JEL Classification: H11, L29                    1  Introduction                       The impact of the fragmented administrative structure was in Slovakia mostly examined in                the context of the quality of public service provision and did not go beyond the boundaries of                individual  local  governments.  In  the  meantime,  however,  more  scholars  are  dealing  with  the                impact of governance and the structure of government in a wider socio-economic context.                      High fragmentation causes, according to Charbit [7], gaps hindering cooperation. These                are: “administrative gap – “mismatch” between functional areas and administrative boundaries,                information  gap  –  asymmetries  of  information  between  different  stakeholders,  policy  gap  –                sectoral  fragmentation  across  ministries  and  agencies,  capacity  gap  –  insufficient  scientific,                technical, infrastructural capacity of local actors, funding gap – unstable or insufficient revenues                undermining  effective  implementation  of  responsibilities  at  subnational  level  or  for  crossing                policies, objective gap – different rationalities creating obstacles for adopting convergent targets                and  accountability  gap  –  difficulty  to  ensure  the  transparency  of  practices  across  different                constituencies” [7; p.16] . All these gaps do significantly affect the quality of government.                      Ahrend et. al [1] deal in their paper with the impact of governance on local productivity.                The object of their research was FURs of several OECD member states – Germany, Mexico, Spain,                United Kingdom and United States of America. Their finding is a significant role of horizontal                fragmentation of administrative structure on the regional productivity.                      Growth in the productivity of cities, based on their size, has been proven, e.g. by Combes et                al. [5; p.2570], who claims that “there are substantial productivity benefits for all firms in denser                areas that are even stronger for more productive firms”. On the other hand, Frick and Rodríguez-                Pose  [10;  p.165]  state,  that  “there  is  considerable  heterogeneity  across  the  world  in  the                relationship between urban concentration and economic growth, which is, to a large extent, a                consequence of contextual factors that have little to do with urban concentration“. In their older                                                               66","paper, do Frick and Rodríguez-Pose [9; p.16] claim that: “larger cities, albeit not the very large                metropolis, can indeed be drivers of growth, but only if the context is favourable“. And that is,                where  the  question  of  quality of  government  again  appears.  Its impact  on  regional  economic                performance has been studied by Crescenzi, R., Di Cataldo, M. and Rodríguez-Pose, A. [6]. They                have found out, that the impact of investments in other than large infrastructural projects has a                highly  significant  connection  with  regional  economic  performance  if  is  interacted  with                government quality.                      In our paper, we would therefore like to take a closer look at the impact of fragmentation                of  the  administration  structure  in  Slovak  functional  economic  regions  on  the  productivity  of                firms based in these regions                  2  Material and Methods                       In order to evaluate the effect of fragmentation of FURs (in terms of spatial and politico-                administrative  aspects  of  FUR)  on  firm-level  outcomes  (TFPR  -  Total  factor  productivity  of                revenueand labour productivity), we combine two rich datasets.                 2.1 Data                      To overcome the problem with lack of data on governance quality, we a proxy indicator –                the effectiveness of local governments. The index is based on structure of expenditures of local                governments. Data on municipal expenditures of Slovak communes in year 2017 comes from the                DataCentre of Ministry of Finance of the Slovak Republic. The data were delivered in the COFOG                classification. The sample includes all communes of Slovakia. In the case of Bratislava and Košice                the original data about expenditures of city districts and the municipal level were aggregated.                      The firm-level data comes from the Registry of Financial Statements and is supplemented                by data from analytical company Finstat s.r.o. The data covers almost all firms in Slovakia and                encompasses  information  from  balance  sheets  as  well  as  profit  and  loss  statements.                Furthermore,  we  are  also  able  to  identify  other  non-financial  characteristics  such  as  size                category, legal form or seat of the firm headquarters. It is crucial to mention that we do not have                data on plant localization but only on firm’s seat. In case of Slovakia it is common for firms to                have firm seat different than the localization of its plants. This fact however presents a major                drawback for our analysis. Even if we have detailed micro data on firm seats, we cannot say with                100 % reliability that certain firm operates in the same city or county. We thus cannot precisely                match  firm  productivity  with  local  area  conditions  as  in  some  cases  we  might  pair  two                completely  unrelated  variables.  If  this  is  true,  then  the  procedure  would  create  serious                measurement error problems and strongly bias our results. We discuss this issue further in the                paper and as we believe, we provide adequate and satisfying solution.                  2.2 Methods                Total factor productivity of revenue                      Our empirical strategy to assess the impact of local government structure and geography                on firm productivity is twofold. First, we estimate firm TFPR using control function approach                developed by Levinsohn and Petrin [12] . In production function estimation literature, the major                obstacle  for  consistently  estimating  TFP(R)  is  correlation  between  unobserved  productivity                shocks and input levels. As Petrin, Poi and Levinsohn [15] state, profit-maximizing firms respond                to positive productivity shocks by expanding output, which requires additional inputs. Negative                shocks lead firms to pare back output, decreasing their input usage. When true, ordinary least                squares (OLS) estimates of production functions are biased and, by implication, lead to biased                estimates of productivity. Various methods have been proposed to tackle such simultaneity issue                and,  according  to  their  approaches, is  possible  to  group  them  in  three families:  Fixed Effects                (FE), Instrumental Variables (IV) and Control Function (CF) [13]. We use the CF approach and                                                                 67","rely on intermediate inputs as a proxy for unobserved productivity shocks (the benefits of using                Levinsohn-Petrin approach are described in Petrin, Poi and Levinsohn [15]).                      We use data on sales, value added, intermediate consumption, capital, personnel costs and                number of employees to calculate nominal TFP - revenue total factor productivity (TFPR) - and                labour  productivity.  To  have  economically  meaningful  estimates,  we  restrict  our  analysis  to                firms  with  more  than  one  employee  and  also  drop  firms  with  zero  output.  Slovak  firm                environment is very specific and large fraction of companies are micro firms with zero or one                employees. Many of these firms are “zombie” firms or solely created for tax purposes. Therefore,                excluding them from estimations is desirable in order to overcome downward productivity bias.                Public  sector,  finance  and  real  estate  companies  are  also  excluded.  For  the  purpose  of  the                analysis, sectors are defined at 3-digit NACE Rev. 2 level. In the case of TFPR estimation we are                very conservative and sectors with less than 100 observations are not taken into account. By                dropping  these  sectors,  we  want  to  achieve  precise  estimates  of  input  elasticities  and  not  to                worry about sample size issues.                      We work with three-factor log-linear Cobb-Douglass production function (capital, labour,                intermediate inputs) as for example in Dias et al. [8]. We apply the Levinsohn-Petrin approach to                a robust panel of more than 1 million firm-year observations covering the period of 2004 – 2016                and calculate desired nominal productivities. The fact that we do not deflate and do not estimate                real TFP stems from recent research developed by Atkin, Khandelwal and Osman [2]. They argue                that  real  TFP  (TFPQ)  performs  poorly  in  productivity  measurements  because  of  variation  in                product specifications across firms. They incorporate quality metrics in productivity estimations                and show that as quality productivity is negatively correlated with TFPQ, TFPR may perform                better  at  capturing  capabilities  in  settings  where  better  firms  make  products  with  more                demanding  specifications.  Our  TFPR  regressions  are  performed  sector  by  sector  (performing                production function estimates sector by sector allows us to estimate sector specific input/output                elasticities and distinguish among different technologies used by firms in different sectors. We                consider 3-digit NACE Rev. 2 level to be suitable disaggregation because 2-digit levels are too                broad to capture specific elasticities, meanwhile in the 4-digit we drop significant number of                sectors which is not desirable) as follows:                 where       represents  log  of  firm  gross  output  (sales)  ,     stands  for  log  of  personnel                costs,               stands  for  log  of  intermediate  inputs.  We  also  incorporate  year  fixed                effects  . Term     is the idiosyncratic error and    represents the unobserved productivity.                Subscripts s, i, t stand for sector, firm and year respectively. Three remarks must be made here.                Firstly, for capital we use total tangible assets from the balance sheets. We do not incorporate                intangibles  as  we  use  them  as  an  explanatory  variable  in  the  second  part  of  the  empirical                analysis. Secondly, we use personnel costs rather that number of employees. By doing so we                control  for  differences  in  worker  skills  and  education.  Firms  operating  with  higher  share  of                highly educated individuals should be more productive and this fact then must be reflected in                more  expensive  labour  input.  Simple metric  of  number  of  employees  would  not  differentiate                between quality of human capital. Intermediate inputs are calculated as the sum of purchased                merchandise, goods and services and energy costs.                      After  the  production  function  estimations  are  performed,  we  continue  with  the  second                part of our empirical analysis. We calculate TFPR for every firm in every year and every sector.                We also calculate yearly TFPR growth rates (as differences in log TFPRs). Using data on nominal                value added and number of employees we calculate labour productivity. These three variables                then represent our main dependent variables that we relate to our regressors of interest and                various firm specific controls. We follow OECD [11] approach and high-dimensional fixed effects                cross section estimation to assess the impact of local geographic and public sector conditions on                firm-level productivities. Since our main explanatory variables are only available for one year,                we use data on productivity levels and growth rates from the last available year, which is 2016                (to account for proper panel data setting and control for unobserved heterogeneity is desired                and will be the aim of further research. We are left with 120 thousand firm observations). We                 build  on  Gal  [11]  and  relate  firm  TFPR  growth  to  the  growth  of  the  so  called  “productivity                                                              68","frontier” in the Neo-Schumpeterian framework (catch-up-to-frontier setting). Following OECD                [11] our catch-up-to-frontier regressions are set up as follows:                         where                   stands  for  firm’s  i  TFPR  growth  between  2016  and  2015,                                   defines TFPR growth of the sector frontier which is calculated as the average                TFPR growth rate of TOP 10 % firms of sector productivity distribution,          represents                the lagged TFPR distance of firm i from the frontier. Frontier is defined as average TFPR of top                10%  firms  in  each  sector.  As  in  OECD  [11]  the  coefficient  of  the  frontier  firm’s  growth  is                expected  to  be  positive,  reflecting  technological  pass-through  from  the  frontier,  and  the                coefficient of the distance from the frontier is expected to be negative, reflecting the fact that as a                firm gets closer to the frontier, the speed of catching-up slows down. Our main coefficient of                interest will be   which captures the effect of local geographic and public sector conditions on                firm  TFPR and  labour  productivity.     represents  dummy  variable  whether a  firm is small                (<50  employees),  medium  (>50  and  <250  employees)  or  large  (>250  employees).     and                represent county and sector fixed effects.   is a standard error term. To alleviate endogeneity                concerns between firms in top decile of productivity distribution and its mean, the regressions                are performed for firms in 1st to 9th decile of the distribution. By looking at the growth rates we                search for local factors that have positive or negative impact on firm performance evolution in                time. Given our results we will able to tell which conditions are more favourable in supporting                productivity growth and evaluate a dynamic nature of our estimations.                      We enhance the analysis also by estimating the impact of our regressors of interest on                productivity levels. In addition to dynamic analysis of TFPR growth rates we add static analysis                of levels to investigate the productivity and local conditions nexus in more detail. In order to do                so we run a cross section regression with rich set of fixed effects to control for various causes of                unobserved heterogeneity. The regressions are specified accordingly:                 where  represents either TFPR of a firm i or log of labour productivity.    will capture the                same  variables  as  in  the  equation  (2).  Vector  of  control  variables     includes  plausible                determinants of firm level productivity such as share of intangible assets in total assets, mark                ups,  human  capital  (share  of  blue-collar  workers  in  total  firm  employment)  and  a  dummy                indicating whether a firm participated in active labour market policy program. The last variable                is very interesting since it should be associated with better allocation and training of workforce                and thus positively related to firm productivity.     stands for ownership dummy. The reason                why we include ownership dummies is country specific. As shown in Výškrabka [17], foreign                ownership  indicator  can  explain  significant  part  of  productivity  differences  among  firms  in                Slovakia.  Muzikářová  [14]  shows  that  foreign  firms  are  on  average  30-50%  more  productive                than domestic ones and this relationship holds for controlling for additional firm characteristics                and sector fixed effects.  is a standard error term.                      Before we turn to the results we must return to localization and company headquarters                problem. As it was mentioned, from our data we cannot determine plant localization but only                company seat. Another specific feature of Slovak firm landscape is that significant fraction of                firms  (32  %)  set  their  seat  in  Bratislava  region  mainly  because  of  two  reasons.  First  is  that                Bratislava as  a capital  city  is  a  natural  economic hub  and  establishing company seat  there is                related  to  significant  economic  and  legal  benefits  (adequate  supply  of  business  services  and                infrastructure, proximity to major state offices, better business networks and so on). Also, many                large corporations (many of them MNCs) have plants distributed across the whole country but                their seat located in Bratislava. The second reason is more “practical” in a sense that the more                firms registered in Bratislava the lower probability of tax control. These two Slovak business                “features”  cause  disproportional  fraction  of  firms  have  their  seats  established  in  Bratislava                region. Therefore, by dropping all such firms we greatly reduce the bias that might come from                this type of matching error. Even if other firms have their seats localized in different cities, it                might still be the same county and thus there is a large probability that they will be matched                correctly with functional urban regions which are the main units of our analysis (all but one                                                              69","variable are calculated at this geographical level). Thus, overcoming the seat/plant issue by this                way  we  match  our  local  conditions  variables  to  firms  using  a  unique  municipality  identifier                common to both firms and variables in FUR database. By dropping Bratislava region and micro                firms as discussed earlier we end up with 50 thousand observations from which we are able to                match 91% to the FUR dataset.                  Functional urban regions                      We aggregated all Slovak communes into functional urban regions defined by Bezák [3] as                model  “FMR  01-A”.  Using  this  model,  the  number  of  observations  decreased  from  2927                communes to 50 FURs. We consider this approach to be the best choice in the context of larger                socio-economic  entities,  because  the  model  presented  by  Bezák  [3]  fits  by  its  definition  and                construction to functional urban areas (in Slovak conditions). They also are in accordance with                the recommendations of The Council of Europe (2016).                      In the next step, we aggregated the spending of local governments in COFOG classification                on the FUR level and then calculated the aggregated effectiveness of FUR’s governments.                      The effectiveness is measured by the formula:                                                                                                            (4)                        As factors, which could have an impact on the composition of public services we have used                4 following indicators.                                                                                                          (5)                                                                                                          (6)                                                                                                           (7)                                                                                                         (8)                       We  are  aware  that  the  cross-sectional  nature  of  our  data  might  not  capture  some                important  time-varying  features  of  the  relationship  between  firm  productivity  and  regional                characteristics.  Thus,  it would  be  desirable  to  construct longitudinal  (panel)  data in  order  to                capture the effect of time-varying factors in conjunction with richer set of fixed effects. This is of                course  an  objective  for  future  research.  Another  concern  may  arise  from  the  fact  that  by                dropping only firms with seat in Bratislava region, we do not completely mitigate the effect of                incorrect geographical matching of firms to the variables of interest. We believe that firms in                wholesale/retail,  utilities  or  HR  agencies  might  not  conduct  business  in  counties  where  they                have seats. Also, firms with more than 500 employees may have multiple establishments located                across the country. In future research we plan to correct for these issues.                      The results can be distorted by the spatial definition of FURs, which is based on Slovak                census 2001. Considering the dynamic economic development of Slovakia in the period from the                acquisition of data for the creation of our chosen model of FURs (based on daily commuters to                regional centres), there has probably been a shift in FURs‘ borders. Territory of FURs with larger                towns and cities and built-in infrastructure should gain. FURs located at their borders and those                lying outside major development axes could shrink.                                                                  70","3  Results and Discussion                       Turning now to results we document that municipality effectiveness, FUR fragmentation                and infrastructure coverage are correlated with our productivity measures. Looking firstly at                catching-up-to-frontier  regression  framework  (Table  1)  we  show  that  frontier  growth  pass-                through  and  distance  to  frontier  are  statistically  significant  and  have  desired  directions.                Switching to variables of interest we show that 10 percentage points increase in municipality                effectiveness leads to 0.3 % increase in TFPR growth rate (local government effectiveness has                unconditional  mean  of  81.5  %  and  standard  deviation  of  14.6  percentage  points).  Higher                effectiveness of local governments means that they can allocate more of their budgets to goods                and  services  of  a  developmental  nature.  More  effective  local  governments,  thanks  to                development spending, represent a better place to live what makes them more attractive for                workers and thus for business.                           Table 1: Catching-up-to-frontier framework, dependent variable id TFPR growth rate*                                            (1)         (2)         (3)         (4)         (5)                     VARIABLES              TFPR growth  TFPR growth  TFPR growth  TFPR growth  TFPR growth                      LocGov. effectiveness   0.0311***                                            (0.0120)                     TFPR frontier (delta)   0.951***   0.950***    0.950***    0.951***    0.950***                                            (0.0173)    (0.0181)    (0.0181)    (0.0181)    (0.0182)                     Frontier distance (-1)   -0.445***   -0.441***   -0.442***   -0.442***   -0.442***                                            (0.0118)    (0.0127)    (0.0127)    (0.0127)    (0.0127)                     Core concentration                 -0.00318                                                        (0.0139)                     Fragmentation                                  0.256*                                                                    (0.137)                     Index of dissim.                                           -0.0277                                                                                (0.0206)                     Infrastructure                                                         0.291***                                                                                            (0.108)                     Constant               -0.405***   -0.374***   -0.381***   -0.362***   -0.391***                                            (0.0175)    (0.0153)    (0.0147)    (0.0176)    (0.0157)                      Observations           45,400      41,389      41,389      41,389      41,389                     R-squared              0.292       0.290       0.290       0.290       0.290                     Sector FE              YES         YES         YES         YES         YES                     Size                   YES         YES         YES         YES         YES                                             Robust standard errors in parentheses                                                 *** p<0.01, ** p<0.05, * p<0.1                Source: Authors.                * Infrastructure and municipality effectiveness effects are robust under an alternative specification that uses the same                additional regulatory impact indicator as in OECD (2013). See Annex for results table.                       Higher concentration of population and businesses in one place creates a precondition for                healthy  competition  both  on  the  labour  market  and  on  the  product  market.  This  means  that                people in such places can pay higher amounts for goods and services produced in such places,                and  on  the  other  hand,  higher  competition  among  firms  forces  them  to  make  better  use  of                production factors.                      Also,  less  fragmented  and  higher  density  build-up  areas  (infrastructure)  are  more                conductive to boost productivity growth.                      Lower FUR fragmentation means that there are fewer administrative units in the territory                and  hence  fewer  borders  and  fewer  larger  markets  than  in  more  fragmented  FURs.  Less                administrative  units  mean  fewer  political  stakeholders  to  communicate  with  when  doing                business.  Although  the  general  conditions  for  doing  business  within  FURs  and  the  whole  of                Slovakia  are  the  same,  administrative  boundaries  cause  market  fragmentation.  This  makes  it                                                                 71","impossible  to  achieve  significant  economies  of  scale  and  puts  pressure  on  the  protectionist                behaviour of political leaders, especially of small administrative units.                      The greater part of the built-up area in the territory of the FUR indirectly refers to the                concentration of the population and therefore the qualitative change of the territory. Population                concentration  brings  both,  a  change  in  the  structure  of  demand  for  goods  and  services  and                creates space for production of new services. Along with this, there is a significant stratification                of  the  society  either  from  the  level  of  education  or  specialisation.  From  the  point  of  view  of                companies, the population's concentration means generally sufficient amount of workforce. Both                in  terms  of  education  or  specialization  (e.g.  hospitals,  universities,  science  and  research,                consultancy companies, advertising), and in terms of quantity (medium and large enterprises).                This  means  that  in  case  of  population  (labour)  concentration,  goods  and  services  can  be                produced  that  would  otherwise  not  be  produced  -  whether  highly  specialized  products  and                services (high added value), production with intensive use of production factors, in particular                labour and capital (economies of scale), or a combination of these.                      The core concentration is the FUR’s centre population share on all FUR inhabitants. We                assumed  that  the  productivity  of  production  factors  in  FURs  with  a  higher  population                concentration in the core will be, based on the arguments mentioned above, higher than in the                FURs,  where  the  population  is  more  dispersed.  However,  this  assumption  has  not  been                confirmed.  Similarly,  the  index  of  dissimilarity  was  statistical  not  significant.  This  indicator,                similar  to  the  core  concentration  indicator,  represented  the  FUR  settlement  structure.  The                assumed relation to the productivity of the production factors lies in the settlement structure of                the FUR. As in the previous case, the dissimilarity index was statistically not significant.                                             Table 2: Pooled specification and county FE                                                           (1)              (2)                             VARIABLES                     TFPR growth      TFPR growth                              TFPR frontier (delta)         0.951***         0.951***                                                           (0.0182)         (0.0175)                             Frontier distance (-1)        -0.442***        -0.447***                                                           (0.0127)         (0.0118)                             Infrastructure                0.283**                                                           (0.113)                             Index of dissim.              -0.00506                                                           (0.0356)                             Fragmentation                 0.243                                                           (0.160)                             Core concentration            -0.000947                                                           (0.0229)                             Municip. effectiveness        0.0222           0.0204                                                           (0.0166)         (0.0156)                             Constant                      -0.412***                                                           (0.0262)                              Observations                  41,376           45,400                             R-squared                     0.290            0.294                             Sector FE                     YES              YES                             Size                          YES              YES                             County FE                                      YES                                             Robust standard errors in parentheses                                                 *** p<0.01, ** p<0.05, * p<0.1                Source: Authors.                                                                72","This  means  that  the  internal  structure  of  the  FUR  (the  settlement  structure)  does  not                affect  the  productivity  of  factors.  But  other  factors  –  administrative  fragmentation  and                effectiveness of local governments as political-administrative factors and share of the built-up                area  as  a  proxy  for  concentration  of  population  and  related  infrastructure  are  statistically                significant.                      Controlling for county fixed effects and using pooled specification (Table 2) where we add                all  local  conditions  variables  (FUR  variables  +  municipality  effectiveness)  together  in  one                estimation  shows  that  share  of  the  build-up  area  (proxy  for  infrastructure  development)                remains positively correlated with TFPR growth rate.                      Moving to static productivity level estimations we show again (Table 3) that local public                sector  and  geographic  conditions  indeed  have  significant  effect  on  firm  productivity.                Municipalities  devoting  more  spending  to  development  activities  such  as  infrastructure                construction,  education  or  social  services  create  more  favourable  economic  environment  for                businesses.  In  econometric  words, 10  percentage point  increase in  municipality  effectiveness                leads to 0.75 % increase in firm TFPR. Also, FUR characteristics such as lower fragmentation and                high share of build-up area boost productivity as well. The arguments are same as above.                                                  Table 3: TFPR level regressions                                       (1)        (2)        (3)        (4)        (5)        (6)                   VARIABLES           TFPR       TFPR       TFPR       TFPR       TFPR       TFPR                    Municip. effectiveness   0.0754***                                         0.0921***                                       (0.00819)                                              (0.0113)                   Intangibles share   0.0661     0.109**    0.108**    0.109**    0.106**    0.0348                                       (0.0588)   (0.0479)   (0.0480)   (0.0480)   (0.0476)   (0.0778)                   Mark up             0.775***   0.774***   0.774***   0.774***   0.774***   0.803***                                       (0.00547)   (0.00568)   (0.00568)   (0.00568)   (0.00568)   (0.00719)                   Human capital       -0.0352***   -0.0334***   -0.0330***   -0.0329***   -0.0335***   -0.0471***                                       (0.00439)   (0.00466)   (0.00466)   (0.00466)   (0.00465)   (0.00539)                   ALMP                0.0600***   0.0576***   0.0580***   0.0575***   0.0615***   0.0638***                                       (0.00352)   (0.00362)   (0.00362)   (0.00361)   (0.00363)   (0.00360)                   Core concentration             -0.00572                                                  (0.00981)                   Fragmentation                             0.292***                                                             (0.0961)                   Index of dissim.                                     -0.0519***                                                                        (0.0144)                   Infrastructure                                                  0.799***                                                                                   (0.0736)                   Constant            2.413***   2.473***   2.466***   2.494***   2.415***                                       (0.0363)   (0.0369)   (0.0368)   (0.0360)   (0.0302)                    Observations        49,004     44,704     44,704     44,704     44,704     37,473                   R-squared           0.944      0.944      0.944      0.944      0.944      0.947                   Sector FE           YES        YES        YES        YES        YES        YES                   Size                YES        YES        YES        YES        YES        YES                   Ownership           YES        YES        YES        YES        YES        YES                   County FE                                                                  YES                   R2_a                                                                       0.753                                             Robust standard errors in parentheses                                                 *** p<0.01, ** p<0.05, * p<0.1                Source: Authors.                                                               73","Our results are consistent with those of Combes et al. [5] and Ahrend et al. [1]. Combes et                al. [5] say that companies are more productive in areas with more dense employment and at the                same time, they say there are benefits of big cities in increasing productivity growth in there                located firms in about half of the industries surveyed. The most productive firms experience also                the  strongest  productivity  gains.  Combes  et  al.  [5]  calculated  that  firms  in  more  densely                populated areas were on average 9.7% more productive than firms in less populated areas, with                productivity gain ranging from 4.8% for firms from the first quartile to 14.4% for firms from the                last quartile. Ahrend et al. [1] found that a 10% increase in city population yields a productivity                gain  of  0.2.  -  0.5%.  If  the  number  of  administrative  units  increases  by  10%  in  a  given                metropolitan region, it is associated with an approximate 0.6% lower productivity.                      Our  result,  the  0.75%  increase  in  firms'  productivity  observed  in  case,  that  the                effectiveness  increases  by  10%,  reflects  both  the  above-mentioned  results:  municipalities                effectiveness increases with their size - Combes et al. [5]; and the lower FUR fragmentation rate                contributes to productivity growth - Ahrend et al. [1].                  4  Conclusion                       Our results have shown that administrative fragmentation of FURs has negative impact on                productivity  of  firms.  Our  findings  state,  that  the  fragmented  structure  of  local  governments                does not affect only the citizens living there, but also firms in their broader neighbourhood. With                this,  the  debate  on  communal  reform  in  Slovakia  gets  new  arguments.  The  impact  of  cities                (concentration)  on  productivity  growth,  as  presented  in  the  literature  review,  has  also  been                confirmed.  Surprisingly,  it  was  found  that  the  FUR  internal  structure  (without  taking  the                geographical factors into account) and the size of the FUR centre had no significant impact on                productivity of firms.                      Further research can follow two directions. The first offers a greater scope for research in                the topic of firm productivity in individual FURs. More detailed information on firm productivity                could  be  helpful  in  the  FUR  specialization  and  tailored  place-based  policies.  Industry-specific                research could help identify declining industries and FURs which are threatened by their decline                and  at  the  same  time  identify  future  \"super-star\"  sectors  that  will  require  the  attention  of                decision makers. Attention should also be paid to a closer analysis of the productivity growth in                individual  FURs.  Which  FURs  grew  faster,  which  are  stagnating  or  declining?  Are  regional                differences increasing or decreasing?                      The second direction of the research focuses on a more detailed analysis of the spatial                relations of individual settlement elements and the finding of a pattern in their arrangement in                relation to the FUR’s centre and the communes in the surrounding area. This knowledge can                contribute to a better design of \"place-based\" policies.                  References                 [1.]  AHREND,  R.,  FARCHY,  E.,  KAPLANIS,  I.  AND  LEMBCKE,  A.  C.  2017.  What  Makes  Cities  More                     Productive?  Evidence  from  Five  OECD  Countries  on  the  Role  of  Urban  Governance.  Journal  of                     Regional Science, 57: p. 385-410. doi:10.1111/jors.12334                [2.]  ATKIN, D., KHANDELWAL, A., OSMAN, A. 2019. Measuring Productivity: Lessons from Tailored                     Surveys and Productivity Benchmarking. NBER Working Paper,No. 25471, Issued in January 2019,                     (DOI): 10.3386/w25471                [3.]  BEZÁK A. 2001. Funkčné mestské regióny na Slovensku v roku 2001. In Geographia Slovaca, vol. 15,                     pp. 1-30.                [4.]  BEZÁK, A. 2014. Funkčné mestské regióny na Slovensku v roku 2001. In: LAUKO, V. a kolektív.                     Regionálne dimenzie Slovenska. Bratislava (Univerzita Komenského), pp. 169-198. 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Estimating Production Functions Using Inputs to Control for                     Unobservables, The Review of Economic Studies, Volume 70, Issue 2, 1 April 2003, Pages 317–                     341, https://doi.org/10.1111/1467-937X.00246                [13.] MOLLISI, V., ROVIGATTI, G. (2017). Theory and Practice of TFP Estimation: The Control Function                     Approach Using Stata (February 11, 2017). CEIS Working Paper No. 399. Available at SSRN:                     https://ssrn.com/abstract=2916753 or http://dx.doi.org/10.2139/ssrn.2916753                [14.] OECD 2019, OECD Economic Surveys: Slovak Republic 2019, OECD Publishing, Paris,                     https://doi.org/10.1787/eco_surveys-svk-2019-en ISBN 978-92-64-31136-7                [15.] PETRIN, A., POI, B. P., LEVINSOHN, J. 2004. Production function estimation in Stata using inputs to                     control for unobservables. The Stata Journal (2004) 4, Number 2, pp. 113–123                [16.] THE CONGRESS OF LOCAL AND REGIONAL AUTHORITIES, COUNCIL OF EUROPE. 2016. Local and                     regional democracy in the Slovak Republic. Report from the monitoring visit.                [17.] VÝŠKRABKA, M. 2018. Lesk a bieda firiem na Slovensku. Analýza údajov firiem na individuálnej úrovni.                     Bratislava: Ministerstvo financií SR, Inštitút finančnej politiky, 2019 reachable at                     https://www.finance.gov.sk/files/archiv/85/Firmy_komentar.pdf                                                                                                 75","Value Preferences of Employees Working in the Non-profit                                                         Sector                                                              a                                     GLASEROVÁ Martina , KOBLÍŽKOVÁ Klára            b                                   Faculty of Management, University of Economics, Prague, Czech Republic                                                 a           b                                                  falm02@vse.cz,  xkobk01@vse.cz                Abstract                 The success and effectiveness of non-profit organizations cannot simply be expressed through traditional                indicators  based  primarily  on  profit,  because  their  evaluation  is  not  primarily  based  on  the  amount  of                generated  profit. Missions of non-profit organizations  are completed and developed through their staff                and  the  values  they  share.  The  aim  of  this  study  was  to  map  the  value  preferences  of  employees  of  a                selected  non-profit  organization,  to  identify  both  their  motivation  for  work  in  the  non-profit  sector  in                terms of the composition of their value ladder and to what extent they identify with the organization. The                degree  of  identification  with  the  organization  can  be  one  of  the  key  means  to  positively  influence  the                effectiveness and success of the organization. The data was obtained from a questionnaire survey based                on the Schwartz's Portrait  Value Questionnaire extended  by a graphical scale and additional questions                mapping the degree of identification with the organization. The data were further corrected by converting                them into comparable values and statistically analyzed based on the calculation of mean values and the                Pearson  correlation  coefficient.  Determination  of  the  employees'  value  setting  and  their  degree  of                identification with the organization could become a tool to detect another factor that may cause conflicts                in the organization and have a negative impact on its functioning and consequently its success.                 Keywords: non-profit organizations; organizational identification; value orientation; Schwartz Value Survey; HR management                JEL Classification: L31                    1  Introduction                       The non-profit sector is an integral part of the economy not only in the Czech Republic but                also elsewhere in the world. It can be understood as an institutional response to the failures of                the state and the market which, in an economic sense, brings about the increase of social wealth                and involves the redistribution of financial resources and mobilization of human resources [7].                At  the  same  time, certain  non-profit-making  tasks  are  entrusted  to  the  non-profit sector,  e.g.                social welfare and humanitarian and development assistance. The type, size and focus of non-                profit  organizations  are  very  diverse.  They  should,  however,  meet  five  basic  characteristics:                organized  structure,  institutional  separation  from  public  administration,  non-distribution  of                profit, self-management and volunteering [21].                      There are many ways to measure the success of an organization in the for-profit sector.                For the non-profit sector, however, traditional indicators based primarily on profit cannot be                used.  The  main  purpose  of  non-profit  organizations  is  other  than  maximizing  profits  and                meeting a profit-oriented business plan. The success of non-profit organizations must, therefore,                be expressed in a different way and it is a question what, in their case, should be considered as                relevant indicators of success. If, however, at least partial meeting of their strategic goals and                completion of their mission can be deemed an achievement of a non-profit organization, then                human resources, both employees and unpaid workers (volunteers and members), are one of                the key elements to achieve them [23].                      Human  resources  indicators  are  an  important  part  of  the  assessment,  even  within  a                broader concept of success of non-profit organizations where the narrow concept of success of a                non-profit organization (achievement of objectives and fulfillment of the mission) is extended by                performance, efficiency, competitiveness, etc. Such indicators include, for example, qualification                                                                 76","and initiative of workers [19], employee turnover [12] or indicators evaluating job satisfaction                of paid and unpaid workers [25].                      The aim of the study was to map the value preferences of employees working in the non-                profit sector, to identify both their motivation for work in a non-profit organization in terms of                the composition of their value ladder and to what extent they identify with the organization. And                it  is  the  degree  of  identification  with  the  organization  that,  in  our  opinion,  is  one  of  the  key                means that may positively influence the effectiveness and success rate of the organization.                      Identification  with  an  organization  can  be  understood  as  a  deep  acceptance  of  the                organizational identity [1]. It is an unstable, time-varying construct [27], [17], [11]; members                interpret  the  current  orientation  of  the  organizational  identity  through  understanding  the                organization’s  activities  and  the  feedback  from  its  surroundings  [4].  For  many,  the                organizational identity can have an even greater significance than the identity based on gender,                age or nationality [14], because it can fulfill their desire to accentuate their own excellence. This                can  be  done  by  identifying  with  the  organization  that,  as  compared  to  others,  the  individual                considers to be non-fungible [10]. If this happens, the individual experiences a sense of work                satisfaction, engagement and loyalty to the organization, etc. [16]. This intrinsic unity between                the individual and the organization is really essential. If the individual accepts the organizational                identity as their own, then they act in the interest of the organization with the best of intentions                [1], which is related to their internal work motivation, level of collaboration in the workplace,                job satisfaction, their performance etc. [10].                      Identification  with  the organization can  also  be understood  as  getting  identified  with a                group of people who pursue a common goal, and individuals perceive themselves as \"we\" within                this group. Through the process of depersonalization, they emphasize the similarity they share                with other members of the organization and pay special attention to what they have in common                [6].  At  the  same  time,  however,  the  individual  creates  their  own  understanding  of  the                organization based on their own experience and makes up their own view of it that may not be                in  line  with  how  the  organization  presents  itself  in  terms  of  its  identity  [13].  It  can  also  be                understood as the degree of alignment between how the individual perceives the organization in                terms of identity and what they expect [9].                      Various aspects of looking at the motives that lead to identification with the organization                can  be  found  in  reference  literature  (based  on  the  theory  of  social  identity  and  the  related                processes of self-categorization distinguishing individual, relational, and collective identities [6],                [10], or from the viewpoint of social and social-emotional reasons [1]), but the aim of this study                is  to measure  the  level  of  identification  with  the organization  in  the  context  of  its members'                value ladder. According to Salancik and Pfeffer, the individual is satisfied at work and motivated                to work if their job's characteristics are compatible with their needs [22], and we believe that                this is also partially based on their value ladder. A practical solution of this is built on Schwartz's                theory of values.                      Values are relatively stable over time and influence the attitudes, judgments and behavior                of  all  people  in  general  [15]  and,  in  our  opinion,  values  help  to  shape  up  the  organization's                internal operations, internal relationships and the so-called indoor climate of the organization,                its image and successful branding of the organization. Although values serve as a mediator in the                interaction of an individual with their social environment [5], the individual becomes aware of                them  only  when  the  received  perspective comes into  conflict  with  the  values  they  recognize.                Values as guiding principles in the lives of individuals form the basis of human attitudes, that is,                the  manner  in  which  the  individual  evaluates  experienced  events.  The  individual  assesses                positively what is in line with the fulfilment of their goals and negatively what threatens them or                prevents them from achieving them [20].                      Values in an organization express the group's demands on how to achieve them, and the                assumptions that may cause conflicts in the organization can include incompatibility of the value                systems  of  individuals  and  organizations  [26].  Although  the  complex  topic  of  organizational                identification cannot be reduced to a single aspect, it is the viewpoint of values and goals shared                by the individual and the organization that is also considered as a means of ensuring coherence                throughout the organization [18].                                                               77","Another aim was to verify the accuracy of the universally accepted assumption that people                working in non-profit organizations do not tend to build a staggering career which is related to                Boer  and  Fischer's  statement  that  the  economic  factor  does  not  influence  value-based  social                attitudes [3], and this partly results also from the fact that there are not enough positions in the                environment of non-profit organizations to satisfy their potential desire for career growth, and                partly from the fact that the financial remuneration is not adequate to the required amount of                work and the responsibilities inherent in the position [24].                  2  Material and Methods                       The data needed to evaluate the issues raised above were obtained from a questionnaire                survey based on the Schwartz’s Portrait Value Questionnaire and the Schwartz’s Value Survey                [20]. The questionnaire investigated the value orientation of executives and ordinary employees                of a selected non-profit organization operating in the area of humanitarian aid and social care.                      The obtained data were corrected through a conversion into comparable values according                to the Schwartz’s recommendation by subtracting the average value calculated through all the                respondents' answers from the answer to each question and further analyzed by calculation of                the mean values (mean) and the Pearson correlation coefficient. The perceived content of the                organizational  identity  and  the  degree  of  similarity  between  the  values  of  members  of  the                organization and the declared value system of the organization were evaluated.                                                 Table 1: Demographic variables                                Total                                105           100%                                Men                                   6            5.71%                                Women                                 99          94.29%                                Employees                             40          38.10%                                employees/ members                    61          58.10%                                Others                                4            3.81%                                ordinary employees                    54          51.43%                                Managers                              48          45.71%                                Others                                3            2.86%                                less than 1 year in the org.          13          12.38%                                1-3 years                             18          17.14%                                more than 3 years                     74          70.48%                                administrative workers                54          51.43%                                health and social workers             45          42.86%                                Others                                6            5.71%                                up to 30 years                        7            6.67%                                31-50 years                           65          61.90%                                51 years and older                    33          31.43%                                primary education                     2            1.90%                                high school education                 76          72.38%                                university education                  27          25.72%                 Source: Authors.                       The questionnaire was sent to respondents via the organization’s internal email system at                the  end  of  2018.  A  total  of  579  employees  were  contacted.  They  were  executive  and                administrative staff members of the organization’s headquarters, managers and administrative                staff of the regional branches of the organization, and staff in services provided by the regional                branches  of  the organization. The research sample  was established  by  negative self-selection                (part  of  the  addressed  employees  did  not  participate  in  the  research  and  did  not  fill  in  the                                                               78","questionnaire), the questionnaire was filled in and sent back by 106 respondents, so the survey                was carried out with 18.3% return rate. One of the submitted questionnaires was excluded from                the  analysis  because  the  respondent  did  not  meet  the  basic  condition  of  the  employment                relationship.  Table 1  shows  statistics  broken  down  by  demographic  variables  (gender,                membership  in  the  organization  beyond  the  employment  relationship,  job  position,  length  of                work in the organization, job classification, age and education).                      Respondents answered each question in the questionnaire by judging the values with 2                items on a six-point scale (1 – it is absolutely not me, 2 – it is very unlike me, 3 – it is rather                unlike me, 4 – it is rather like me, 5 – it is very much like me, 6 – it is definitely me, and for                questions  about  organizational  values  1  –  it  is  absolutely  not  my  organization,  2  –  it  is  very                unlike  my  organization,  3  –  it  is  rather  unlike  my  organization,  4  –  it  is  rather  like  my                organization, 5 – it is very much like my organization, 6 – it is definitely my organization). In                addition, an adapted graphical scale of identification was used according to Bergami and Bagozzi                [2], to which numerical values (0 - zero identification to 5 - complete identification) were also                assigned for further statistical processing, and additional questions according to Fombelle et al.                [8] that could also be answered on a six-point scale (1 - absolutely disagree, 2 - very disagree, 3 -                rather disagree, 4 - rather agree, 5 - very agree, 6 - totally agree).                  3  Results and Discussion                       First, a correlation analysis was made between the mean values of the organization and its                employees  shown  in  Figure  1.  The  correlation  coefficient  was  0.63,  there  is  a  certain                concordance between the values of the individual and the organization.                      In  the  selected  non-profit  organization  operating  in  the  field  of  humanitarian  aid  and                social  care,  the  highest importance is  given  to  the  values  of  Benevolence (1.22)  and Security                (1.08) by its employees. It is, therefore, perceived primarily as an organization that transcends                itself and the need for smooth functioning of the group / society, the need to be a part of a larger                entity, and the need for helpfulness and for increase of well-being are its determining needs. But                also  the  need  for  a  certain  position  in  the  social  rankings,  a  sense  of  security,  harmony  and                stability in the society and in the organization itself.                      The  value  of  Self-Direction  (0.19),  which  is  characterized  by  the  need  for  creativity,                independence, curiosity and freedom, ranks last. The value of Stimulation (0.30), i.e. the need for                extraordinary  stimuli,  challenges  and  excitement  ranks  penultimate.  Both  values  are                antagonistic  to  the  near-leading  value  of  Security  according  to  the  Schwartz’s  motivational                continuum.                                   Figure 1: Correlation of individual values and organization’s values                                 Source: Authors.                                                                      79","Figure 2: Organization’s values and individual values                                 Source: Authors.                      In  terms  of  demographic  variables,  perceptions  of  organization’s  values  are  not                fundamentally altered, not even in the case of comparison of ordinary employees and managers                who are often the faces of the organization in the non-profit sector. The only exception can be                found  in  the  category  of  men,  the  category  of  respondents  under  the  age  of  30  and  the                respondents with basic education who perceive the values of Self-Direction and Stimulation as                significantly  more  restrained  than  others  in  the  organization.  Interestingly,  men  perceive                Tradition (0.87) characterized by humility and sensitivity to the expectation of the environment                as the most important value in the organization, followed by the value of Universalism (0.78)                that could be simply characterized as an effort to understand and protect the well-being of all                people, and it is not until after these values that the values of Benevolence and Security (0.70)                follow. In the category distinguishing between the employees/members of the organization and                mere  employees,  there  is  a  different  perception  of  Self-Direction  which  is  suppressed  for                employees, while employees/members have an obviously stronger feeling of doing what they                chose.                      As  far  as  individual  values  are  concerned,  employees  in  the  selected  non-profit                organization  consider  on  average  Security  (1.36)  to  be  the  most  important  value,  closely                followed by the value of Benevolence (1.34) and Universalism (1.30). The value of Power (0.40),                i.e. the desire to achieve certain social status and prestige and the need to demonstrate authority                and wealth, was the last. The assumption that people working in non-profit organizations are                not wired to build a breakthrough career has, therefore, been confirmed on a given sample. The                organization's and its employees' value settings are shown in Figure 2.                      Based on the results, respondents were further divided according to the declared level of                identification with the organization into three basic groups - below-average identified, average                identified and above-average identified respondents. The least represented category (1.90%) of                below-average respondents reached the correlation with organizational values of 0.32, the value                setting of these employees rather does not match the organizational values.                           Figure 3: Correlation of the average identified respondents with organization’s values                                 Source: Authors.                                                               80","The category of average identified respondents (34.0%) reached the correlation rate with                the organizational values of 0.71, in which case it can be stated that the value setting of these                employees coincides with the values of the organization to a large extent (see Figure 3). A typical                representative of the category of the average identified respondents is a woman aged 31 to 50                who has been a regular employee (not a member) of the organization for more than three years,                works  as  a  health  care  or  social  worker,  has  high  school  education  related  to  the  work  she                carries out in the organization and has not considered leaving the organization yet.                      The most represented category of above-average identified respondents (69.0%), which,                unlike the average identified, mainly includes those employees who work in the administration                and are also members of the organization, reached a correlation with the organizational values                of 0.59, i.e. rather weaker consonance. This has already been indicated to us by the fact related                to  the  perception  of  the  organization's  value  setting  -  there  is  a  different  perception  of  Self-                Direction among employees/members within the given sample. In their case, the Self-Direction                is perceived as more significant than on the overall average, which points to the fact that these                individuals chose to work in the organization deliberately and by doing this work they have a                certain sense of autonomy and freedom.                      Why the highest consonance has been achieved in the category of the average identified                respondents should be subjected to deeper analysis which, in our opinion, will depend on other                factors that have not been the focus of this research.                      Another question we dealt with in the research was what values that are determining for                the operations of the organization and reflect in its publicly declared mission are assigned by                both managers and ordinary employees to each of the principles. The values of Benevolence and                Universalism, which hide the desire for understanding, protection of the welfare of people and                nature,  social  justice  and  benevolence  placed  first  and  second.  Coming  in  last  places  are  the                values of Power and Achievement that represent the desire of social power, dominance over                people  and  resources  and  achieving  success  as  an  expression  of  personal  ambitions.  These                findings are also in line with the perception of the value setting of the selected organization as                well as the individual value setting of its members.                   4  Conclusion                       The aim of this study was to map the value preferences of employees of a selected non-                profit organization operating in the Czech Republic, their perception of the value setting of the                organization and the degree of their identification with it. Having applied correlation analysis,                we found that there is a congruency between the average values of the organization and the                value setting of its employees; the employees are more or less in the line with the organization                that is perceived by them as an organization for which helpfulness and increasing of well-being                are  important.  Partial  misalignments  in  perceiving  the  organization's  value  setting  occur  in                further subdivided categories of respondents, which can be used by the organization for further                targeted  work  with  its  human  resources.  Not  only  can  the  organization  at  least  partially                understand  the  motives  of  their  employees'  behavior,  but  it  can  also  influence  the  potential                impact of their continuance in the organization.                      In our study, we found a striking congruency with the organization’s values in the category                of average identified respondents. In our opinion, this phenomenon is not clearly related to the                fact that these respondents would project their own value ladder into their perception of the                organization, or that they would simply assimilate in the organization's environment, because                there  was  no  such  significant  congruency  in  the  category  of  above-average  identified                respondents. It can be assumed that this is a more complex problem affected by many other                factors  that  should  become  the  subject  of  further  research,  which  could  provide  answers  to                questions  about  the  extent  to  which  the  degree  of  identification  plays  its  role  in  relation  to                various  components  of  an  individual's  identity,  and  what  role  this  fact  plays  within  the                organization.                                                                 81","Identifying  employees'  value  orientation  and  their  degree  of  identification  with  the                organization could, in our opinion, become a tool to reveal one of the factors that may cause                conflicts  in  the  organization  and,  thus,  have  a  negative  impact  on  its  functioning  and                consequently its success.                      Apparently, this aspect could make it possible to improve the process of recruitment and                selection of employees so as they resonate better with the declared and internally understood                values of the organization and are able to understand better the contents of these important                values. If the organization's priority values are fundamentally inconsistent with the motivation                of its employees, it can hardly be assumed that this will have a positive effect on the achievement                of the organization’s strategic goals, completion of its mission, efficiency and, thus, the overall                success of the organization.                  References                 [1.]  ASHFORTH, B. E. 2016. Distinguished Scholar Invited Essay: Exploring Identity and Identification in                     Organizations:  Time  for  Some  Course  Corrections.  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Journal of Management Inquiry [online]; 15(3): 219–234.                                                                                                             83","Public Sector Financial Support for SME Innovativeness:                                   Case Study of Selected CEE countries                                                                             b                                                                                               c                                              a                           GYAMFI Solomon ; ANDERSON Henry Junior ; STEJSKAL Jan                                       Faculty of Economics, University of Pardubice, Czech Republic                                  a                   b                  c                                   solomon.gyamfi@upce.cz,  henry.anderson@upce.cz,  jan.stejskal@upce.cz                Abstract                 The  impact  of  innovation  on  economic  development  cannot  be  underestimated.  Innovation  has  been                touted as the anchor  on which firms can  nick a competitive advantage for themselves.  Over  the years,                public  sector  interest  in  innovation  has  been  emphasized  due  to  the  impact  innovation  has  made  on                economic development of some nations. Different public sector support systems are available to firms to                access for their innovative activities. Small and Medium Scale Enterprises (SME’s) play vital role in the                economies  of  most  countries.  Despite  their  contribution  to  development,  they  are  constrained  by                inadequate  funds  to  engage  in  R\&D  for  innovation.  In  the  light  of  this,  the  research  sought  to  find  out                whether the innovativeness of SME’s from Selected CEE Countries determines the public financial support                from  the  government  or  the  European  Union.  The  logistic  regression  model  was  employed  using  the                harmonized European Union Community Innovation Survey 2012-2014 data for the empirical analysis.                Our results indicate that SME’s that are engaged in innovative activities attract public financial support                from national government and/or the European Union. This is because, the public sector financial support                from the government and the EU target firms that are already engaged in innovation or show potential to                be innovative.                 Key Words: Firm Innovativeness, Public sector financial support, Small and Medium-Size Enterprise                JEF Classification: H30, H41, H50                ______________________________________________________________________________                  1  Introduction                       Recently,  innovation  has  had  enormous  impact  on  economic  development  of  many                countries both developed and developing [19], [3]. More so, due to resource scarcity and the                aftermath  of  the  financial  Crises  saw  the  European  Commission  in  2010  emphasizing  in  its                communication  to  the  member  states  the  need  to  spend  efficiently  resources  on  innovation                activities. However, businesses cannot propel growth alone due to the inadequacy of resources                and market imperfections [11], [4] and lack of capital [14]. This is because, both big and small                firms need support from external resources to bolster their internal resource geared towards                innovative activities firm whose spillover effect in the long run impact positively on the growth                and development of the public economy, but they are financially constrained. Different support                systems are available to firms to source for their innovative activities especially from the public                sector. [10] have suggested avenues through which the public sector supports firms’ innovative                activities. They include; cooperation arrangements between firms, and other bodies, Loan from                the public banks, tax incentives and direct government funding through policies and projects of                the  government  aimed  at  stimulating  innovation.  Such  subsidies  given  to  firms  have  both                positive  and  negative ramifications,  i.e.  they  may  complement  private financial  investment in                firms’ R\&D or block such avenues (crowding out effect). Small and Medium Scale Enterprises                play vital role in the economies of most CEE countries. Small firms are necessity for employment                creation  [2],  [16],  [15],  [7].  Bela  et  al  opine  that  SMEs  play  important  role  in  the  Czech  and                Slovak republic [2].                      Their activities ensure economic growth due to the fact that they promote competition by                their radical introduction of new products to the market [18]. Therefore, public sector support is                invariably  important  if  SME’s  are  to  be  able  to  engage  in  innovative  activities  as  a  tool  of                innovation policy. Essential amount of literature has dealt with the impact of public funding on                                                               84","the  firm  innovative  activities  [25],  [8],  [1]  and  many  others  have  also  concentrated  on  the                analysis  of  the  effects  of  public  policy  on  R\&D  activities  of  the  firm.  Most  developing  and                developed states support SME’s innovative activities through subsidies for firms’ R\&D against                the backdrop that they are sources of innovation. In the same light, the EU has conceived SME’s                to be the backbone of the EU economy [18]                      Hesmati \& Loof advance an interesting point about how the public sector support firms in                their innovative activities [10]. They concur with the assertion of [13] that many of the literature                on  public  financial  support  assume all  firms  have  the  possibility  to  receive  support from  the                public support programs. Rather, most of these firms attract and receive financial support due to                their activeness in innovative activities or owing to their track record and viability of a novel                innovative product and or service. In this case, small firms are less privileged than the big firms                to  access  funds  from  the  public  sector.  Likewise,  highly  innovative  small  and  medium-scale                enterprises  are  considered  to  the  less  or  non-innovative  ones.  Again,  some  literature  on                innovation  support  by  the  public  sector  has  concluded  that  effective  public  sector  financial                support helps to induce or stimulate innovation activities among firms. However, this research                seeks to show that in most cases, public sector support for innovation is competitive and project                base [5]. Thus, the most innovative and viable innovative activities of a firm would be supported.                It will also outline the kind of financial support firms attract in the selected countries.                      The next section delineates a brief review of literature to illuminate the gap in the support                of innovation by the public sector. Section three provides the method employed for the empirical                analysis  and  data  used. The findings  of  the  research  are  discussed  in section  four  and  lastly,                conclusions and recommendations highlighted.                 1.1 Theoretical Background                      The underlying reasons for public sector financial support for firms’ innovative activities                is attributable to market failure which stems from underinvestment in innovative activities and                financial  constraints.  Also,  the  reason  that  the  public  sector  must  ensure  improvement  in                technology  [6]  for  product  and  service  to  the  general  public  also  stimulates  public  financial                support. Westmore finds in his investigation of the influence of the public policies on private                sector innovation of selected OECD countries that social rate of return on innovative support                exceeds  the  private  rate  of  return  [25].  Therefore,  governments’  intervention  in  innovative                activities is paramount for the realization of social benefits on outcomes of innovation. However,                Chudnovsky  et  al  opine  that  subsidies  from  public  sector  are  given  to  government  selected                projects with high social rate of returns [5]. Subsidies and financial support in general provide                firms with the ability to grow therefore as many literatures have argued small and medium-size                firms have to be supported for two reasons. First, due to financial constraints, survival of many                SME’s  becomes  less  because  firms  are  unable  to  internally  generate  funds.  Secondly,  SMEs                possess  the  potential  to  lead  in  the  economic  growth  of  nations  because  they  account  for                employment, innovation and capital stock.                      Moreover, the historical antecedent of the perspective of the then communist regime in                the selected CEE countries must be emphasized. Unlike the communism era where new ideas                and research were unidirectional i.e. R\&D was the task for a group of research institutes who                inter alia controlled the various innovative activities of the firm including intellectual property                right  and  patents,  the  contemporary  neoliberal  economic  systems  of  the  CEE  countries  as  a                result of their EU accession has shifted from the lack of in-house research activities among firms                [12] to encompass an innovative ecosystem of many stakeholders and enormous research and                collaborative agreements due to effective and efficient innovative policies.                      The post-accession to EU has in no doubt strengthened the firm level R\&D activities ably                supported by both national (government) funds and EU funding through the structural funds as                well as other special funds. The EU does not only support firm innovative activities but affect                innovation policies in the region as well. Kattel et al has described the integration process CEE                economies have been through [12]. The economic restructuring and integration into the global                economy meant that the CEE countries took the peripheral approach or rather were dipped into                the EU economy at the time. That means most big companies at the communist time without                                                              85","R\&D units had either have to up their game or merge with the then Multi-National Companies                who had established their outsourced companies here in the CEE region. Current trends which                started a decade ago has seen more innovation activities at different levels in the CEE region.                SME innovative activities are prevalent leading to the major economic growth in some countries                in the region.                      As a matter of fact, Steyerberg et al concur that government subsidies and research grants                are provided for firms through application process [23]. Moreover, it is the public sector agency                that  selects  such  programs  to  be  funded.  Enormous  research  has  been  done  in  this  field                especially  assessing  the  impact  of  public  sector  subsidies  and  financial  support  and  firm                performance. But there exist quite a number of methodological issues as Hyytinen \& Toivanen                re-echoed  in  their  analysis  of  SMEs  in  Finland  [11].  Amongst  them  is  the  issue  of  reverse                causality and selectivity bias with government funding of innovation at the firm-level [10] on                one hand and the nature of data set [8]. They emphasize the endogeneity of firms’ innovative                activities and funds SME’s receive from the government. Klette et al also argue that, researchers                in  most  studies  ignore  the  fact  that  government  deliberately  select  firms  to  receive  R\&D                subsidies and this mostly leads to significant bias in the econometric estimates and conclusion                [13]. Recent papers have however tried to account for this bias by putting certain dummies such                as industry and location dummies to control for this bias. However, one possibility to eliminate                this  bias  is  by  making  the  public  financial  support  or  subsidy  dependent  on  the  innovative                activities of the firm and their outcomes while accounting for the propose dummies. The current                research  employs  this  methodology  to  show  that  firms  innovative  activities  determines  the                public sector financial support for SME’s in selected CEE countries.                      Firm  level  innovation  can  be  measured  both  in  terms  of  the  input  and  outcomes  of                innovative activities such as intellectual property rights and so on. However, knowledge capital                assets have been used recently. As we will show in the subsequent sections, outcomes of the firm                innovation are as a result of firm activities such as firms internal and external R\&D, purchase of                external knowledge and so on and is mostly used as means to attracting financial support from                the public sector. In the light of this assumption, we propose two hypotheses as follows;                      H1. SME’s that are engaged in innovative activities attract public financial support                      H2. Innovative SME’s attract financial support from the EU and or National government.                      The purpose of this paper is to analyze whether the innovativeness of SME’s determine the                public sector financial support innovative SME’s attract in some selected Central and Eastern                European Countries.                   2  Methodology and Data Source                       The  Data  for  the  empirical  analysis  was  sourced  from  the  European  Union  Community                Innovation Survey (CIS) conducted for three years from the period 2012-2014. The CIS data has                enormous reference across various fields of innovation hence it widely usage by many authors                [21], [17], [22] across the innovation field. The CIS gather data on innovation and innovation                activities of firms in the EU using a harmonized survey questionnaire. The data from the CIS                provides  dichotomous  variables  which  makes  analysis  of  the  data  possible  by  using  binary                logistic regression [21], [24]. Logistic regression is employed for the empirical analysis because                it  is  able  to  predict  the  probability  of  an  innovative  SME  attracting  public  financial  support.                Additionally, since the dependent variable (Public Financial Support-PFS) is a binary variable or                dichotomous  in  nature,  it  fits  the  model  used  by  predicting  the  relationship  between  the                dependent and the independent variables. The strength in using the logistic regression model                stems from the fact that it is able to provide salient information and make inherent relationship                predictions  that  other  binomial  models  fail  to  account  for.  The  general  formula  for  logistic                regression model is given in the form:                  PFS = β 0  + β 1  (Intramural R\&D)x + β2 (Extramural R\&D)x + β3 (Machine Acquisition)x + β4 (External   (1)               knowledge acquisition)x + β5 (Training for innovative activities)x + β6 (Innovation introduction)x + β7 (Patent                            application)x + β8 (Industrial design right)x + β9 (License/Sell patent)x + εx                                                              86","The formula shows that the propensity for SMEs to attract public financial support from                Government and EU is dependent on the innovative activities and innovation outcomes of the                firm. The dependent variables denoted by PFS represent FUNGMT/FUNEU and εx denotes the                residual error margin, β0 is the intercept and β1- β9 denotes the independent variables. We then                run the analysis for both dependent variables and the results are presented by tables 1 and 2                below.                                         Figure 1: shows the analytical concept for the model                                    Firms  Internal                                  and  External                                   Research                                   Activities                                 Machine and                                  Knowledge                                        Government                                  Acquisition            H1   Public               H2  Funding                                                              Financial                                 Training  and                Support               EU Funding                                 Introduction  of                                  Innovation                                  Intellectual                                 Property  Right                                 and  Licensing                 Source: Authors’.                      Some  CEE  countries  (Bulgaria,  the  Czech  Republic,  Estonia,  Croatia,  Hungary,  Latvia,                Lithuania,  Romania  and  Slovakia)  were  selected  for  the  analysis.  These  CEE  countries  were                selected  because  majority  of  them  if  not  all  rely  on  SMEs  as  their  backbone  for  economic                development.  Most  of  these  SMEs  are  highly  innovative  and  as  such  have  the  propensity  to                expand internationally and ensure competitiveness. Due to this, government and EU (through                structural funds) support various activities of these firms to continue in their strides. One key                support by these public sectors is financial support. Hence, we seek to analyze which financial                support the SME’s attract. In the light of this, we propose the conceptual framework as shown in                figure 1. The framework illustrates that firm’s innovative activities determine public financial                support (H1) and such innovative firms may attract these funds from the public sector or EU                funds H2.                   3  Results and Discussion                       The empirical results on whether the innovativeness of SME’s determine the public sector                financial  support  firms  attract  in  some  selected  Central  and  Eastern  European  countries  are                presented in the tables 1 and 2. The research considered all SME’s that responded to the CIS                2012-2014  innovative  questionnaire  based  on  the  CIS  NACE  category  regardless  of  their                enterprise group to be able to determine whether innovative SME’s funding support come from                the EU or the National government.                      The effect of government funding of firm’s innovativeness has often been said to contain                selective  bias  and  reverse  causality  problem  [11].  Most  researchers  have  argued  that  firm’s                innovation activities may be endogenous of government funding, i.e. government funds are likely                to be given to firms that engage more in research and development for innovation.                      From the analysis, we observe that government funding supports innovative SME’s in the                CEE  countries  in  the  firm’s  internal  research  and  development  and  Machine  acquisition.                However, this was not so for firm’s external research and development with the exception of                Romania  and  the  Slovak  Republic  which  proved  to  have  no  effect  on  attracting  government                funding. The results complement [9] findings that small and start-up firms have high capital cost.                Firm’s capital cost involves the purchase of fixed assets such as equipment or machinery which                are  fundamental  for  both  product  and  process  innovation.  Since  government  sees  innovative                firms as a source of new ideas and growth, most innovative SME’s have the propensity to attract                government financial support.                                                               87","Regarding  external  knowledge  acquisition,  innovative  SME’s  in  Hungary,  Estonia,  the                Czech  Republic,  Croatia  and  Latvia  attracted  government  funding.  Only  SME’s  in  Estonia                attracted  government  funds  for  introducing  innovation.  This  evidence  can  be  linked  to                government policy aimed at supporting innovative capacity building in SME’s for engaging in                further innovation activities such as the EU Horizon 2020. Also, innovative SME’s that applied                for patent received funding support from the government except Croatia, Hungary, Lithunia and                Slovakia. It has also been shown that only SME’s in Bulgaria with industrial design right received                support  from  the  government.  And  lastly,  Hungary  and  the  Czech  Republic  SME’s  attracted                government financial support for licensing or sale of patent.                                     Table 1: Government Funding for Firms Innovative Activities                            Bulgaria   Czechia   Estonia   Croatia   Hungary   Lithuania   Latvia   Romania   Slovakia                 Firm Innovative Activities                 Intramural   2.127   2.985   1.583    1.699    1.672   1.773    2.364    4.679    3.443                 R\&D        (0.001)   (0.001)   (0.019)   (0.030)   (0.001)   (0.001)   (0.052) *   (0.001)   (0.001)                            ***      ***      **       **       ***     ***               ***      ***                 Extramural   -0.779   -0.813   -0.182   -1.015   -0.397   -0.463   -0.428   0.090   -0.442                 R\&D        (0.013)   (0.001)   (0.603)   (0.017)   (0.066) *   (0.125)   (0.495)   (0.877)   (0.329)                            **       ***               **                 Machine    3.161    1.579    1.458    4.869    3.281   2.325    1.748    1.651    2.264                 Acquisition   (0.001)   (0.001)*  (0.001)*  (0.001)*  (0.001)*  (0.001)   (0.008)   (0.001)   (0.001)                            ***      **       **       **       **      ***      ***      ***      ***                 Ext. Know   -0.041   -0.321   0.795   -0.639   0.707   0.134    -1.551   -0.174   -0.253                 Acq.       (0.835)   (0.097) *   (0.019)   (0.065) *   (0.001)*  (0.640)   (0.096) *   (0.673)   (0.664)                                              **                **                 Training    0.253   0.011    0.804    0.092    0.210   -0.038   0.762    0.569    0.256                            (0.116)   (0.944)   (0.017)**   (0.765)   (0.222)   (0.881)   (0.209)   (0.419)   (0.635)                  Innovation   0.098   0.088   -0.313   0.832    0.216   0.061    -0.220   1.284    -0.565                 Intro.     (0.579)   (0.566)   (0.345)   (0.007)*  (0.236)   (0.822)   (0.729)   (0.107)   (0.336)                                                       **                 Intellectual Property Right                 Patent     0.682    2.031    2.109    0.390    0.354   0.166    1.803    1.932    0.843                 Applicat.   (0.002)*  (0.001)*  (0.001)*  (0.524)   (0.254)   (0.698)   (0.010)**   (0.001)*  (0.388)                            **       **       **                                          **                 industrial   0.668   0.500   1.128    0.825    -0.532   -0.630   -15.665   -0.682   -0.886                 design right   (0.041)*    (0.829)   (0.368)   (0.189)   (0.352)   (0.465)   (0.991)   (0.482)   (0.466)                 License or   -0.153   1.316   -0.575   0.647   1.318   0.582    0.517    -14.582   -15.865                 Sell Patent   (0.665)   (0.026)**   (0.361)   (0.475)   (0.001)*  (0.479)   (0.567)   (0.988)   (0.990)                                                                **                 N          13749    4193     1672     1025     6195    2151     1367     7143     2411                 McFadden   0.287    0.329    0.326    0.431    0.407   0.208    0.277    0.521    0.355                 R                  2                 Cronbach‘s   0.76   0.80     0.82     0.81     0.81    0.76     0.81     0.73     0.79                 α                Source: Authors’ own analysis.                Significant values at p<0.5*, p<0.01**, p<0.001***                       Regarding EU funding for firm’s innovative activities, the analysis shows similar trend as                the  government  funding  but  for  Croatia  and  Estonia,  firm’s  machine  acquisition  and  internal                R\&D show no effect on firms attracting EU funds. Regarding training for innovative activities and                firm’s introduction of innovation, the results show the propensity for innovative SME’s to attract                funds  from  the  EU  with  the  only  exception  being  Bulgaria  and  Latvia  (for  introducing                innovation)  but  innovative  firms  in  the  Czech  Republic  and  Slovakia  show  the  probability  to                attract EU funds for introducing innovation and training for innovation activities. Majority of                innovative SME’s that applied for patent are likely to attract EU funds except for Lithuania and                Slovakia. Only Bulgaria and Latvia innovative SME’s showed propensity to attract EU funds for                industrial design right but for Hungary, sale of patent showed no effect on firm attracting EU                funds.                                                                     88","Table 2: EU Funding for Firms Innovative Activities                            Bulgaria   Czechia   Estonia   Croatia   Hungary   Lithuania   Latvia   Romania   Slovakia                 Firm Innovative Activities                 Intramural   2.007   1.275    1.164    -2.175   1.187    3.402   3.020     3.859   1.885                 R\&D        (0.001)*  (0.001)*   (0.110)   (0.348)   (0.001)**  (0.001)*  (0.001)**  (0.001)*  (0.020)**                               **       **                         *       **    *           **                 Extramural   -0.626   -0.320   0.449   1.881    0.093    -0.836   -0.778   0.103   -0.179                 R\&D        (0.047)*   (0.067)*   (0.197)   (0.103)   (0.649)   (0.001)*  (0.037)**   (0.853)   (0.702)                                                                           **                 Machine     3.432    2.637    0.569    17.845   3.001    1.578    2.155    1.940   3.577                 Acquisition   (0.001)*  (0.001)*  (0.126)   (0.992)   (0.001)*  (0.001)*  (0.001)*  (0.001)*  (0.001)*                               **       **                        **       **       **       **       **                 External    -0.200   0.082    -0.330   1.042    0.143    0.105   -1.044    0.446   0.104                 Knowledge   (0.251)   (0.652)   (0.339)   (0.076)*   (0.505)   (0.680)   (0.021)**   (0.282)   (0.819)                 Acqusition                 Training    0.707    0.107    1.027    1.179    -0.016   -0.200   0.906   -0.338   -0.095                            (0.001)*  (0.475)   (0.003)*  (0.120)   (0.920)   (0.366)   (0.005)*  (0.670)   (0.831)                               **               **                                  **                 Innovation   0.118   0.225    0.899    -0.447   0.705    0.444    0.036    1.825   -0.432                 Intro.      (0.446)   (0.144)   (0.006)*  (0.473)   (0.001)*  (0.053)*   (0.917)   (0.023)**   (0.392)                                                **                **                 Intellectual Property Right                 Patent App.   0.387   1.097   1.319    1.999    0.741    0.438    1.606    2.287   -0.364                            (0.069)*   (0.001)*  (0.005)*  (0.031)**   (0.015)**   (0.267)   (0.001)*  (0.001)*  (0.758)                                        **      **                                  **       **                 industrial   1.263   2.302    0.469    -0.502   -0.374   0.394    1.175   -1.432   -0.623                 design right   (0.001)*  (0.301)   (0.383)   (0.716)   (0.457)   (0.609)   (0.044)*   (0.184)   (0.584)                               **                 License or   0.391   0.157    -0.781   -19.593   1.177   0.530    0.232   -14.805   -0.713                 Sell Patent   (0.216)   (0.779)   (0.570)   (0.999)   (0.002)*  (0.493)   (0.676)   (0.987)   (0.521)                                                                  **                  N           13749    4193     1672     1025     6195     2151     1361     7143    2411                 McFadden    0.373    0.283    0.289    0.386    0.415    0.276    0.406   0.473    0.355                 R                  2                 Cronbach‘s   0.76     0.80     0.82    0.81     0.81     0.76     0.81     0.73     0.79                 α                Source: Authors’ own analysis.                Significant values at p<0.5*, p<0.01**, p<0.001***                  4  Conclusion                       Innovation  as  it  has  been  discussed  in  the  numerous  literatures  above  contributes                immensely to the economic growth and prosperity of nations. This assumption by far has been                highlighted in all policy documents of the EU to which member states have adopted same. Hence                innovation  and  firm’s  innovation  activities  cannot  be  underestimated.  The  main  goal  of  this                paper  is  to  analyze  whether  firm’s  innovativeness  determines  the  public  financial  support                innovative SME’s attract in some selected CEE countries. Based on the conceptual framework,                we deduced that; innovative SME’s that are engaged in innovative activities attract government                financial support and or EU funds for their innovative activities. As a result of public innovation                policies  that  support  SME’s  which  engage  in  innovative  activities,  national  and  EU  funds  are                likely to be awarded SME innovators.                      Our result has demonstrated that based on the innovative activities firms engage in, which                are measurable per their innovation outcomes achieved, majority of the SME’s in CEE countries                attract financial support from the central government and or EU. These findings have therefore                confirmed  our  hypotheses  H1 and  H2. The  results  corroborate  the  finding  of Un  \&  Montoro-                Sanchez  [23]  that  public  funding  is  influenced  by  firms’  propensity  to  innovate  likewise                Heshmati and Loof [10] who found public funds to support SMEs in Sweden. North, Smallbone \&                Vickers [16] also found in the UK that depending on the intensity of the SME in innovation, the                firm gets to participate in public sector support programs in Lee Valley region of London.                      In the meantime, the analysis provides mixed results regarding public financial support                especially  regarding  EU  funds.  This  is  mainly  due  to  the  different  levels  of  the  innovation                                                               89","capacity of the selected countries and their propensity to receive financial support. For instance,                [19]  describe  these  innovation  groups  i.e.  (innovative  capacity  and  performance)  to  be                moderate, modest and strong innovators in their analysis of some selected CEE countries. In the                current 2018 European Innovation Scoreboard, all the selected CEE countries are categorized                into  either  moderate  or  modest  innovators  with  Bulgaria  and  Romania  well  below  the  EU                average. As such, differences exist among states and their funding policies.                      The result also shows the robustness of innovation and SME’s innovative activities in the                CEE countries after the post-EU accession and the economic recession. State financial support is                necessary to drive firms to productive ways and innovation has been the key driver. Firms have                to perform and survive whilst creating employment for people thereby contributing to economic                growth. In the nutshell, we recommend that much attention be giving to the outcomes of these                supported innovative activities of SME’s in the selected countries since the result showed rather                less effect of public financial support on them. Also, cross regional research be done in order to                duly  ascertain  the  most  efficient  SMEs  for  comparison  sake  and  to  show  policy  direction  of                public authorities.                  References                 [1.]  ALMUS,  M.,  \&  CZARNITZKI,  D.  2003.  The  effects  of  public  R\&D  subsidies  on  firms'  innovation                     activities: the case of Eastern Germany. Journal of Business \& Economic Statistics; 21(2):226-236.                [2.]  BELAS, J., DEMJAN, V., HABANIK, J., HUDÁKOVÁ, M., \& SIPKO, J. 2015. 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[11.] HYYTINEN, A. \& TOIVANEN, O. 2005. Do financial constraints hold back innovation and growth?                     Evidence on the role of public policy, Research Policy; 34(9):1385-1403                [12.] KATTEL, R. \& KAROL, E., 2009. The copying paradox: Why converging policies but diverging                     capacities development in Eastern European Innovation Systems? Georgia Institute of Technology.                [13.] KLETTE, T. J., MØEN, J. \& GRILICHES, Z. 2000. Do subsidies to commercial R\&D reduce market                     failures? Microeconomic evaluation studies. Research Policy; 29:471–495                [14.] LESARKOVA, L. 2014. Evaluating Innovations in Small and Medium Enterprises in Slovakia, Social                     and Behavioral Sciences; 110:74 – 81                [15.] LLOYD-REASON, L., \& MUGHAN, T. 2002. Strategies for internationalization within SMEs: the key                     role of the owner-manager. 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Different Approaches to Managing Innovation Activities: An                     Analysis of Strong, Moderate, and Modest Innovators, Engineering Economics; 28(1): 47–55                [20.] SARLIJA, N., BILANDZIC, A. \& STANIC, M. 2017. Logistic regression modelling: procedures and                     pitfalls in developing and interpreting prediction models, Croatian Operational Research Review                     (CRORR); 8:631–652                [21.] STEJSKAL, J., \& HAJEK, P. 2017. Modelling collaboration and innovation in creative industries using                     fuzzy set qualitative comparative analysis. The Journal of Technology Transfer; 1-26.                [22.] STEJSKAL, J., MERICKOVA, B. M. \& PROKOP, V. 2016. The Cooperation between Enterprises:                     Significant part of the innovation process – a Case Study of the Czech Machinery Industry,                     Ekonomika a management; XIX (3):110-122.                [23.] UN, C. A., \& MONTORO-SANCHEZ, A. 2010. Public funding for product, process and organizational                     innovation in service industries. The Service Industries Journal; 30(1): 133-147.                [24.] STEYERBERG, E. W., EIJKEMANS, M. J., HARRELL, F. E., \& HABBEMA, J. D. F. 2001. Prognostic                     modeling with logistic regression analysis: in search of a sensible strategy in small data sets. Medical                     Decision Making; 21(1): 45-56                [25.] WESTMORE, B. 2013. Innovation and Growth: consideration for public policy, Review of Economics                     and Institutions; 4(3):50                                                                                                           91","Facebook Practices of the Czech Regional Capitals – Pilot                   Insights in the Character of the Communication with Citizens                                                          a                                                                               b                                           HRŮZA Filip , MAKÝŠOVÁ Lucia                                  Faculty of Economics and Administration, Masaryk University, Czech Republic                                             a                b                                              99925@mail.muni.cz,  402978@mail.muni.cz                Abstract                 Social  media  are  continuously  becoming  a  new  significant  tool  for  public  administrations,  not  only  for                reaching  their communities, but also for getting feedbacks, generating discussions  or stimulating other                forms  of  civic  participation.  From  this  perspective,  the  introduction  and  use  of  social  media  in  public                administration  have  enabled  to  intensify  and  expand  this  two-way  relationship  between  public                administration bodies on a particular level of government and the public or relevant stakeholders. Current                practice and previous relevant research show public administration entities use social media with diverse                intensity, purpose or strategy. This research is gathering current experience and knowledge concerning                this  specific  issue  abroad  and  with  focus  on  the  Czech  Republic.  The  sample  contains  the  data  of  the                Facebook  posts  of  the  Czech  regional  capitals  and  the  aim  of  the  paper  is  to  analyse  what  type  of                information  local  governments  publish  through  its  Facebook  pages  and  how  public  is  engaged  in  the                communication.                Keywords: In-depth analysis; descriptive statistics; regional cities; Facebook                 JEL Classification: H11, Z13                    1  Introduction                       Over  the  past  few  decades,  public  administration  and  politics  have  undergone  various                changes.  One  of  the  major  was  the  transformation  of  communication  between  public                administration entities or politics and citizens caused by the development of new technologies.                Especially  the  internet  created  and  provided  completely  new  space  for  various  interactions                between  these  actors  with  almost  unlimited  potential.  The  transformation  of  the  Web  1.0                (passive,  one  way  of  communication)  to  Web  2.0  (interactive  and  responsive  two-way                communication)  changed  the  way  of  how  public  administration  (PA)  entities  (for  example,                municipalities, regions or agencies) can communicate with its citizens or customers (responsive                websites,  social  networks  etc.).  Since  the  online  space  provides  various  tools  for  online                communication  (websites,  social  networks,  mailings  etc…),  differing  among  themselves  in                certain aspects, for the particular research it is better to distinguish between them and focus on                each  of  them  separately.  Therefore,  social  networks  and  their  use  by  public  administration                entities were chosen to be analysed in this paper.                      Using social networks (SNs) as one of the communication tools is an opportunity for local                governments  to  inform  its  citizens  via  different  channels,  providing  more  space  or  forms  of                information  transfers  between  the  source  of  the  information  and  recipient.  But  SNs  can  also                raise citizens’ awareness of the PA institution role and competencies (Špaček 2018) or create                two-way communication with their users (e.g. citizens, residents, tourists, NGO, companies etc.).                This  particular  communication  tool  can  be,  therefore,  used  not  only  to  disseminate  relevant                information  (like  an  official  municipal  magazine  or  not  well-developed  websites)  but  also  to                receive feedbacks, opinions and ideas or to raise various discussions and debates more or less                sophisticated. This, in fact, can help improve public policies and public services and motivate                citizens to actively participate in public matters (Bonsón et al., 2017). However, the use of SNs in                the life of a municipality can be far more significant. They can also be used as a nudging tool for a                similar effort as previously mentioned, or they can help foster social cohesion of a community                (Špačková and Ouředníček 2012). Last but not least, other previous research also revealed the                                                               92","linking  between  the  use  of  social  media  and  trust  in  government  (Song  and  Lee  2015).  It                confirms our assumption that SNs belongs to the variety of communication tools perceived by                citizens as a matter of governmental accountability to them (Picazo-Vela et al. 2012). But indeed,                it depends on what and how it is communicated to the audience. Further research could show                whether governments use SNs for this purpose (for example, to raise their credibility among its                audience) and whether it succeeded or whether they use this specific communication tool to a                different purpose (for example, to develop the community life).                      Current practice and previous relevant research show public administration entities use                social media with various intensity – from a complete absence of activity at the social media to                frequent  and  intensive  use,  usually  associated  with  higher  investments  and  also  following                outputs.  Although  the  previous  research  indicates  increasing  trends  of  using  SNs  by  public                institutions (cf Mossberger et al., 2013, Bellström et al., 2016), there is still lack of research and                knowledge  based  on  empirical  evidence  on  how  SNs  are  adopted  and  used  by  these  type  of                institutions (Bonsón et al., 2017). This research is focusing on analysing the mentioned aspects                from the perspective of regional cities in the Czech Republic with focus on the use of particular                social network (Facebook) as a dominant SN platform used by public administration entities in                the  Czech  Republic. There  are also  available other  similar  tools  like Twitter  or  YouTube,  but                their significance from the perspective of using by Czech public administrations is negligible in                comparison with Facebook.                      This research is preliminary and is trying to gather what it is currently known about the                practice of using SNs by the Czech municipalities from previous research and discuss what the                research potential of this issue is considering the possibilities, limits and specifics of SNs. By                analysing  the  posts  uploaded  by  the  Czech  regional  cities,  the  paper  analyses  what  type  of                information local governments publish through its Facebook pages, how the public engage in the                communication, in terms of what is the type of their engagement and based on when the post is                published. Subsequently, the outcomes of our research will be compared with the findings of                relevant domestic and international research. The discussion is formulated based on the review                of relevant literature and own preliminary research done in this field, that should initiate further                and much more in-depth research on this topic, which the authors intend to continue.                  2  Data and Methods                       The  methods  used  for  this  paper  are  interpretative  content  analysis  and  descriptive                statistics. Research questions and design of this paper was inspired by the previous relevant                researches listed in the following table.                                             Table 1: Research focus of prior literature                Author(s)        Research question                Hoffman  et  al.  What kind of government communication behaviour is successful in SN?                (2013)                Sivarajah  et  al.  What is the impact of using Web 2.0 technologies by LGs for internal work?                (2015)                Bellström  et  al.  What type of information does an LG send through its Facebook page?                (2016)           What type of information does an LG receive through its Facebook page?                                 What  does  the  type  of  information  communicated  on  Facebook  reveal  about                                 government-citizen communication?                Bonson  et  al.  How do LGs in Western Europe use FB as a communication and engagement channel?                (2017)           How are citizens engaging with their LGs by using FB?                                 What factors influence activity levels by LGs and engagement levels by citizens?                DePaula  et  al.  To  what  extent  can  the  Facebook  messages  in  a  sample  of  LG  departments  be                (2018)           categorized within the typology?                Source: Authors.                                                                  93","For the purpose of the analyses, it was retrieved 838 posts uploaded on Facebook by the                Czech regional capitals in April 2018 (Brno - 55; České Budějovice - 112; Hradec Králové - 154;                Jihlava - 17; Karlovy Vary - 25; Liberec - 29; Olomouc - 23; Ostrava - 21; Pardubice - 59, Plzeň -                81; Praha - 117; Ústí and Labem - 67 and Zlín - 78). The data were collected from Facebook by                using Netvizz. The application is a variable data extractor that provides outputs for different                sections of Facebook in standard formats. It enables to extract data of particular profile, except                of personal profiles (Rieder, 2013). For each post it may extract data about the content and the                form of the post, the date when the post was uploaded or the number of reactions, comments                and shares. These variables were used in the analysis. Moreover, the data regarding the number                of fans in April were retrieved for each observed Facebook page.                      Firstly, the qualitative interpretative content analysis was used to classify the posts based                on the purpose of the post and the field of the information provided within. The coding was                performed  in  three  steps.  In  the  beginning,  the  initial  list  of  potential  purposes  and  areas  of                information covered in the posts were prepared, based on the previous research (Bellström et                al., 2016, Bonsón et al., 2015). Then, the list was modified based on the content of the analysed                posts. Finally, the sample was re-coded and checked again. The posts were subjected to only one                category. If a post could be classified into more than one category, it was classified in the most                suitable category.                      Secondly, municipalities were split into two groups based on selected criteria (fans per                capita, engagement per post, engagement per fan) measuring their basic features according to                general goals (scope or activity etc..) from the perspective of social networks or marketing in                general.  The  purpose  of  this  split  was  to  distinguish  municipalities  according  to  their                successfulness in using SNs for deeper analysis. The regional cities that ware ranked among the                three best at least in one of the criteria, were classified as a municipality with the successful use                of Facebook (Hradec Králové, Karlovy Vary, Liberec, Praha, Ostrava, Zlín), remaining cities were                assigned to the control group (Brno, Jihlava, Olomouc, Pardubice, Plzeň, Ústí and Labem).                               Table 2: Ranking of the regional municipalities based on the selected criteria                                                      1             2                3                                                       st                                                                     nd                                                                                      rd                           Fans per capita     Karlovy Vary     Liberec     České Budějovice                                                                Karlovy                           Reactions per post   Praha                       Ostrava                                                                Vary                           Reactions per fan   Hradec Králové   Praha       Zlín                Source: Authors.                       Thirdly, the descriptive statistics were used to investigate how regional municipalities use                SNs and whether and how the engagement (calculated as sum of comments, shares and different                type of reactions) and the content differs between the two groups. Moreover, engagement of                Facebook users was analysed, based on the content of the uploaded post and based on the time                and day when the post was uploaded.                  3  Results and Discussion                       The  content  analysis  reveals  a  one-way  form  of  communication  prevails  on  Facebook                pages of the Czech regional capitals. This finding is in line with the main outcome of Svidroňová                et al. (2018). Based on the analysis of social networks of Slovak regional cities (posts uploaded                during  February  and  March  2018),  the  authors found  out  that  LGs  communication  on SNs  is                characterised mainly by ex-ante informing and various competitions associated with funding for                some public services, but with very limited calling for more active participation of citizens or                followers  in  decision-making.  The  main  intention  of  municipalities  on  SNs  is  to  disseminate                information regarding life in the municipality. This finding corresponds with the conclusions of                Bonsón et al. (2015), Mossberger et al. (2013) and of Špaček (2018) analysis based on the data                of Czech regions using Facebook. If the municipality published posts asking their fans to express                                                               94","their opinion, mostly the posts were related to the leisure activities and had a form of a contest;                the stimulation of civic participation was missing. Similar results were also obtained by Špaček                (2018). These findings indicate selected public administration entities are still not capable of                benefiting from the opportunities that social networks offer and use them for informing public                about issues and events occurring in the regional municipality (public and community issues).                Further analysis showed specific differences in LGs performance on SNs and with the use of the                control  group  the  difference is  also  observed.  The  differences could  be  identified in  terms of                what and how is communicated to the users (followers).                                             Figure 1: Purpose of the PA communication                                  Source: Authors.                       Following  table 3  shows  the  differences  in  post  distribution  and  average  engagement                (overall and then categorised based on the particular type of engagement) between both groups                from the perspective of thematic areas inspired by relevant literature.                                Table 3: Differences in characteristics between control group and the rest                                                                            Avg. number of   Avg.                                     Post distribution   Avg. engagement                             Avg.                                                                             comments     number of   number                                                                                           reactions                                                TOTA               TOTA             TOTA              of                 Category           1     2             1     2            1    2           (like,                                                 L                  L                L              shares                                                                                            sad…)                 Architecture      0.9%   6.6%   3.0%   97.4   18.0   33.9   22.2   2.1   6.1   27.0    2.0                 Commercial services   14.7%   5.0%   11.2%   44.8   17.3   41.0   3.9   0.3   3.4   33.3   4.4                 Culture           3.5%   1.0%   2.6%   29.7   20.4   26.2   1.1   1.7   1.3   22.2     2.7                 Education        11.2%   11.9%   11.5%   31.7   16.7   24.7   1.3   0.6   1.0   20.6   2.9                 Environment       3.0%   4.3%   3.3%   29.2   21.1   26.4   1.5   2.2   1.8   21.9     2.7                 Health care       6.2%   5.6%   6.0%    6.5   21.5   14.0   0.0   0.0   0.0   12.5     1.5                 History           0.4%   0.7%   0.5%   24.7   40.4   33.7   1.0   2.9   2.1   26.3     5.2                 Housing           3.9%   9.3%   5.8%   40.7   23.6   30.0   5.3   2.8   3.8   21.3     5.0                 Charity           0.6%   1.7%   1.0%   19.8   29.2   24.1   3.5   0.4   2.1   16.9     5.1                 Job offer         1.1%   1.7%   1.3%   12.3        12.3   0.0        0.0       7.8     4.5                 Leisure activities/                 entertainment     0.7%   0.0%   0.5%   48.8   25.0   39.3   1.4   1.2   1.3   30.0     8.0                 Marketing                 municipality     13.2%   15.9%   14.2%   190.5   25.9   164.2   5.3   1.6   4.7   139.5   20.1                 Others            2.4%   2.6%   2.5%   45.9   51.9   48.2   1.8   7.1   3.9   29.3    15.0                 Public administration   2.2%   3.6%   2.7%   30.7   13.8   22.6   3.5   3.4   3.4   16.5   2.7                 Reconstruction    3.2%   2.6%   3.0%   118.7   46.6   95.6   23.9   6.8   18.4   68.4   8.8                 Regional development   2.2%   3.6%   2.7%   35.0   31.9   33.5   8.2   7.0   7.6   23.7   2.2                 Safety            3.7%   3.6%   3.7%   57.0   45.5   52.9   8.0   2.5   6.0   16.8    29.0                 Sport            10.1%   9.9%   10.0%   38.9   41.5   39.9   3.1   1.5   2.5   29.5    7.7                 Technical services   6.0%   1.3%   4.3%   17.4   20.0   17.7   0.9   1.0   0.9   13.3   3.4                 Tourism           1.9%   0.0%   1.2%   133.9       133.9   4.4       4.4     104.9    24.6                 Transport         8.8%   8.9%   8.8%   68.6   24.5   52.5   18.7   3.4   13.1   29.1   10.3                Source: Authors.                                                                 95","There are no noticeable differences between those groups in terms of post distribution                (the most substantial differences can be seen in categories as architecture, commercial services,                housing or technical services). However, there are significant differences between the groups in                terms of average engagement or the average number of comments which can be caused by a                different  distribution strategy,  the  audience  with  different  characteristics,  different  quality  of                posted content etc.                      Further, our research also confirmed the higher potential of original content (not shared)                in terms of raising general awareness (number of reactions and comments). In case the post was                original, the average engagement was 59.7, whereas the average engagement of the shared post                was  19.8.  Slightly  surprising  could  be  the  finding  that  posts  containing  visual  feature  are                significantly more successful in raising the engagement in case of own (original) content (with                an  average  engagement  of  61.3)  rather  than  the  shared  ones  (16.7).  Unfortunately,  the                mechanism  of  the  Facebook  algorithm  is  hidden  for  our  eyes.  It  seems  that,  perhaps,  it                prioritises  the  content  generated  by  the  profile  owner  over  the  shared  content  as  well  as  it                probably prioritizes the content depending on the day or time it was uploaded on Facebook.                However, this assumption must be verified on larger data sets using further techniques because                there is still a lot of unknown variables and factors influencing efficiency and success of the SNs                communication.Table 3 depicts the average distribution of users’ engagement based on the hour                (0-24h) and day of the week (Mo-Su) when the post was uploaded. It confirms the assumption                that  the  audience  is  engaged  the  most  within  the  weekends  (users  have  more  free  time  at                disposal,  generally  to  spend  it  by  leisure  activities,  social  networks  including).  From  the                perspective of a day time it seems that most active hours according to the uploading of the posts                are during the late afternoons and evenings or within the mornings. More successful (with using                the  control  group  and  based  on  the  selected  criteria)  municipalities  in  terms  of  higher                awareness on SNs focus their communication between 8-10h and 18-20h (time represents, in                this case, the time when the post was uploaded) and spread it within the whole week rather than                concentrating on publishing their content only on certain days. Contrary to the assumptions the                highest probability in reaching high users’ engagement is within the weekend (Sa-Su), based on                our data and observations. From the perspective of raising the discussion, it seems that there is                no significant difference like in engagement discussed above. An ideal timeframe for raising the                discussions seems to be afternoon 16-18h.                                         Table 3: Average distribution of users’ engagement                          Avg. engagement   Mo   Tu      We     Th      Fr     Sa      Su    Total                               0–8        87.0    60.9   55.4    15.6   24.3   14.3     5.0   34.5                               8–10       51.6    62.5   47.0    44.9   92.3   134.9   46.4   64.0                              10–12       32.8    14.3   33.0    49.7   25.5   174.4   24.8   40.0                              12–14       32.1    30.4   43.1    22.4   31.9   19.0    14.5   31.0                              14–16       41.8    49.9   42.8    55.4   47.2   83.6    40.8   49.4                              16–18       45.2    32.3   24.4    38.2   79.3   49.6   250.3   51.2                              18–20       93.5    88.7   136.7   56.7   47.1   113.0   141.7   102.8                              20–24       19.5    16.0   147.7   99.2   25.5   21.4    25.7   49.7                              Total       44.9   45.9    52.2   45.2    46.0   96.7    70.9   52.8                Source: Authors.                  4  Conclusion                       The analysis shows that municipalities use different communication strategies with users                via SNs with different outcomes (in terms of engagement, content, reach etc…). With the use of                evidence-based methods, LGs can use SNs more actively (to achieve two-way communication)                concerning the principles as accountability, transparency or participation. SNs provide a two-                                                                 96","sided problem to be solved – supply (LGs) and demand (users) - with different kind of methods                and approaches that can be used.                      The  issue  of  engagement  is  not  purely  black  and  white  matter,  public  administrations                profiles including. The purpose and the content of their communication may differ from private                companies, which also use this communication tool to do business. But as well as the companies,                if governments want to use this tool efficiently to reach their goals (raise credibility, improve                service delivery, develop the life in community etc.), they need to:                      1.  set up a clear strategy of their marketing communication (including the strategy for                         using their SN profile);                      2.  understand the needs and behaviour of their audience (Kennedy and Moss 2015), how                         to build it (able to reach new users), how to maintain and develop it;                      3.  know how to raise the awareness in tough and very intensive competition with other                         information providers on SNs (companies, NGOs, users etc.).                      Therefore, governments usually must upload a suitable mixture of posts reflecting both                their primary mission as well as supplementary activities and initiatives ideally supported with                responsive commentary strategy to not only raise awareness but also to raise the engagement in                the community. It is, however, the ideal scenario of how to build a community via social network                and how to keep it viable according to certain principles and goals. But this whole scenario in                general  breaks  down  into  many  pieces  that  are  affected  by  different  factors,  internal  and                external, including sponsorship. Thus, further research in this area needs to take into account                previously mentioned specifics and limits of the research. We would like to follow up on this                preliminary  research  and  its  findings  and  continue  by  further  research  in  this  field  by                verification of preliminary findings on more massive datasets, developing and testing of content                typology  and  in-depth  analysis  of  LG  communication  via  SNs  to  understand  what  they                communicate to their users and with what efficiency or success.                  Acknowledgment                       This  research  is  supported  by  the  Masaryk  University  internal  grant,  project                no. MUNI/A/1121/2018:  “Online  fundraising  a  sociálne  média  v prostredí  neziskových                organizácií”.                  References                 [1.]  BELLSTRÖM, P. et al. 2016. Facebook usage in a local government: A content analysis of page owner                     posts and user posts. Transforming Government: People, Process and Policy, vol. 10 no. 4, p. 548-567.                [2.]  BONSÓN, E. et al. 2015. Citizens' engagement on local governments' Facebook sites. An empirical                     analysis: The impact of different media and content types in Western Europe. Government                     Information Quarterly, vol.32, no. 1, p. 52-62                [3.]  BONSÓN, E. et al. 2017. Facebook practices in Western European municipalities: An empirical                     analysis of activity and citizens’ engagement. Administration \& Society, vol. 49 no. 3, p. 320-347                [4.]  DEPAULA, N. et al. 2018. Toward a typology of government social media communication: Democratic                     goals, symbolic acts and self-presentation. Government Information Quarterly, vol. 35 no. 1, p. 98-                     108.                [5.]  HOFMANN, S. et al. 2013. What makes local governments' online communications successful?                     Insights from a multi-method analysis of Facebook. Government Information Quarterly, vol. 30 no. 4,                     p. 387-396.                [6.]  KENNEDY, H., MOSS, G. 2015. Known or knowing publics? Social media data mining and the question                     of public agency. Big Data \& Society, vol. 2 no. 2, p. 1-11.                [7.]  MOSSBERGER, K et al. 2013. Connecting citizens and local governments? Social media and                     interactivity in major US cities. Government Information Quarterly, vol. 30 no.4, p. 351-358.                                                                 97","[8.]  PICAZO-VELA, S. et al. 2012. Understanding risks, benefits, and strategic alternatives of social media                     applications in the public sector. Government information quarterly, vol 29 no. 4, p. 504-511.                [9.]  RIEDER, B. 2013. Studying Facebook via data extraction: the Netvizz application. WebSci, vol. 1, p.                     346-355.                [10.] SIVARAJAH, U. et al. 2015. Evaluating the use and impact of Web 2.0 technologies in local                     government. Government Information Quarterly, vol. 32 no. 4, p. 473-487.                [11.] SONG, CH., LEE, J. 2016. Citizens’ Use of Social Media in Government, Perceived Transparency, and                     Trust in Government. Public Performance \& Management Review, vol. 39 no. 2, p. 430-453.                [12.] SVIDROŇOVÁ, M. M., KAŠČÁKOVÁ, A., VRBIČANOVÁ, V. 2018. Can Social Media be a Tool for                     Participatory Governance in Slovak Municipalities? NISPAcee Journal of Public Administration and                     Policy, vol. 11, no. 2, p. 81-101.                [13.] ŠPAČEK, D. 2018. Social media use in public administration – the case of facebook use by Czech                     regions. NISPAcee Journal of Public Administration and Policy, vol. 11 no. 2, p. 199-219.                [14.] ŠPAČKOVÁ, P., OUŘEDNÍČEK, M. 2012. Spinning the web: New social contacts of Prague’s                     suburbanites. Cities, vol. 29 no. 5, p. 341-349.                                                                                                                            98","Competencies and Financing of the City of Bratislava                                                  and its Boroughs                                                                                   b                                                        a                                        JACKO Tomáš ; KAŇKOVÁ Alexandra                                  Faculty of National Economy, University of Economics in Bratislava, Slovakia                                           a                 b                                            tomas.jacko@euba.sk;  alex.kankova@gmail.com                Abstract                 The aim of the paper is to analyze selected competencies and their financing in the City of Bratislava and                its 17 city boroughs. The representatives of the City of Bratislava and the respective boroughs argue that                they  receive  insufficient  funding  in  terms  of  central  government  income  tax  revenue  distribution.                Furthermore, according to research, the current system is costly, inefficient and does not deliver the same                quality standards of public service provision for all citizens in Bratislava. The article offers suggestions for                possible  changes  in  order  to  decrease  the  cost  and  increase  efficient  use  of  public  finances.  Two  key                solutions  are  proposed  and  discussed.  First,  reduction  in  the  vast  number  of  city  borough  councillors.                Second,  using  the  analysis  of  selected  competencies  transferred  from  the  central  government  to  the                municipal  registry  offices  and  construction  offices,  the  paper  provides  a  comparative  perspective  and                shows the differences in expenditure and efficiency of individual boroughs and their respective offices.                The  authors  identify  performance  benchmarks  among  boroughs  and  discuss  the  claims  of  insufficient                funding  given  to  construction  offices.  The  authors  collected  quantitative  data  which  shows  contrasting                differences in expenditure and efficiency among the 17 boroughs. Based on an analysis of final accounts                and other statistical data, the paper presents results that could make public expenditure of Bratislava city                boroughs more economic and efficient.                Keywords: local government; competencies; financing; Bratislava; efficiency                 JEL Classification: H72                    1  Introduction                       The city of Bratislava is the capital city and also the most populous city of Slovakia. As the                country’s capital city, it has some specificities compared to other municipalities in Slovakia – for                instance  a  federal  two-tier  structure  of  local  self-government  which  splits  Bratislava  into  17                separate  self-governing  boroughs  on  top  of  one  city  level.  The  authors  decided  to  analyze  2                transferred central government competencies and in particular their financial aspects in all of                the 17 Bratislava city boroughs. The paper will examine two of them, namely the registry offices                and  construction  offices.  Generally,  financial  security  and  funding  of  registry  offices  is  not                questioned by the Bratislava city boroughs and their representatives. By contrast, many of the                boroughs argue that central government funding is not sufficient for running their construction                offices.  The  authors  decided  to  choose  these  two  competencies  since  all  17  Bratislava  city                boroughs  hold  construction  office  powers  and  14  city  boroughs  carry  out  registry  office                responsibilities.                      The aim of the paper is to analyze selected competencies based on their financing in the                city of Bratislava and its 17 city boroughs. The representatives of the city of Bratislava and the                respective boroughs argue that they receive insufficient funding in terms of central government                income  tax  revenue  distribution.  Furthermore,  according  to  research,  the  current  system  is                costly, inefficient and does not deliver the same quality standards of public service provision for                all citizens in Bratislava. The article offers suggestions for possible changes in order to decrease                the  cost  and  increase  efficient  use  of  public  finances.  Two  key  solutions  are  proposed  and                discussed.  First,  reduction  in  the  vast  number  of  city  borough  councillors.  Second,  using  the                analysis  of  selected  competencies  transferred  from  the  central  government  to  the  municipal                registry  offices  and  construction  offices,  the  paper  provides  a  comparative  perspective  and                                                                99","shows the differences in expenditure and efficiency of individual boroughs and their respective                offices.                  1.1 On Bratislava local self-government                      The city of Bratislava together with the city of Košice have a special status in the system of                territorial  self-government  in  Slovakia.  As  the  number  of  their  inhabitants  exceeds  200                thousand,  they  are  obliged  to  follow  special  legislation  (Act  no.  377/1990  on  the  City  of                Bratislava; and Act no. 401/1990 on the City of Košice). Another specific feature is that they are                the only two cities in the Slovak Republic that have a two-tier local self-government. Apart from                the city level, there is also the borough level with 17 self-governing boroughs. [1, 5]                      The city-level authority is the city mayor (primátor) who is the statutory body of the city,                carries out an executive role and represents the city. The other equally important body is the                city  council  which  acts  as  the  city’s  legislative  body  and  collectively  decides  on  the  most                important questions of the city for the benefit of its citizens. The city-level institution is the city                hall or city office (magistrát) which is the administrative, organizational and service centre of                the city. At the borough level, the statutory authority and executive role is vested in the borough                mayor  (starosta).  Borough  offices  (miestne  úrady)  follow  the  same  structure  and  logic  but                operate  only  at  the  borough  level  and  carry  out  different  functions  to  the  city  office.  [4,  10]                Hence, citizens of Bratislava are provided the same services by law but they can be performed                very differently across the city – both in terms of cost and quality – depending on the borough in                which they live. [2]                      Individual  municipalities  carry  out  self-governing  (i.e.  original)  and  delegated  (i.e.                transferred)  powers  (i.e.  competencies)  through  elected  representatives  and  employed                municipal office staff. Original competencies are financed purely from the local self-government                budget and the individual municipalities are solely responsible for the service provision, quality,                financing and availability. For example, protection of municipal property, collection of local taxes                and fees, management of municipal property, etc. On the other hand, transferred competencies                are financed from budgetary chapters of respective ministries. Slovak municipalities (i.e. local                self-governments) receive central government funding based on a formula which reflects among                other variables the number of citizens, altitude, number of students living in the municipality,                number of citizens over the age of 62, etc. For example, construction offices, registry offices and                schools belong to transferred competencies.                      Local self-governments or municipalities and in the case of Bratislava, city boroughs hold                regular local elections in which voters can directly elect their local representatives. Due to the                large number of deputies in the territory of Bratislava (17 borough mayors, 1 city mayor, 272                borough councillors and 45 city councillors) and the associated expenses, one of the aims of the                paper is to demonstrate the possibility of spending less public finances by simply reducing the                number of borough councillors. Of course, other means of increasing efficiency and effectiveness                are possible. For instance, even in some transitional economies with a significant degree of state                ownership, local governments can be successfully supported by their public enterprises [3].                   2  Material and Methods                       The  paper  explores  the  concepts  of  economy  and  efficiency  as  two  of  the  3  Es  (the                remaining one being effectiveness). For the purposes of this paper, the authors focus on two of                them: economy (i.e. spending less) and efficiency (i.e. doing more with less). Economy shall be                understood  as  cost-effectiveness  or  an  effort  to  minimize  costs,  i.e.  minimizing  public                expenditure. Efficiency goes one step forward and expects a particular process to perform better                in  terms  of  the  input  vs  output  ratio.  Hence,  a city  borough  that  aims  to  perform  both                economically and efficiently should focus on providing its services and/or performing its basic                legal  competencies  at  the  lowest  possible  cost  and  with  the  highest  possible  outputs.  The                authors  understand  the  complexity  and  various  details  behind  local  self-government                expenditure, competencies and service provision. Quality of service provision is for instance one                                                               100","of crucial topics that deserve thorough research attention but it is not taken into consideration                in  this  paper.  Some  research  has  already  been  conducted  in  the  area  quality  and  service                provision by local self-governments in Slovakia. [2] Although this might be seen as a research                limitation and authors readily admit it, focusing on selected aspects of economic and efficient                use  of  public  resources  reveals  at  least  some  parts  of  the  self-government  expenditure  and                service provision mosaic in Bratislava.                      The paper sets two aims. First, to discuss the possibility and potential financial benefits                from  decreasing  the  number  of  borough  councillors.  From  an  economic  perspective,  such  a                measure would be the easiest to implement and would immediately result in relatively small but                quick  financial  gains  for  the  boroughs.  However,  this  is  a  hard  measure  to  pass  politically  –                voluntarily and perhaps even harder through the national legislative process.                      Second,  the  aim  of  the  paper  is  also  to  analyze  and  financially  compare  two  of  the                transferred  competencies  –  namely  the  registry  offices  and  construction  offices  –  from  the                budgetary and public expenditure perspective. The aim is to provide suggestions for change that                will contribute to more economic and efficient use of public finances. These two competencies                were  selected  purposely  due  to  the  fact  that  both  are  transferred  competencies  (i.e.  public                finances are transferred separately for them from the central government budget). Furthermore,                they will also bring some contrasting perspective since registry offices are regarded as being                sufficiently financially covered or subsidised, whereas construction offices are seen by many city                boroughs as being underfunded. Perhaps the only realistic option for boroughs has been to co-                fund (i.e. further subsidise) them using their local budgets and own financial resources. This, of                course, means that financial resources are missing elsewhere. Based on collected financial data,                the paper will show to what extent these claims are substantiated or not and how individual                boroughs financially manage and cover these two selected competencies.                      In terms of data collection, the authors collected necessary quantitative data from readily                available sources published online (e.g. boroughs‘ budgets) but some data had to be collected by                means of Freedom of Information requests. For instance, the figures regarding the number of                borough councillors are publicly available on borough websites. However, the authors had to                submit a number of Freedom of Information requests in order to receive annual expenses and                councillors’  remuneration  data.  The  authors  of  the  paper  readily  admit  that  the  research                methods  used  in  this  article  are  rather  simplistic  and  limited  in  scope.  Instead,  more                sophisticated  research  methods  and  tools,  non-parametric  and  parametric  reference                technologies such as DEA could be used in further research to provide more accuracy and depth.                [9]                  3  Results and Discussion                  3.1 Cutting the number of councillors                      The  number  of  councillors  in  each  Bratislava  borough  and  municipality  in  Slovakia                depends primarily on the size of their population. However, each municipality has the right to                decide on its own number of councillors within the legally set minimum and maximum limit.                Bratislava city boroughs can have – based on their population - between 5 and 35 councillors.                The lowest number of councillors is in the boroughs of Čunovo, Devín, Jarovce and Lamač, while                the largest number of councillors is in the most populous borough of Petržalka.                      Until  recently,  there  was  no  minimum  or  maximum  limit  regarding  councillors’                remuneration.  This  changed  in  2018  and  the  law  now  sets  a  limit  to  the  councillors’                remuneration which can be a maximum of 1/12 of the municipal mayor’s salary. However, at the                time of collecting data for this article, all Slovak municipalities including the 17 Bratislava city                boroughs could decide on the remuneration of their councillors as they saw fit. Hence, Table 1                shows significant differences across the 17 boroughs in terms of remuneration per councillor.                      The paper has already mentioned the abundance of elected representatives in the city of                Bratislava (17 borough mayors, 1 city mayor, 272 borough councillors and 45 city councillors).                Having such a vast number of paid representatives and at the same time claiming that funding is                                                               101","not sufficient makes cutting the number of councillors as the first and easiest way of cutting                expenditure. There could be an argument made regarding the need for more representatives,                which could claim a greater extent and options for representative democracy. However, one of                the key expectations from political representation or any form of democracy or government in                general, is its functioning and cost. [6] Voters can legitimately question the need to remunerate                more than 300 elected city representatives in a city of under 500 thousand inhabitants when                cities of a similar population or size can do a better job with significantly fewer paid elected                representatives. For instance, the Municipality of Copenhagen (Denmark) with a population of                600 thousand has only a 55-member city council and 1 Lord Mayor. City of Chandler (Arizona,                USA) has only 5 council members and one mayor in a city of 250 thousand people.                                                 Table 1: Number of councillors                                        Source: Authors.                       The obvious financial indicator with public expenditure saving potential is the number of                councillors and their annual and average remuneration. One other important indicator is also                the number of councillors per 1000 inhabitants, which brings a more comparative perspective of                whether boroughs really need such a high number of councillors. Boroughs of Devín and Lamač                were the only boroughs where councillors were not given any remuneration. Devín was in the                state of receivership and hence they did not have much choice. Councillors in Jarovce on the                other hand voluntarily chose not to be given any remuneration in the given year and saved the                resources for other use by the borough.                      Based on the obtained data, the authors created a table that includes, in addition to the                above data, a proposal for changes in the number of councillors, as well as the potential cost                saving, should this proposal be implemented. The proposal to adjust the number of councillors is                based  on  the  legal  minimum  and  maximum  number  of  councillors  that  boroughs  can  have.                Therefore, the authors used the minimum number as both a proposal and the benchmark for                some simple calculations and the corresponding results than can be seen in the table. Based on                the proposed model, the number of councillors of all boroughs would be 181. Despite being still                a high number, it would mean a reduction by 91 councillors compared to the current situation.                The  number  of  councillors  per  1000  inhabitants  would  be  0.43  rather  than  the  current  0.64                councillor per 1000 inhabitants.                      The  table  also  shows  significant  differences  in  average  councillor’s  remuneration.  For                instance, councillors in Ružinov received 10 291.68 € as their average annual remuneration. On                the other hand, the councillors in Čunovo received only 281.86 €. Perhaps most importantly,                total annual councillors’ remuneration would be under the authors’ proposed model 491 178.15                € less. It could be argued whether this is a significant cost-cutting mechanism but nevertheless it                could be one of a number of ways how to cut unnecessary cost. In case of a much more radical                decrease  of  the  number  of  councillors,  the  resulting  sum  would  be  even  more  interesting.                                                              102","Examples from across the world show that local government can be effectively managed and                citizens can feel even more democratically empowered with less councillors. There are other                numerous  means  of  public  participation  (e.g.  participatory  budgeting,  e-referendum,  citizen                focus  groups,  public meetings  and  discussions, etc.).  [7]  Hence,  public  participation  and  local                democracy should not be limited to merely electing councillors once every 4 years – no matter                the ratio of citizens per councillor. Elections and representative democracy neither guarantee                nor automatically lead to citizen involvement.                 3.2 Registry offices                      From the many original and transferred competencies that municipalities are obliged to                perform, the authors selected two transferred competencies: registry offices and construction                offices. This was done on purpose due to the fact that the two competencies are performed by                most  Bratislava  boroughs  and  hence  are  possible  to  compare  and  benchmark.  Almost  all                boroughs have their own construction offices except for Devín, Dúbravka and Lamač, which have                entrusted  the  borough  of  Karlova  Ves  to  perform  this  role  in  exchange  for  their  funding.  All                boroughs run their own registry offices.                      City boroughs‘ representatives generally argue that central government subsidies for the                municipal  construction  offices  are  largely  insufficient  (collected  data  proves  this)  and  by                contrast, subsidies for the municipal registry offices are sufficient (collected data also proves                this). Hence, comparison of these two particular competencies should also bring interesting data                in  terms  of  (in)sufficient  funding  which  could  also  support  or  refute  the  general  political                statements.                      The authors examined the following data obtained through publicly available sources and                Freedom of Information Act requests, in particular:                      •  subsidies from the national budget for the registry and construction offices,                      •  revenue from fees collected by the registry and construction offices,                      •  expenditure of the registry and construction offices,                      •  number of staff working at the registry and construction offices,                      •  surplus or extra funding needed to cover offices’ expenditure (= subsidy + collected                         fees - expenditure)                      •  expenditure per citizen,                      •  average cost per employee.                       Funding for the registry offices is provided from the national budget and also from the                administrative  fees  that  municipalities  collect.  Results  in  Table  2  show  that  only  5  of  the                boroughs (Podunajské Biskupice, Staré Mesto, Rusovce, Vajnory, Vrakuňa) must extra co-fund                this  competency  since  the  national  government  subsidy  and  revenue  from  the  collected  fees                seem  to  be  insufficient.  However,  the  table  also  shows  boroughs  which  have  a  much  better                expenditure per citizen and average cost per employee than others. Naturally, every borough is                different and there are unique characteristics which have an impact on these results too (e.g.                level  of  population  growth).  Nevertheless,  some of  the  results  are  very contrasting  –  even in                boroughs  with  similar  populations  and  size  (e.g.  Podunajské  Biskupice  vs.  Rača,  Rusovce  vs.                Záhorská  Bystrica).  Boroughs  with  the  best  results  in  terms  of  expenditure  per  citizen  and                average  cost  per  employee  (Záhorská  Bystrica,  Rača,  Jarovce)  can  be  used  as  performance                benchmarks not only for the 5 boroughs which need to co-fund this competency but also for                other boroughs which could save more resources and use them elsewhere.                                                                           103","Table 2: Registry offices                                              Source: Authors.                      One  of  the  goals  was  to  show  whether  national  government  subsidies  provide  enough                funding to cover selected transferred competencies. Only five of Bratislava‘s boroughs have to                co-fund  this  activity  since  the  national  subsidy  and  the  collected  administrative  fees  are  not                enough. However, instead of co-funding, they ought to analyse their internal processes and find                possible  ways  to  cut  costs  and/or  make  their  registry  offices  work  more  efficiently.  Devín,                Lamač, Dúbravka and Karlova Ves are good examples of how sharing competencies and basic                concepts such as economies of scale and working together can result in an economically viable                solution  for  all.  Further  research  is  necessary  to  assess  more  closely  not  just  the  5                underperforming  boroughs  but  also  other  boroughs  and  their  respective  registry  offices  and                reasons for their financial results. Nevertheless, from financial and comparative perspectives,                they seem to have limits that can be and should be addressed by their local leadership – for                example, through staff performance appraisals. [8]                  3.3 Construction offices                      Similarly to registry offices, construction offices also belong to the group of transferred                local self-government competencies. However, construction offices compared to registry offices                need  to  be  co-funded  by  Bratislava  boroughs  to  a  much  greater  extent.  This  is  not  merely                political rhetoric but also supported and proved by collected financial data. Table 3 shows that                14  out  of  17  construction  offices  need  further  co-funding  since  both  national  government                subsidies and revenue from fees collected by construction offices are not sufficient. Data shows                that almost 800 thousand € had to be covered by boroughs’ own financial resources. Only three                boroughs ended up with surpluses (Čunovo, Devín, Ružinov). Again, further research is needed                to look more deeply into the workings of the three surplus boroughs and the 14 underfinanced                boroughs.                      Construction  offices’  agenda  is  to  a  large  extent  affected  by  the  number  of  inhabitants,                structure of population (e.g. young families moving in and building houses), extent of business                and real estate activity, etc. Hence, one employee’s annual agenda in a small and rather rural                borough  such  as  Čunovo  deals  with  significantly  different  construction  issues  and  agenda                compared  to  her  colleague  in  the  inner  city  borough  of  Staré  Mesto.  Nevertheless,  when                boroughs of similar size and urban development character are compared, this still brings very                contrasting results especially in terms of cost per citizen and average cost per construction office                                                                104","employee. For instance, Vajnory and Záhorská Bystrica are boroughs of similar population size                and  both  are  undergoing  significant  construction  activity.  However,  the  borough  of  Vajnory                spent  only  6.72  €  per  citizen  on  the  construction  office  agenda  and  the  average  cost  per                construction office employee was 12 445.04 €. By contrast, the borough of Záhorská Bystrica                spent nearly twice as much (11.68 €) per citizen and the average cost per employee was more                than double (26 614.00 €).                                                   Table 3: Construction offices                                           Source: Authors.                       The  authors  acknowledge  the  fact  that  construction  office  agenda  is  very  complex  and                even  two  otherwise  similar  boroughs  may  face  different  challenges  resulting  in  significantly                different expenditure. However, differences in cost per citizen and average cost per construction                office  employee  are  significant  not  only  between  individual  boroughs  that  share  similar                characteristics but across all the 17 boroughs. This naturally raises the issue of economic and                efficient use of public finances. Is there an inherent financial problem resulting from the lack of                national government subsidy to cover this crucial self-government competency or is it rather a                problem  of  financial  management?  In  other  words,  if  three  construction  offices  can  be  in  a                surplus, why cannot the rest 14?                  4  Conclusion                       The  article  offered  suggestions  for  possible  changes  in  order  to  decrease  the  cost  and                increase efficient use of public finances in 17 Bratislava city boroughs. Two key solutions were                proposed and discussed. First, reduction in the vast number of city borough councillors which                would save at least 491 178.15 € each year. Second, using the analysis of selected competencies                transferred  from  the  central  government  to  the  municipal  registry  offices  and  construction                offices,  the  paper  provided  a  comparative  perspective  and  showed  the  differences  in                expenditure  and  efficiency  of  individual  boroughs  and  their  respective  offices.  The  authors                identified  performance  benchmarks  among  boroughs  and  discussed  the  claims  of  insufficient                funding given to construction offices.                      This  admittedly  simplistic  but  necessary  financial  analysis  showed  that  Bratislava  city                boroughs  still  have  considerable  reserves  in  the  management  of  public  funds  and  that  the                argument of insufficient national subsidies is not completely valid and should be addressed by                local leaders in more detail and demonstrated by corresponding data. Otherwise, it will remain                merely as political rhetoric and a smokescreen to cover waste of public resources. Also, results                                                               105","and  conclusions  ought  to  be  questioned  and  tested  by  other  quantitative  and  qualitative                methods. More sophisticated methods and tools such as DEA could be used in further research                to bring more accuracy and depth into the topic.                  Acknowledgements                       This article was supported by VEGA grant no. 1/0705/18 Ekonomika spoločného výkonu                kompetencií.  The  article  is  based  on  results  from  the  bachelor‘s  thesis  “Kompetencie  a                financovanie  mesta  Bratislava  a  mestských  častí“  by  Alexandra  Kaňková  (University  of                Economics, 2017).                  References                 [1.]  BUČEK, J. et al. 2010. Miestne financie a miestny ekonomický rozvoj. Bratislava: Geografika.                 [2.]  ČERNĚNKO, T. 2017. Measuring Performance and Effectivity of Local Governments. In Winter                     Seminar of Regional Science. 7th Winter Seminar of Regional Science: Proceedings: 15th -18th March                     2017, High Tatras, Slovakia. Bratislava: EKONÓM publishing                [3.]  DEBORGER, B., KERSTENS, K. 1996. Cost efficiency of Belgian local governments: A comparative                     analysis of FDH, DEA, and econometric approaches. Regional Science and Urban Economics; 26 (2):                     145-170.                 [4.]  KLIMOVSKÝ, D. 2014. Základy verejnej správy. Bratislava: Wolters Kluwer.                [5.]  NIŽŇANSKÝ. V., HAMALOVÁ, M. 2013. Územné a správne členenie Slovenska. Bratislava: Vysoká škola                     ekonómie a manažmentu verejnej správy.                [6.]  ROGOFF, K. 1990. Equilibrium political budget cycles. American Economic Review; 80: 21 -36.                [7.]  SPÁČ, P., SLOBODA, D. 2014. Municipalizácia, volebný systém a možnosti participácie v miestnej                     samospráve na Slovensku. Piešťany: Komunálne výskumné a poradenské centrum, n. o. Piešťany,                     available from http://www.konzervativizmus.sk/upload/regio/Studia_Spac-                     Sloboda_2014_finalna_verzia.pdf [accessed 15 January 2019]                [8.]  STAROŇOVÁ, K., SPAČKOVÁ, J. 2017. Uses of Performance Appraisal. Information: The Case of                     Trenčín Municipal Office. Proceedings of the 21st International Conference Current Trends in Public                     Sector Research Šlapanice, 19–20 January 2017, Masaryk University, 105-112.                [9.]  WALDER, A.G. 1995. Local Governments as Industrial Firms: An Organizational Analysis of China's                     Transitional Economy. American Journal of Sociology; 101 (2): 263-301.                [10.] ŽÁRSKA, E. et al. 2016. Verejná správa. Bratislava: Vydavateľstvo Ekonóm.                 Other sources                    •  Budgets and final accounts of all 17 city boroughs for 2014 and 2015.                    •  Freedom of Information Act replies from city boroughs.                                                                                    106","The Impact of Public Expenditure Efficiency                                  on Labour Productivity in V4 Countries                                                        a                                                                                  b                                        JÍLKOVÁ Eva ; ZÁVADSKÁ, Miroslava                                          Moravian Business College, Olomouc, Czech Republic                                          a                b                                           eva.jilkova@mvso.cz;  miroslava.zavadska@mvso.cz                Abstract                 This paper is focused on the comparison of labour productivity in the four Visegrad countries (the Czech                Republic,  the  Slovak  Republic,  Hungary  and  Poland).  It  briefly  deals  with  the  measurement  of  labour                productivity on a macroeconomic scale. The main goal of this paper is to compare the development of                labour  productivity  in  the  four  Visegrad  countries  as  related  to  public  expenditures  based  on  labour                market policies and average wages. We use linear and nonparametric correlation analyses to quantify the                association between the tested variables. To explore associations between variables we also use graphical                displays. The results of our analysis on labour productivity show the dependency of the two indicators,                namely the labour productivity and average wages. Moreover, no correlation was found between labour                productivity and public expenditure on labour market policies for all V4 countries. The outcome for labour                market policies expenditure shows in the highest correlation between the Czech Republic and Hungary,                but no significant result for other V4 countries. It could be caused by different government strategies on                labour policy and non-economic influence.                 Keywords: labour productivity; average wages; labour market policies expenditure; Visegrad countries.                JEL Classification: C10, E24, J24, H5                    1  Introduction                       The  economic  community  is  strongly  interested  in  the  productivity  of  all  kinds  of                production factors especially because it is closely connected with the growth of the real wages                and living standards of the population. Labour productivity is an indicator of vital importance. It                is used as GDP per person employed. The productivity of the four Visegrad countries may be                dependent on public expenditures and wages. Labour market policy expenditure or decisions in                this area could have influenced the development of labour productivity.                      Several authors, who are interested in this topic, are Jardim et al.[1], Riley and Bondibene                [2] The mentioned authors have looked at the issue of labour productivity with connection to                policies,  economic  growth,  welfare  and  their  implications  for  wages.  Labour  productivity                changes  over  time.  The  changes  in  productivity  could  depend  on  level  of  wages  and  labour                policies. The evidence shows that productivity does not increase when there is a reduction in                firm’s workforce [2]. We can see the relationship between labour productivity and minimum                wages as well. British authors [2] find evidence to suggest that companies responded to these                increases in  labour  costs  by  raising  labour  productivity. Organisational  changes,  training  and                labour skills are also very important for rising productivity.                      Many  authors  [3],  [4],  [5]  etc.  have  attempted  to  analyse  labour  productivity  and  its                determinants.  According  to  neoclassical  economic  theory,  price  floor  policies,  including  the                minimum  wage,  should  lead  to  a  non-market  equilibrium  marked  by  excess  supply  and                diminished demand. [1].                      On the basis of observations, they are making a number of recommendations to promote                the higher productivity of labour. For the higher labour productivity is important to consider the                other  determinants  such  as  capital  intensity,  electricity  intensity,  fuel  intensity  and  wages.                Moreover, additional categories, for example, management and environment, should be included                for the assessment of labour productivity [5].                                                                107","The issue of labour productivity is also addressed in the scientific works of Boserup [6],                McGowan and Andrews [7], Hansen [8] and many others.                      The study [9] shows that unemployed individuals sympathizing with the political right are                more  strongly  opposed  to  demanding  measures  than  employed  individuals  with  the  same                political preferences. Moreover, aggregate support is found to be correlated with the country's                active labour market policies (ALMP) legacy, varying from high levels in Germany and the UK to                low  levels  in  Denmark  and  France.  The  findings  suggest  that  most  ALMPs  are  in  fact                implemented  despite  the  opposition  of  their  beneficiaries.  The  German  labour  market  policy                regime  constitutes  a  reliable  supporting  pillar  of  the  highly  productive  German  employment                system  [10].  Main  findings  of  Polish  authors  [11]  show  that  there  is  a  need  to  work  out  a                complex evaluation of labour market policies in the EU to provide comparative analysis of the                EU countries (or groups of countries). It would allow determining the level of development of                the country in terms of the efficiency of labour market policies. The EU countries with the best                labour market indicators represent diverse levels of LMP expenditure, which will be analysed in                this research for the four Visegrad countries.                  2  Material and Methods                       The analysis includes three sets of data for the four Visegrad countries (Czech Republic,                Slovakia, Poland and Hungary). Firstly, it includes the GDP per person employed as a measure of                labour productivity. This variable is presented in Euros per person in 2010 price level. Secondly,                the  expenditure  on  labour  market  policies  is  used  and  presented  in  Euros  spent  by  each  V4                country. And thirdly, this research contains the level of average monthly wages in Euros for each                year  of  V4  countries.  All  three  datasets  comprises  of  yearly  data  points  from  2006  to  2016,                which  were  downloaded  from  the  Czech  Statistical  Office,  Hungarian  Statistical  Office  and                Eurostat [12],[13],[14].                      Pearson correlation [15] belongs to linear analysis. The correlation coefficient can take the                values between -1 and +1, where -1 is perfect negative and +1 is perfect positive correlation                between the variables. When the coefficient is 0 then there is no linear correlation. This method                is widely used in the research as it highlights any relationships between tested variables. For                example,[16] applied this method in their analysis.                      The Pearson’s coefficient is the covariance of the two variables divided by the product of                their standard deviations. The form of the deviation includes a product moment, which is the                mean of the product of the mean-adjusted random variables.                      The Pearson linear analysis is followed by the Spearman nonparametric method, which is                less restrictive and it is applied for robustness checks and comparative examination.                      Spearman correlation [17] is a nonparametric correlation. It measures and determines the                strength and direction of monotonic relationship between two ranked variables, where the two                assumptions must be met. Firstly, as value of one variable increases, the other variable value                increases. Secondly, as value of one variable increases, the other variable value decreases. This                method is less restrictive than linear correlation.                  3  Results and Discussion                       The results in this chapter firstly look at each Visegrad country separately and after that it                highlights the correlations for every tested dataset including all V4 countries.                      Table 1 highlights the correlation coefficients for both methods in each country, and Table                2 represents the correlation outcomes for labour productivity, average wages and expenditure                on labour market policies.                                                                     108","Table 1: Main correlation results for each V4 country                                                      Pearson                  Spearman                                             LP and Wages  LP and LMP  LP and Wages  LP and LMP                              Czech Republic    0.605**        Х         0.836*         Х                              Slovak Republic   0.967*         Х         0.973*         Х                              Poland            0.781*         Х         0.836*         Х                              Hungary             Х            Х         0.700**        Х                              Note: * means 99% and ** means 95% significance level. x means not significant.                Source: Authors (2019).                                       Table 2: Main correlation results for each tested variable                                                   Pearson                                Spearman                                   CZ and    CZ and   CZ and    PL and    CZ and    CZ and    CZ and    PL and                                   SK        PL       HU        SK        SK        PL        HU        SK                 Labour                 productivity       0.896*    0.857*      Х       0.955*    0.964*   0.936*      Х       0.973*                 Wages              0.884*    0.850*   0.701**    0.885     0.882*   0.664**   0.655**   0.836*                 LMP                  Х         Х      0.815*       Х         Х        Х      0.718**      Х                 Note: * means 99% and ** means 95% significance level. x means not significant.                Source: Authors (2019).                 3.1 Czech Republic                      The  Pearson  and  Spearman  correlation  analysis  indicate  a  medium  strength  positive                relationship between the labour productivity, which is measured as a GDP per employed person,                and  the  average  wages.  It  shows  that  these  two  variables  co-move  together  over  the  period                between 2006 and 2016. Moreover, the impact of the set level of wages plays a role in growing                labour productivity. None of the methods identified any correlation between labour productivity                and the expenditure on labour market policies (LMP).                               Figure 1: Labour productivity, LMP and averages wages in the Czech Republic                                    €240,000                                    €200,000                                    €160,000                                    €120,000                                    €80,000                                     €40,000                                        €0                                           06  07  08  09   10  11  12  13  14   15  16                                                           Labour productivity_CZ                                                           LMP_CZ                                                            Wages_CZX100                Note: All figures are in Euros. The average wages figures were multiplied by hundred for better illustration purposes.                Source: Authors (2019).                                                                    109","In Figure 1 is shown the historical development of labour productivity, expenditure on                labour market policies and average wages. Average wages are multiplied by 100 for illustration                purposes and better visibility.                  3.2 Slovakia                      The  results  from  both  correlation  analysis  exhibit  very  high  (near  to  perfect  positive)                outcome. The Pearson coefficient is 0.967 and the Spearman correlation is 0.973. This very high                correlation is between the LP and wages, where the behaviour is strongly interconnected and                changes together over time. This result indicates even higher dependency than in case of the                Czech Republic, which should be taken into account by policy makers as it reflect the level of                growing labour productivity in this country. The outcome shows no correlation between labour                productivity and the expenditure on labour market policies.                      Figure 2 represents the historical development of all three variables between 2006 and                2016.                              Figure 2: Labour productivity, LMP and averages wages in the Slovak Republic                                 €300,000                                  €250,000                                  €200,000                                  €150,000                                   €100,000                                   €50,000                                      €0                                          06  07   08  09   10  11   12  13   14  15   16                                                           Labour productivity_SK                                                           LMP_SK                                                           Wages_SKX100                Note: All figures are in Euros. The average wages figures were multiplied by hundred for better illustration purposes.                Source: Authors (2019).                 3.3 Poland                      High and positive correlation was found in case of Poland at 0.781 for Pearson and 0.836                for Spearman correlation, which suggests both linear and nonparametric correlation between                labour  productivity  and  average  wages.  Also,  no  correlation  was  found  between  labour                productivity and LMP expenditure.                      Figure 3 shows the development of the tested datasets in Poland.                                                                                   110","Figure 3: Labour productivity, LMP and averages wages in Poland                                €250,000                                  €200,000                                 €150,000                                  €100,000                                   €50,000                                      €0                                         06  07   08   09  10   11   12   13  14   15   16                                                           Labour productivity_PL                                                           LMP_PL                                                           Wages_PLX100                Note: All figures are in Euros. The average wages figures were multiplied by hundred for better illustration purposes.                Source: Authors (2019).                 3.4 Hungary                      The  Pearson  correlation  outcome  did  not  show  a  significant  result  at  5%  level,  but  it                indicated a correlation of 0.700 for Spearman nonparametric correlation at 5% significance level                between LP and wages. The correlation between LP and LMP was not significant for any of the                two methods.                      In  Figure  4 are  featured the  changing  levels  of  the  labour  productivity,  expenditure  on                labour market policies and average wages in Hungary.                                  Figure 4: Labour productivity, LMP and averages wages in Hungary                                  €350,000                                 €300,000                                  €250,000                                 €200,000                                  €150,000                                  €100,000                                  €50,000                                      €0                                          06  07   08  09   10  11   12  13   14  15   16                                                            Labour productivity_HU                                                           LMP_HU                                                           Wages_HUX100                Note: All figures are in Euros. The average wages figures were multiplied by hundred for better illustration purposes.                Source: Authors (2019).                                                                         111","3.5 Labour productivity                      The outcomes for labour productivity indicate high positive correlation between the Czech                Republic  and  Slovak  Republic,  also  between  the  Czech  Republic  and  Poland,  and  Poland  and                Slovak Republic. The highest labour productivity is displayed in the Czech Republic from 2006 to                2011 and from 2012 to 2016 in the Slovak Republic. No correlation was found between Hungary                and other V4 countries. This can be due to a fact that Hungarian labour productivity differs in                the development to other tested states, as shown in Figure 5.                                            Figure 5: Labour productivity of V4 countries                                   €36,000                                   €34,000                                   €32,000                                    €30,000                                   €28,000                                   €26,000                                   €24,000                                    €22,000                                   €20,000                                          06  07   08  09  10   11  12  13   14  15  16                                                           Labour productivity_CZ                                                           Labour productivity_HU                                                           Labour productivity_PL                                                           Labour productivity_SK                Note: Labour productivity is presented in Euros per person calculated from GDP in 2010 prices.                Source: Authors (2019).                 3.6 Average wages                      The findings show that there is a high and positive correlation for average wages between                all four countries. The coefficient is the highest between the Czech Republic and Slovak Republic.                However, the coefficient is the lowest for Hungary using both correlation methods. Again, this                shows that Hungary slightly diverges from V4 countries, where from 2006 to 2008 the average                wage was the highest in Hungary, which changed from 2009 onwards (see Figure 6).                                              Figure 6: Average wages of V4 countries                                   €1,100                                    €1,000                                      €900                                     €800                                      €700                                      €600                                          06  07  08   09  10  11  12   13  14  15   16                                                         Wages_CZ   Wages_HU                                                         Wages_PL   Wages_SK                Note: The average wages are presented in Euros.                Source: Authors (2019).                                                                112","3.7 Expenditure on labour market policies                      Both linear and nonparametric methods displayed high and positive correlation between                the Czech Republic and Hungary; however, the level of expenditure differs considerably among                these two countries, as shown in Figure 7. There was no correlation found between other V4                countries. The expenditure on labour market policies shows how each government allocates the                resources within this sector.                                   Figure 7: Expenditure on labour market policies of V4 countries                                 €360,000                                   €320,000                                 €280,000                                   €240,000                                  €200,000                                  €160,000                                  €120,000                                          06  07   08  09   10  11   12  13   14  15   16                                                           LMP_CZ    LMP_HU                                                           LMP_PL    LMP_SK                Note: The LMP figures are presented in Euros.                Source: Authors (2019).                  4  Conclusion                       The analysis of the labour productivity in V4 countries between 2006 and 2016 identified                high and positive correlation between average wages and labour productivity. This result was                confirmed  by  both  (linear  and  nonparametric)  methods.  The  correlations  between  the  Czech                Republic,  the  Slovak  Republic  and  Poland  exhibited  similar  outcomes.  This  is  in  contrast  to                Hungary, where the results displayed different findings to other V4 countries when comparing                the development of the labour productivity, average wages and expenditure on public labour                policies.  The  efficiency  of  expenditure  on  public  labour  policies  (LMP)  did  not  confirm  any                significant  results  between  labour  productivity  and  LMP.  This  can  be  due  to  a  fact  the  LMP                includes multiple elements, which can be divided into sub-sections and analysed separately.                      The greater demand for skilled workers and policies such as training schemes would be                conducive  to  raising  productivity  even  further.  Also,  other  active  components  of  the  LMP                expenditures  such  as  contribution  to  support  regional  mobility,  socially  effective  jobs  or                bridging allowance could help to mitigate the wage inequality effects and help to increasing of                productivity.                      Therefore,  the  future  research  could  include  active  and  passive  components  of  the                expenditure on the labour market policies to be able to distinguish how each part affects the                labour productivity. Also, a regression analysis could highlight the relationship and impact of                each LMP component.                                                                          113","References                [1.]  E. JARDIM, L. C. MARK, R. PLOTNICK, E. INWEGEN, J. VIGDOR, and H. WETHING, “Minimum Wage                     Increases, Wages, and Low-Wage Employment: Evidence from Seattle,” NBER  Work. Pap. 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BOSERUP, The Conditions of Agricultural Growth. New York: Routledge, 2005.                [7.]  A. MCGOWAN, D. ANDREWS, M. ADALET MCGOWAN, and D. ANDREWS, “Labour Market Mismatch                     and Labour Productivity EVIDENCE FROM PIAAC DATA,” OECD Econ. Dep. Work. Pap., vol. 1209, p.                     51, 2015.                [8.]  B. E. HANSEN, “The New Econometrics of Structural Change: Dating Breaks in U.S. Labor                     Productivity,” J. Econ. Perspect., vol. 15, no. 4, pp. 117–128, 2001.                [9.]  F. FOSSATI, “Who Wants Demanding Active Labour Market Policies? Public Attitudes towards                     Policies that put Pressure on the Unemployed,” J. Soc. Policy, vol. 47, no. 01, pp. 77–97, Jan. 2018.                 [10.] S. BOTHFELD and P. ROSENTHAL, “The End of Social Security as we know it – The Erosion of Status                     Protection in German Labour Market Policy,” J. Soc. Policy, vol. 47, no. 02, pp. 275–294, Apr. 2018.                [11.] E. ROLLNIK-SADOWSKA and E. DĄBROWSKA, “Cluster analysis of effectiveness of labour market                     policy in the European Union,” Oeconomia Copernicana, vol. 9, no. 1, pp. 143–158, Mar. 2018.                 [12.] EUROSTAT, “Eurostat,” 2018. [Online]. Available: https://ec.europa.eu/eurostat. [Accessed: 09-Oct-                     2018].                [13.] Český statistický úřad, “Obyvatelstvo | ČSÚ,” 2018. [Online]. Available:                     https://www.czso.cz/csu/czso/obyvatelstvo_lide. [Accessed: 14-Jun-2018].                [14.] “Hungarian Central Statistical Office,” 2018. [Online]. Available: http://www.ksh.hu/?lang=en.                     [Accessed: 18-Oct-2018].                [15.] K. PEARSON, “Proceedings of the Royal Society of London - Royal Society (Great Britain) - Google                     Books,” in Notes on regression and inheritance in the case of two parents, 1895, pp. 240–242.                [16.] E. JÍLKOVÁ and V. ŘÍHOVÁ, “Regression and correlation analysis of labour and resource productivity                     indicators compared within the V4 countries,” Zesz. Nauk., vol. 115, no. 42, pp. 171–183, 2017.                [17.] C. SPEARMAN, “The Proof and Measurement of Association between Two Things,” Am. J. Psychol., vol.                     15, no. 1, p. 72, Jan. 1904.                                                                                 114","The Changing European Labour Market and its Consequences                                         on Social Expenditure System                                 KOTÝNKOVÁ, Magdalena         1, a ; WILDMANNOVÁ, Mirka    2, b                                  1                                    Department of Economics, University of Economics Prague, Czech Republic                                 2                                   Faculty of Economics and Administration, Masaryk University, Czech Republic                                          a             b                                          kotynkov@vse.cz;  mirka.wildmannova@econ.muni.cz                Abstract                During the second half of the 20th century, significant changes in the structure and concept of the welfare                state in Europe have emerged, mainly due to the changes in labour market. Since the 70s last century,                progressive  implementation  of  labour  -  saving  technologies  and  current  technologies  based  on  the                Internet  of  Things,  Data  and  Services  have  been  changing  economic  activity  and  consequently  the                character and forms of work. The accompanying phenomenon of these changes has been growing labour                market uncertainty and unemployment. People threatened by the unemployment, especially by the long-                term unemployment became dependant on social benefits and do not adequately contribute to the social                system used to finance the benefits. Therefore, welfare state has found itself in a crisis. The aim of our                discussion  is  to  evaluate  social  expenditure  trends  of  the  EU  Member  States  in  the  light  of  the  labour                market changes. Social expenditure trends are researched on the ESSPROS - Eurostat database on social                protection. The methods used are extrapolation and prediction. The original welfare state was built on a                well-functioning labour market with sufficient jobs creation, but new social risks emerged in last decades.                We agree that the European countries will have to make a crucial decision, whether the European social                model, which has played a key role in maintaining social contract in the past, is sustainable even in the                future.                Key words: social expenditure system, labour - saving technologies, digitisation of production, long - term unemployment                 JEL Classification: H53, I131, J165, J68                    1  Introduction                       Over a hundred years, the welfare state went through several stages, starting from the first                insurance company systems through the ”golden era“ of the 1960‘s to the current welfare state                crisis. Evolution of the social systems in the individual countries differed to a large extent with                respect to the voluntariness, i.e. insurance cover obligation related to various losses. The oldest                compulsory  insurance  concerned  occupational  accidents  and  was  introduced  in  several                European  countries  before  the  end  of  the  19th  century.  On  the  contrary,  unemployment                insurance was often voluntary and in most cases became compulsory after the World War I.                      Since the past century, the European countries have gone through major social reforms.                From  the  end  of  the  19   century,  Europe  has  been  one  of  the  most  dynamically  developing                                        th                continents in terms of social risk protection. Step by step the European welfare state started to                evolving. The objective of the welfare state and the reason for its establishment was to protect                families  and  individuals  against  social  risks.  Traditionally,  this  concerns  adequate  income  to                cover basic needs at the time of sickness, old age, disability, etc. Besides these traditional social                risks, new risks started being discussed at the end of the 70s last century (hereafter: “the 70s”).                The most significant problems appeared to be changes in the labour market and lack of cover all                risks including the long-term unemployment [12].                      The period of social expansion (1962 – 1973), sometimes also called “the welfare state                golden era”, is characterised by growing productivity and related rising standard of living of all                social  classes  and  high  employment  rate,  in  some  Western  countries  up  to  almost  full                employment rate. Thanks to sufficient funds, the number of social benefits increased along with                their amounts as well as the share of social expenses of the GDP [14].                                                                115","During  the  70s,  the  welfare  state  started  gradually  stagnating.  The  main  reason  was                progressive  implementation  of  labour  -  saving  technologies,  information  and  communication                technologies  (hereafter:  “ICT”)  which  have  changed  economic  activity,  the  structure  of                production and afterwards the character and forms of work. The accompanying phenomenon of                these  changes  on  the  labour  market  was  growing  uncertainty  and  unemployment  [13].  The                economic growth in mid-70’s slumped to lower figures, whereas some countries had reached up                to 5 % annual GDP increase in the previous decades. The European countries governments came                up  against  great  pressures  of  rising  social  expenditure  related  mainly  to  the  rising                unemployment and other benefits, such as benefits in need. Given the setup of the social systems                in the past and the very limited possibilities of restricting some of the social expenditure, i.e. in                health  system,  education,  social  services,  the  increasing  public  expenditure  share  was                accompanied by public debt. As a result of these as well as other factors such as the population                aging, the welfare states started struggling with the crisis which principally persists to the date                [14].                      Furthermore, next changes on labour market are expected in the concept \"Industry 4.0\".                The  term  means  the  vision  of  increasing  digitisation  of  production  based  on  the  Internet  of                Things, Data and Services [11]. The concept outlines the vision of the complete networking of all                production processes and the increased use of robots, which control themselves. The robots are                coming and if the forecasts are correct, it can mean the extinction for millions of jobs [6].                      The original welfare state was built on a well - functioning labour market with sufficient                jobs creation, but new social risks emerged in last decades. It is clear that given labour market                changes and population aging have changed the view of the welfare state in Europe. We agree                that  the  European  countries  will  have  to  make  a  crucial  decision,  whether  the  European  social                model, which has played a key role in maintaining social contract in the past, is sustainable even in                the future.                      Social  expenditure  dynamics  and  trends  in  European  countries  are  researched  on  the                ESSPROS database on social protection [5].                  2  Material and Methods                       The  objective  of  this  paper  is  to  evaluate  the  EU  Member  States  social  expenditure                dynamics as well as to identify their current fiscal trend, which requires an analysis of social                expenditure in a time series of the European countries. Therefore, the paper is based on the                ESSPROS database on social protection [5].                      However,  we  also  need  to  identify  the  main  directions  affecting  the  fiscal  pressures  in                European social policies. From that reason the paper is centred around the opinions of leading                European experts on labour market and welfare state trends and on EU strategic documents.                      The  methods  used  are  extrapolation  and  prediction.  The  basis  for  predicting  future                developments  in  the  labor  market  is  the  analysis  of  the  labor  market  development  from  the                beginning of the industrial era and, in particular, the analysis of labor market changes due to the                implementation of labor saving technologies in the 1970s. The sustainability of the European                Social Model is derived from further predicted labor market developments.                  3  Results and Discussion                       It  is  necessary  to  identify  main  reasons  affecting  welfare  state  requirements.  We  have                taken  into  our  consideration  primarily  labour  market  risks,  such  as  the  unemployment  and                specially the long term unemployment. Since the 70´s labour market risks have begun to rise due                to changes in dependence between economic growth on one hand and the volume of workforce                on the other hand.                      Industrial era dominated in Europe since the second half of the 19th century. However, at                the  beginning  of  the  70´s  the  structure  of  production,  character  and  forms  of  work  being                changing with introduction of labour-saving technologies. Relations between economic growth                                                               116","and jobs creation have weakened. A side effect of increasing labour productivity has become                unemployment, which has been a commonly discussed problem in the EU Member States. The                call  for  a  common  fight  against  unemployment  was  firstly  published  by  the  European                Commission  in  the  document  Growth,  Competitiveness,  Employment-Challenges  and  Ways                Forward for the 21th Century [3] and in the document European Social Policy-the Way Forward                for the Union [4].                      Labour-saving  technologies  weakened  jobs  creation.  Owing  to  that,  the  world  of  work                changed dramatically,  free  workforce  started  to  pass  from  the industry  to  the service  sector.                Gradually  the  whole  structure  of  the  economy  has  changed,  services  are  becoming  dominant                namely  both  in  the  share  in  GDP  and  in  employment.  With  the  time  production  of  material                property  stopped  being  crucial  for  the  economic  growth,  but  production  of  knowledge  and                algorithms and their application has become the most important. This caused a change in the                relation between the capital and labour.                      If there had been a relation of mutual dependence between economic growth and volume                and  quality  of  workforce  since  the  beginning  of  industrial  era,  in  the  last  decades  this                interconnection ceases to be significant. The relation between economic growth and labour was                separated which can be proved with the fact that the economic growth in the last decades of the                20  century started being reached even when the number of vacancies stagnated or increased                   th                very slowly [1]. At the beginning of that century, the International Labour Organisation stated                that 1% economic growth encourages increase in new workplaces by 0.3% while the relation                keeps weakening [10].                      But already in the year 1969, the economic theory accepted a concept of so called natural                unemployment  rate  where  unemployment  was  considered  being  a  natural  phenomenon.  The                concept  supposed  the  existence  of  the  lowest  sustainable  unemployment  rate  in  long-term                corresponding  with  a  potential  product.  Milton  Friedman  by  the  criticism  of  Philips  curve                coming  from  mutual  dependence  of  unemployment  and  inflation  based  on  the  premise  that                unemployment can be reduced versus higher inflation, stated that the dependence is true only                for  a  short-term  period.  In  the  long  term,  the  Philips  curve  is  stabilised  at  a  level  of  natural                unemployment  corresponding  with  a  potential  product.  Efforts  to  reduce  the  natural                unemployment rate by means of demand oriented economic policy of the government or the                Central Bank will lead to the rise in inflation only [7]. In the course of time it seems that the                natural rate of unemployment keeps increasing.                      Currently, labour market future is discussed. The trigger of this discourse was the German                concept Industry 4.0 [11], which was first introduced in 2011 and followed by the concept Work                4.0 [Green Paper Work 4.0, 2016].The term “Industry 4.0” was first introduced by the German                Industry-Science Research Alliance in 2011. In 2012, the German Working Group on Industry 4.0                presented  a  set  of  recommendations  to  the  German  federal  government.  The  Industry  4.0                workgroup members are recognized as the driving force behind Industry 4.0 [2].                      Industry 4.0 is the vision of increasing digitisation of production. The concept describes                how  the  Internet  of  Things,  Data  and  Services  will  change  production,  logistics  and  work                processes  in  the  future.  The  changes  brought  about  by  networking  based  on  the  Internet  of                Things, Data and Services have a greater impact than for industrial production alone because                they affect not only economies, but also the world of work and social life as a whole. The concept                Industry  4.0  is  now  shaping  the  digital  discourse  in  Europe  because  further  changes  are                expected with the implementation of new innovations and technologies [15].                      The  robots  are  coming  and  if  the  forecasts  are  correct,  it  can  mean  the  extinction  for                millions of jobs. Innovations may seem grandiose, but they can also be destructive, rendering                entire  professions  obsolete  even  as  they  boost  productivity  and  convenience.  If  widespread                predictions are correct, automation in the workplace is set to increase at an unprecedented rate                [9].  Many  areas  of  manual  work  are  being  affected.  Robots  in  factories  and  warehouses  are                becoming  more  mobile,  versatile  and  affordable.  It  is  not  just  manual  labour  that  is  ripe  for                automation:  white-collar  jobs  are  also  at  risk  as  software  becomes  more  sophisticated.  Data                analysis work in areas such as advertising and finance is being outsourced to computers.                                                                117","One issue that will loom ever larger as the incidence of automation increases is income                and  social  inequality.  Automation is fundamentally  the  substitution  of capital  for  labour. The                problem is that the people who already have the capital are the ones who will benefit most,                because they are the ones who will invest in the new automation. In other words, the rich will                get  richer  and  the  rest  will  suffer.  The  Internationale  Labour  Organization  (hereafter:  “ILO”)                needs to respond to the future of the work ongoing changes in order to be able to advance its                mandate for social justice.                      Labour  market  uncertainty,  unemployment  and  especially  long-term  unemployment                alongside with population aging are significant reasons of changing opinions on the role of the                state in the field of social policies. However, it can be shown that the importance of the welfare                state remains stable.                      According to the latest data from Eurostat, the statistical office of the European Union, the                social  protection  expenditure  reached  28.1  %  of  the  GDP  in  the  European  Union  in  the  year                2016. Since 2006, these expenditure in the European Union has increased, from 25.6 % of GDP in                2006  to  28.1  %  in  2016.  Eurostat  data  indicate  long-term  increase  in  the  social  protection                expenditure  till  the  year  2010.  A  rapid  increase  occurred  at  the  time  of  the  financial  crisis                between  2008  –  2010,  which  was  accompanied  by  increasing  unemployment.  However,                stagnation the social protection expenditure can be seen in the following years. Social protection                expenditure  started  stagnating  in  the  second  decade  of  that  century,  but  their  share  in  GDP                remains high. For more details see table No. 1.                         Table 1: Total social expenditure as a percentage of GDP in the time period 1995 – 2016                 Country          1995        2006       2008       2010        2012       2014       2016                 EU 27            .            .         25.6       28.6        28.7       28.7       28.1                 EU 28            .           25.7       25.9       28.6        28.7       28.7       28.1                 Eurozone         .           26.2       26.5       29.2        29.4       29.7       29.2                 Included:                 Belgium          27.3        26.6       27.7       29.4        29.6       30.2       29.8                 Bulgaria                     13.9       14.7       17.0        16.6       18.5       17.5                 Czech Republic   16.7        17.6       17.9       20.1        20.4       19.7       18.9                 Denmark          31.9        28.4       28.9       32.4        32.0       32.8       3.6                 Estonia                      12.0       14.7       17.6        15.0       14.9       16.4                 Finland          31.4        25.4       25.1       29.3        30.1       31.9       31.8                 France           30.3        30.7       30.8       33.2        33.8       34.5       34.3                 Ireland          18.6        17.1       20.2       24.8        23.6       20.6       15.8                 Italy            24.3        25.6       26.7       28.9        29.3       29.9       29.7                 Lithuania        .           13.3       15.9       19.1        16.3       15.3       15.4                 Latvia           .           11.9       12.1       18.3        14.4       14.4       15.2                 Hungary          .           21.9       22.3       22.5        21.3       19.8       29.2                 Germany          28.3        27.8       27.2       29.9        28.8       29.0       29.4                 Netherlands      30.6        26.3       26.1       29.3        30.6       30.6       39.5                 Poland           .           19.7       19.3       19.7        18.9       19.1       20.3                 Portugal         20.4        23.7       23.4       25.8        26.4       26.9       25.2                 Austria          28.8        27.5       27.6       29.6        29.2       29.8       30.3                 Greece           22.3        20.6       22.8       25.9        28.1       26.4       26.6                 Slovakia         18.5        16.0       15.7       18.2        18.0       18.5       18.4                 Slovenia                     22.3       21.0       24.4        24.9       23.9       23.3                 United Kingdom   27.1        24.8       25.7       28.8        28.9       27.5       26.2                 Spain            21.6        20.0       21.4       24.6        25.5       25.4       24.3                 Sweden           33.5        28.6       27.9       28.8        29.5       29.5       29.6                .  not available                Source: Eurostat- Esspross (2019).                      The EU average continued to mask major disparities between Member States. While the                social  protection  expenditure  reached  28.1  %  of  the  GDP  in  the  European  Union,  social                protection  expenditure  in  Eurozone  exceeded  29  %  of  the  GDP  in  Eurozone.  Traditionally,                Europe is led by France with nearly 34.3 % of social expenditure in the GDP in the year 2016 and                ranked  the  top.  Furthermore,  Finland,  Belgium,  Denmark,  Netherland,  Italy,  Austria,  Sweden,                Germany, United Kingdom and Greece currently spend over one fourth of their GDP on social                                                               118","protection expenditure. In contrast, social protection expenditure stood below 20% of GDP in                Romania, Latvia, Lithuania, Estonia, Ireland, Malta, Bulgaria and Slovakia, as well as in the Czech                Republic. These disparities reflect differences in living standards, but are also indicative for the                diversity of national social protection systems, labour market changes and population ageing                specific to each Member State. For more details see figure No. 1.                                         Figure 1: Social Expenditure as % of GDP, year 2016                                    Source: Eurostat- Esspross (2019).                       Social  protection  expenditure  per  capita  varies  substantially  across  Member  States.  In                2016,  social  protection  expenditure  per  capita  in  Purchasing  Power  Standards  (hereafter_                “PPS”),  which  eliminates  price  level  differences  between  countries,  showed  large  differences                between  EU  Member  States.  After  Luxembourg,  the  highest  expenditure  per  capita  were                recorded in Denmark and Austria. In contrast, the lowest expenditure per capita was registered                in Romania, Bulgaria and Latvia.                      Although there are common features in the evolution of the welfare state in the individual                countries, for example the growing role of the state in social policy, rate of redistribution and                provision of social services, there are also many differences between them. The scope of social                services differs depending on the economic conditions of the state, traditions, values and historic                development.                  4  Conclusion                       The original welfare state was built on a well-functioning labour market, but new social                risks emerged in last decades. It can be said that the industrial era dominated in Europe since                the second half of the 19th century ends today. A big change came in the 70s, when the character                of economic activity has changed due to the implementation of labor saving technologies and                forms of work have changed as well.                      If there had been a relation of mutual dependence between economic growth and volume                and quality of workforce typical for the industrial era, nowadays the interconnection does not go                anymore [1]. The relation between economic growth and labour was separated which can be                proved with the fact that the economic growth during the last decades of the 20  century started                                                                                           th                to  be  reached  even  when  the  number  of  vacancies  stagnated  or  increased  very  slowly  [3].                Similarly the International Organisation of Labour states that 1% economic growth encourages                increase in new workplaces by 0.3% while the relation keeps weakening [10].                      Further  changes  are  expected  on  labour  market  due  to  the  implementation  of  new                innovations and technologies. The concept Industry 4.0 is the vision of digitized economic activity                describing how the Internet of Things, Data and Services will change production, logistics and                work processes in the future and how will change the world of work and social life as a whole.                The concept Industry 4.0 is now shaping the digital discourse in Europe because the robots are                coming and if the forecasts are correct, it can mean the extinction for millions of jobs.                                                               119","People threatened by the unemployment become dependent on social benefits and do not                adequately  contribute  to  the  social  system  used  to  finance  the  benefits.  Unemployment  and                labour market uncertainty have become part of social and economic reality of Europe together                with the increase of disadvantaged groups of population on the labour market since the 70s.                Europe  keeps  struggling  with  the  labour  market  uncertainty  and  with  the  problem  of                sustainability of the welfare state. Digitization and robotics can even increase these problems.                However,  the  implementation  of  the  Industry  4.0  concept  brings  major  changes  in  economic                activity,  which  can  ultimately  affect  competitiveness  and  economic  development.  The  most                developed countries are aware of this fact.                      The  social  policy  is  trying  to  treat  families  facing  social  problems  with  various  social                benefits and allowances. The current social policy expenditure in the European countries has                been kept at a high level for a long time. In most European countries, in particular the western                ones, the expenditure exceed 25% of the GDP, i.e. more than one-fourth of their GDP. However,                EU  Member  States  are  heterogeneous  in  terms  of  social  aspects.  One  of  the  reasons  for  the                increased EU heterogeneity was the EU expansion to the east. An example can be shown: the rate                of social expenditure in France is 34% of GDP, while in Latvia only 15%. Europe diverges in                social aspects not only because of the economic development of the individual countries but also                as a result of various approaches to the social matters. The EU Member States tend to be divided                into groups based on the recognition and practicing of a different social expenditure philosophy                and this is one of the reasons why the EU fails to achieve a single direction.                      As emphasised by ILO expert, Daniel Vaughan-Whitehead [14], the European Social Model                played  a  key  role  in shaping  up  the  European  society after  the  2. Word War  by  encouraging                inclusive economic growth, high standard of living and decent working conditions. In some of                the European countries the key elements of the European Social Model have been transformed                in response to the crisis that began in 2008. As a result of the crisis it has turned out that the                current form of the European Social Model is not sustainable. The European Commission as well                as  ILO  has  come  to  realize  that  certain  elements  of  the  European  Social  Model  need  to  be                transformed  in  light  of  such  challenges  such  as  high  unemployment,  especially  long  term                unemployment  and  population  aging  in  Europe.  Therefore,  it  is  presently  necessary  for  the                European  Union  to  make  a  crucial  decision,  whether  the  European  Social  Model,  which  has                played a key role in maintaining social contract in the past, is sustainable even in the future.                   Acknowledgements                      The paper resulted from the grant – financial support of the Internal Grant Agency of the                University of Economics, Prague IGS F5/12/2018 and from the project of Masaryk University                MUNI/A/1018/2017.                  References                 [1.]  BAUMAN Z. 1998. Work, Consumerism and The New Poor. Oxford: Oxford University Press.                [2.]  BULLINGER, H. J. et al. 2014. Perspektivenpapier der Forschungsunion: Wohlstand durch Forschung –                     Vor welchen Aufgaben steht Deutschland? [online] Available on:                     http://www.forschungsunion.de/pdf/forschungsunion_perspektivenpapier_2013.pdf [cit. 2018-08-                     11]                 [3.]  European Commission. 1993. Growth, Competitiveness, Employment - the Challenges and Ways                     forward for the 21st Century. Brussel: European Commission.                [4.]  European Commission, 1994. 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Available on:                     http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=354                     36.                                                                                                        121","Efficiency Measuring in Public Administration from the                                             Employees´ Perspective                                                           a                                                                              b                                            KRÁL, Martin , HÁJEK, Ladislav                               Faculty of Informatics and Management, University of Hradec Králové, Czech Republic                                             a                b                                              martin.kral.2@uhk.cz,  ladislav.hajek@uhk.cz                Abstract                 Most developed countries around the world still have budget deficits at the moment of economic growth.                Instead of creating reserves for a period that may not be beneficial from a macroeconomic point of view,                most  of  these  countries  are  increasing  consumption  expenditures  and  virtually  passing  through  their                income.  In  addition,  in  recent  years,  the  issue  of  efficiency  not  only  of  consumer  spending  but  also  of                investment projects has become more and more frequent. Ensuring objective monitoring and evaluation                of  efficiency  in  public  administration  is,  however,  very  problematic,  both  from  the  point  of  view  of                politicians´ and managers´ abilities, as well as from their fear of failure. This paper describes basic ways to                measure efficiency in the public sector. Its aim is to identify a method of measuring efficiency based on a                survey of employees in public administration in the Czech Republic, which is the most appropriate - on the                basis of selected criteria (e.g. simplicity, complexity, time requirements, etc.). The survey results show that                the  most  promising  measurement  of  efficiency  is  through  performance  indicators.  On  the  contrary,                methods that are often used to evaluate business performance are not transferable to public sector at all.                The reason is their big focus on profit or theoretical and application complicatedness.                Keywords: Efficiency; Public Sector; Survey; Efficiency measuring                 JEL Classification: H11; H21; C83                    1  Introduction                      At present, most countries around the world are facing high debt, and surplus budgets in                developed countries are rather an exception. Even though 10 years have passed since the last                financial crisis, political representation in most countries has failed to find a way to sustainable                public finances. As a result, there is an ever-increasing growing trend of mandatory spending,                which  is  primarily  driven  by  household  consumption  or  savings,  instead  of  investments  that                would generate added value and would be a source of income in the future.                      The behavior of politicians is, however, understandable. In today's dynamic times, political                representation uses public finance to a large extent as a means of retaining and gaining more                potential  voters.  [14]  Public  finance  reforms  that  worsening  or  reversing  more  and  more                wastage by public resources are politically very poorly enforceable.                      Governments pay people, which put high pressure on wage growth not only in the public                sector. With the increase in the amount of money that is intended to pay wages, the sense of the                importance of relevant officials also grows. [4, 20] According to an individual job offer, more and                more employees are in a situation where they demand higher wages, but they do not match their                productivity. Here, however, public administration is faced with a fundamental problem, namely                the  impossibility  to  determine  the  financial  relationship  between  inputs  (pay)  and  outputs                (work). Unlike the private sphere, it is not the goal of public administration to make a profit, so                officials cannot use financial indicators to assess their efficiency, which would make it possible                to find out if their work is worthwhile. [13]                      However,  it  is  not  only  a  problem  of  evaluating  and  improving  the  performance  and                efficiency of the wages of employees in public administration but also of the various activities                and projects that public administration finances. It can be public goods (education, health, public                transport, etc.) and also various types of public services (e.g. elections, provision of data and                information, official boards, IT portals, etc.). This paper focuses on the topic of performance and                                                               122","efficiency evaluation, a topic that is very unpopular in public sector, and which is more spoken                and written than realized.                   2  Literature overview                       Efficiency in general (effectiveness) can be characterized by two main components, which                are  expediency  (results  must  match  their  quantity,  quality,  and  structure  of  needs)  and                economy, i.e. cost-effectiveness (action must be at the lowest cost). In order to talk about the                efficiency of the activity, both conditions have to be met at the same time. Increasing efficiency                occurs  when  the  effect  is  increased  (increasing  its  quantity,  quality,  structural  change)  and                reducing the costs associated with this effect.                      Governments  move  to  measure  accomplishments  and  associated  outputs,  activities  and                costs,  many  faces  mounting  pressure  to  produce  efficiency  measures,  which  show  \"units  of                output or outcome per unit of input\" for every program. Improvements in outputs per unit of                cost can easily come at the expense of service quality.                      When evaluating efficiency, methods used in the economic sphere are used in a specific                specification, the modification is also applied in the area of public administration. [10, 18] Given                the  real  use  of  public  sector  efficiency  assessment  methods,  this  article  compares  only  those                methods that, according to the Ministry of the Interior, have the greatest realization potential.                They  are  Management  by  Objectives  (MBO),  key  performance  indicators  (KPIs),  Balanced                Scorecard, data envelopment analysis (DEA), benchmarking, and assessment of compliance rates                (rating scales and evaluating interviews). [11]                      Metrics - Rating scales indicate the status of a particular system, eventually its efficiency.                Metrics are of a quantitative or qualitative nature, which can also be expressed as an objective                value. Even though it is a very simple method of efficiency evaluation, at first sight, it is used, for                example,  in  Lean  manufacturing  (LM).  It  involves  all  practices,  activities,  tools,  methods  and                techniques designed to reduce and even eliminate waste within organizations. [16]                      Management by Objectives (MBO) is a method based on setting and mutually agreeing on                goals and evaluating the success of their achievements. [3] This method emphasizes the result                rather than how it is achieved. It gives greater discretion to decision-makers and line staff who                are  responsible  for  meeting  the  goal  as  well  as  for  fulfilling  it.  In  terms  of  international                comparisons in public administration, this is the most used method of efficiency evaluation. [11]                This method is further developed in the Balanced Scorecard method, which additionally includes                a requirement of inter-linking goals.                      Balance scorecard (BSC) is a strategic management and efficiency measurement system                developed by Robert S. Kaplan and David P. Norton in the 1990s. [7] The BSC is based on the                principle of the balance of individual objectives, which requires the identification and evaluation                of several objectives in a context. The main areas of the organization's assessment are financial                perspective, customers (clients) perspective, process perspective, learning, and growth. The BSC                method is applicable in all areas, including the public sector, for which the financial perspective                has also been modified to the budgetary perspective. [18]                      Key Performance Indicators (KPIs) include performance indicators (metrics) of particular                processes, services, organizational units, organizations. KPIs, in addition to the required quality                and  efficiency.  These  indicators  are  used  at  all  management  levels  within  the  organization,                particularly in the area of strategic management and management by objectives (MBO). Their                use is fairly common in both the private and public sectors. [11]                      Evaluating  Interviews  (person-to-person  method)  are  one  of  the  main  methods  used                mainly  in  human  resources.  As  part  of  the  evaluation  interviews,  the  emphasis  is  placed  on                planning and examining the fulfillment of partial goals, developing employee skills and adequate                remuneration. Efficiency is usually rated by senior, subordinate, colleagues, but also to people                outside  the  organization,  for  example,  business  customers  or  citizens  with  whom  the  person                under review comes into contact.                                                                 123","Another method that is often used to evaluate efficiency is benchmarking. This method is                based  on  the systematic measurement  and  comparison  of selected  indicators  with  respect  to                other  reference  values,  which  may  be  either  historical  or  comparable  with  other  reference                entities  (eg  other  comparable  departments  or  comparable  organizations).  Currently,                benchmarking  in  public  sector  is  used,  for  example,  to  evaluate  the  efficiency  of  building                management, health care etc. [2, 6, 8, 9] Benchmarking is a major benefit to the public sector due                to the fact that it brings elements of market competition to the public sector. [15,17,19]                      The Data envelopment analysis (DEA) method is used to evaluate the technical efficiency                of production units based on the size of inputs and outputs. DEA models are based on the Farrel                model for measuring the efficiency of single-input and single-output units. Assessed units may                be  businesses,  but also hospitals, schools,  offices. [5]  However,  this method  is  practically  not                used in public administration. [11]                  3  Methodology                       The aim of this paper is to answer the question of which of the above-mentioned methods                the public employees evaluate as the most preferred one or the \"best one\", and which method is,                therefore, most preferred by them. Such a finding can then completely change the general idea of                the most appropriate method that can be measured by efficiency and then consider whether                efficiency measurement is efficient if the public administration staff does not identify with the                chosen method and tends to not work consistently. In this case, measuring efficiency could not                be done efficiently.                      The answer to the above-mentioned research question is found on the basis of data from                the  questionnaire  survey  (a  deliberate  and  purposeful  selection  of  respondents  based  on                availability and voluntariness) conducted in the 4Q 2018, using research methods based on the                logic principles, ie analysis - synthesis, induction - deduction.                      Firstly, the structured interview method was used to create the questionnaire. It helped                identify  the  most  important  criteria  that  affect  the  efficiency  assessing  process  -  simplicity                intelligibility  of  the  method,  time-requirements,  financial  requirements,  ease  of  data  and                information collection, objectivity, and comparability and the possibilities of overall use in their                organization.  Subsequently,  the  questionnaire  was  sent  to  the  relevant  representatives                (especially auditors and economic experts) of all regions and approximately 80 municipalities                within the Czech Republic, which are involved in the benchmarking project, with a request to                evaluate the weights of individual criteria and to evaluate specific methods according to these                criteria. For the evaluation, the rating scale from 1 to 6 has been used, where 1 was the worst                and 6 best. Subsequently, these values were recalculated on a percentage scale, where 1 rated                0%  and  6  rated  100%.  Finally,  the  responses  were  processed  in  MS  Excel  and  the  basic                characteristics were calculated in the IBM SPSS Statistics software. Subsequently, the Criterium                Decision Plus program was used for overall managerial comparison.                  4  Results                 4.1 Characteristics of respondents                      A total of 161 respondents (106 women and 55 men) of 10 Czech regions and the capital                city  of  Prague  participated  in  the  questionnaire  survey.  They  were  mainly  employees  of                municipality  offices  (69.6%)  and  regional  offices  (14.9%).  Other  employees  worked  in                government administration bodies.                      The  biggest  share  (55%)  of  employees  was  46-64  years  old.  It  was  due  to  the                predominance  of  these  employees  in  both  senior  positions  (management)  and  public                administration in general. The reason for this is the remuneration of employees, which depends,                among other things, on the length of the work experience (increasing the length of the work                experience increases the tariff wage). Young employees in public administration do not work in                proportion to older people, and they do not have a significant influence on executive decision-                                                              124","making.  This  is  related  to  the  length  of  respondents'  work  experience,  while  29  employees                (18%) work in the public administration less than 3 years, 71 employees (44.1%) work there                more than 16 years.                      Another identifying feature was education. As the questionnaire was designed for more                qualified  employees,  the  share  of  university  educated  employees  is  a  significant  majority                (80.8%),  as  expected.  Other  employees  have  either  secondary  education  (17.4%)  or  higher                vocational education (1.8%). For more educated employees, they are also generally more likely                to hold managerial positions. A total of 73 (45.3%) of respondents held a leading position. 67                (91.8%) from these managers were university graduates. These managers mostly (69.9%) had                up to 50 directly and indirectly subordinates.                      In general, it can also be stated on the basis of the responses that the target group (public                administration  employees,  who  have  the  possibility  to  influence  the  measurement  of                performance  and  efficiency)  participated  in  the  questionnaire.  The  respondents  are  mainly                managers with a higher length of work experience, and it can be assumed that the given issue is                not strange for them.                 1.1  Criteria evaluation                      Specific  methods  of  measuring  efficiency  may  be  very  different,  so  respondents  firstly                evaluated  significant  of  the  performance  criteria  (simplicity  and  intelligibility,  introduction                speed, implementation speed, financial requirements, ease of data and information collection,                objectivity, and comparability). The highest importance was attributed by the respondents to                objectivity (5.39 points, i.e. 87.8%) and to simplicity and intelligibility (5.24 points, i.e. 84.8%).                On the contrary, time requirements (introduction and implementation speed) have the lowest                importance (3.99 points, i.e. 59.8%, or 4.40, i.e. 68.0%).                       Table 1: Criteria preferences evaluation - men, women, and managerial positions (yes / no) (%)                                                                          Ease of data                           Simplicity   Introduction   Implementa-  Financial   and               Comparabili-                           and intelligi-  speed   tion speed   requirements   information   Objectivity   ty                           bility                                                                          collection                 Men             80.8        62.2        61.8        75.2        78.2        87.2        78.6                       No        62.8        64.2        57.2        80.0        65.8        91.4        68.6                       Yes       86.8        61.4        63.4        73.6        82.4        85.8        82.0                 Women           86.8        58.4        71.2        74.4        84.4        88.2        82.4                       No        87.0        57.8        71.0        74.8        84.4        89.2        82.8                       Yes       86.2        60.0        71.2        73.2        84.4        85.6        81.8                 Total           84.8        59.8        68.0        74.6        82.2        87.8        81.2                Source: Authors.                       However,  not  all  employees  evaluate  the  criteria  alike.  Based  on  the  chi-square  test                goodness of fit (for a level of significance alpha = 0.05) it can be stated that the difference in the                evaluation of the simplicity and ease of data and information collection in the men who hold the                managerial position and those who are not managers is statistically significant. Managers attach                greater importance to simplicity, which may indicate some disbelief to their subordinates and                their ability to understand the method. On the other hand, there is no statistically significant                difference between women and men.                      In general, simplicity and objectivity are most important for most of the employees. On the                other  hand,  financial  and  time  requirements  (e.g.  staff  training  costs,  the  time  needed  to                determine competencies, etc.) do not play such an important role, but the differences are not too                large between the criteria. This means that all the criteria are important in the end.                 1.2  Efficiency measurement methods evaluation                      From the point of view of the aggregate results of the evaluation of specific methods used                to measure efficiency, the differences among different groups (gender, age, education, length of                                                               125","practice, regions, managerial positions, etc.) were not significantly different. The following table                shows the evaluation of the individual methods according to the specified criteria:                               Table 2: Evaluation of the efficiency measuring methods – men, women (%)                                                                        Ease of data                                  Simplicity and   Time    Financial    and                                                                                     Objectivity   Comparability                                  intelligibility   requirements   requirements   information                                                                        collection                 Rating scale                      Men                77.0         56.2        69.4         62.2         51.6         47.2                      Women              84.0         55.2        61.6         59.6         48.0         50.0                      Total              81.6         55.6        64.2         60.4         49.2         49.0                 Management by objectives                      Men                60.4         53.0        52.6         46.6         61.4         53.8                      Women              62.8         49.2        50.4         48.2         58.0         52.6                      Total              62.0         50.6        51.2         47.6         59.2         53.0                 Key performance indicators                      Men                61.4         43.0        49.2         43.2         63.6         61.4                      Women              66.4         55.4        56.2         50.8         63.0         60.8                      Total              64.8         51.2        53.8         48.2         63.2         61.0                 Person-to-person method                      Men                72.8         43.8        51.2         41.8         43.6         51.2                      Women              83.2         41.6        50.6         36.8         49.0         45.6                      Total              79.6         42.4        50.8         38.6         47.2         47.6                 Benchmarking                      Men                73.8         54.6        55.8         48.8         62.6         61.4                      Women              70.6         46.2        55.6         44.0         63.0         65.0                      Total              71.6         49.0        55.6         45.6         62.8         63.8                 Balance scorecard                      Men                39.0         32.0        33.8         31.0         68.0         56.8                      Women              47.0         29.8        33.4         30.6         61.2         54.6                      Total              44.2         30.6        33.4         30.6         63.4         55.2                 Data envelopment analysis                      Men                33.4         32.0        36.8         29.4         61.0         53.4                      Women              42.2         27.2        30.4         29.8         57.0         49.0                      Total              39.2         28.8        32.6         29.6         58.4         50.6                Source: Authors.                       Generally,  the  simpler  methods  (rating  scale,  person-to-person  method  and                benchmarking) were considered by all respondents as intelligible and not financially and time-                consuming.  Contrarily,  the  use  of  key  performance  indicators,  balanced  scorecard,  and  data                envelopment  analysis  are  seen  as  relatively  complex  and  costly.  On  the  other  hand,  these                methods are mostly seen as objective and comparable, unlike the rating scale.                      However,  in  partial  responses,  it  was  possible  to  identify  interesting  differences.  For                example,  the  balanced  scorecard  method  was  rated  by  young  men  (under  26  years  old)  as                relatively  simple  (4.00  points,  i.e.  60.0%),  but  not  very  appropriate  in  terms  of  time                requirements (3.50 points, i.e. 50%). Such a combination may mean that these people know the                method,  and,  for  example,  they  have  encountered  it  during  their  studies,  but  they  see  it  as                impracticable  in  their  surroundings.  Additionally,  some  partial  responses  show  a  difference                between age groups, employees under 26 years old, and over 46 years old rated methods more                extreme than those from 27 to 45 years old, which mostly correspond to their average. This may                be  seen  in  the  key  performance  indicators  from  the  point  of  view  of  comparability.  Older                employees  evaluate  this  method  equally  worse,  and  on  the  other  hand,  younger  employees                better.                                                                126","After taking into consideration the weights of the individual criteria, a decision tree was                compiled in the decision support system. A comparison of the individual methods was made, in                Figure 1 there are five methods that have been evaluated as the most preferred:                                         Figure 1: Contribution to the most preferred method                                 Source: Authors.                      The most preferred method is the rating scale, despite the fact that it is seen as one of the                least objective and comparable method. However, in terms of other criteria (simplicity, ease of                data and information collection and financial and time requirements), it is evaluated as the most                appropriate  and  according  to  the  results  of  the  comparison,  approximately  56%  fulfills  the                characteristics of the ideal method that can be used for the efficiency evaluation. An alternative                to  this method  is  benchmarking,  which  is  characterized  by  a  high  level  of  comparability  and                objectivity,  but  not  by  such  simplicity  of  data  collection  or  time  requirements.  Similarly,  key                performance indicators were evaluated as appropriate of about 53%. The difference between                these  three  methods  is  relatively  small.  Conversely,  the  balanced  scorecard  and  data                envelopment  analysis  methods  were  found  to  be  less  appropriate.  Although  most  employees                consider it to be more objective than the rating scale, they are also considered as very complex                and  in  the  public administration  almost imperceptible, despite  the  fact  that,  for  example,  the                balanced scorecard method uses a set of performance indicators.                 1.3  Sensitivity analysis                      In  order  to  determine  whether  the  ranking  of  selected  efficiency  evaluation  methods                would change significantly if criterion weight changed, a sensitivity analysis was also performed.                For the weighting of all criteria, except for objectivity and comparability, there were only minor                changes  in  the  order  of  most  preferred  methods,  and  the  rating  scale  method  was  still                recommended. However, with the criterion of objectivity and comparability, the result would                change with the weighting of these criteria (see Fig. 2).                                     Figure 2: Sensitivity to the most preferred method - objectivity                               Source: Authors.                                                                  127","If  the  overall  weight  of  this  criterion  of  18%  exceeds  25%  then  it  would  be  the  most                preferred  benchmarking  method.  Further  growth  would  increase  the  preference  of  other                methods - key performance indicators, management by objectives and finally balance scorecard.                The  balance  scorecard  method  would  become  the  most  appropriate  method  for  measuring                efficiency  in  public  administration  in  the  case  of  the  weighting  the  criterion  of  over  93%.                Similarly, even if the relevance of the comparability criterion would increase, in such a case, the                most preferred methods would be benchmarking, KPIs and balanced scorecard.                  5  Discussion and conclusion                       There are a big number of researches and practical uses of performance and efficiency                evaluation methods. Some of them evaluate efficiency by comparing performance indicators [e.g.                2, 6], or they use more advanced efficiency evaluation methods that require greater knowledge.                [5] Nowadays, however, public administrations are struggling with the lack of highly qualified                employees who are able to fully enforce and apply efficacy assessments across the organization.                The analysis of the Ministry of Interior shows that the most widely used way of measuring the                efficiency in the public administration in Europe is a way of using performance indicators. [11,                12] Effective research in the Czech Republic, for example, Bohatá et al., aimed at streamlining the                performance  of  public  policies  at  the  central,  regional  and  local  levels.  The  methodology                emphasizes  quality  management  and  is  based  on  the  Common  Assessment  Framework  CAF                (Common Assessment Framework). [11]                      The aim of this paper was to extend the field of performance and efficiency assessment in                public administration to the employees’ perspective. Based on the questionnaire survey, it was                examined  how  these  effective  staff  assessment  methods  are  viewed  by  these  employees  and                whether  and  how  they  identify  with  each  method.  The  results  of  the  survey  show  that                employees, regardless of gender, age, education or length of practice, prefer the simpler methods                more than more complex. For example, methods based on performance indicators, which, unlike                rating scales or interviews, have a higher potential in terms of objectivity, comparability, and                simplicity,  unlike  the  DEA  method,  which  most  employees  reject  because  of  their                complicatedness.                      A possible limitation of this finding is the fact that respondents have a hypothetical view of                the issue of efficiency assessment, not the real state. The greatest preference may to some extent                reflect  resistance  to  change  and  learning  new  things  that  could  increase  efficiency  in  public                administration. On the other hand, the issue of introducing management methods and methods                of  efficiency  assessment,  which  are  used  in  the  private  sector,  has  not  yet  met  in  the  public                administration  with  a  warm  reception. The  New Public Management  period  was  followed  by                a Good  Governance  era  that  leaves  a  very  free  interpretation  of  efficiency.  Against  this                background, there is no other way than to encourage managers in public administration to see                what they see as appropriate and forward-looking, thereby enabling them to improve efficiency                in ways that are more useful in practice but also emphasize non-financial factors.                   Acknowledgements                       This  study  is  supported  by  internal  research  project  No.  2103  Investment  evaluation                within  concept  Industry  4.0  at  Faculty  of  Informatics  and  Management,  University  of  Hradec                Kralove, Czech Republic.                                                                          128","References                [1.]  BOHATÁ, M. et al. 2017. [online] Metodika hodnocení společenské efektivnosti institucí vykonávajících                     veřejné politiky Available on https://tacr.cz/dokums_raw/metodiky/TD03000258_metodika.pdf                [2.]  CHEN, Y. at al. 2017. Resilient regional energy benchmarking of classified public buildings. Energy                     Procedia; 142(December 2017): 2365-2370.                [3.]  DRUCKER, P. 2010. The Practice of Management, New York USA: Harper Collins.                [4.]  DRUGOV, M. 2010. Competition in bureaucracy and corruption. 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European Journal of Political Economy; 51(January 2018): 57-68.                                                                  129","Evaluation of the Service Quality in Public Hospitals                         from the Patient’s Perspective – the Case of Albania                                                             a                                                                              b                                            KURTI Sllavka ; DOLLANI Petrit                                                   University of Tirana, Albania                                     a                             b                                      sllavkakurti@fakultetiekonomise.edu.al;  petrit.dollani@unitir.edu.al                Abstract                 Patient's outlook and opinions need to be taken increasingly into consideration, because they are the ones                who consume the services and are therefore provided with more valuable information on the manner and                quality of the services being offered. For this reason, the assessment of patient opinion on the general                aspects of hospital care, collected during hospital stay, could provide an opportunity to identify potential                areas where patients are satisfied or  dissatisfied, as well as to present a general  picture regarding  the                quality of services provided by the hospital, in order to take appropriate action to improve them. The aim                of this paper is to present a set of perceptions about the quality of health services that patients receive                during their hospitalization in public hospitals in Albania, focusing particularly on two research questions                or  topics,  general  satisfaction  with  hospital  services  and  the  rating  of  hospital  health  services  though                patient  perceptions.  Methodologically,  this  paper  is  initially  based  on  primary  research,  most  notably                through the SERVPERF method, where the quality of hospital services is evaluated through measuring 5                component dimensions: Tangible, Reliability, Responsiveness, Assurance, and Empathy. The instrument                used was a questionnaire, answered by 115 patients hospitalized at the regional hospital in Durres City,                one of the largest hospitals in Albania. The data collected were processed and aggregated to conclude in                the overall assessment of the quality of hospital services from the patient point of view with regard to                responsiveness (best evaluated), followed by assurance, reliability, empathy and tangible elements.                 Keywords: Healthcare; public hospital; service quality; SERVPERF                JEL Classification: I10                    1  Introduction                       Historically,  setting  standards  of  quality  in  healthcare  facilities  has  been  delegated  to                medical  professionals  and  not  casually  the  quality  has  been  determined  by  clinicians,  whose                focus was technical aspect of providing care, where cure or improvement of the health condition                is one of the basic expectations of the health service [4]. In our opinion, quality in healthcare                organizations can not be claimed simply and only by inspecting whether the technical quality                standards are met or not. Improvement requires the implementation of a total quality culture                that should include supporting staff, medical staff, managers / administrators, policy makers and                especially  patients.  According  to  the  recent  literature,  patients  provide  valuable  and  unique                information  on  the  quality  of  care  [26],  as  it  is  even  believed  that  the  main  indicator  of                healthcare is the patient's satisfaction with the quality of the health service and not the health                status.  Nowadays  healthcare  organizations  should  constantly  make  attempts  to  identify  the                needs  and  expectations  of  patients  and  then  provide  services  according  to  them  [2].  The                evaluation of hospitals’ services quality, from the patient point of view, is not a new topic for the                development countries, but in Albania the studies in this area are very rare, and conducted only                during the last 5-6 years. In general, there is a lack of research on this field, focused on Albanian                healthcare organisations and especially on hospitals, most of which are public. This emphasize                the need  for further research or studies on perceived hospital services quality in our country,                that  adhere  to  be  part  of  European  Union  and  the  fulfilment  of  the  quality  standards  is  an                obvious priority.                                                                   130","2   Literature review                       Service quality perception wildly has been in the focus of many studies from the last three                decades. Because of the services quality special nature, which is intangible, simultaneous, and                heterogeneous, researchers have been making constant efforts in defining the concept, as well as                in  evaluating effective measurement methods. Still  nowadays  there  is  no  agreement  between                them,  and  they  are  far  from  a  consensus,  about  a  universal  model  and  assessment  methods.                However, almost all the researcher agree on the fact that service quality is a cognitive construct                [10].                      Service  quality  is  defined  as  an  assessment  of  customer,  from  the  overall  excellence  of                service  [28],  as  the  difference  between  customer  expectation  and  their  perception  about  the                service experience [21], where quality is satisfactory, if performance meets with expectations                [14].  The  importance  of  healthcare  quality  cannot  be  underestimated,  since  quality  of  a                healthcare service is whatever the patient perceives it to be [11].                      Service  quality  can  determine  the  degree  of  competitiveness  among  healthcare                organizations. Therefore,  it  is  very important for hospitals  to  assess  what patients  value  and                how  they  perceive  the  quality  of  care,  to  assess and  improve  the  usefulness  of  their  medical                practices and procedures [23]. Different studies have evaluated the link between service quality                with  patient  satisfaction  [8]  [16]  [17]  [18]  [25],  with  the  hospital  operational  measure  of                utilization [18], with hospital financial performance [12] [9] [18], with the level of loyalty and                recommendation to others or positive word-of-mouth endorsements [1], and it influence on the                patient’s health [10]. Service quality assessment enables hospital administrators to recognize                quality deficiencies perceived by patients and enhances the efficiency and quality of services to                exceed expectations and reach patient satisfaction.                      Increasingly,  in  the  environments  of  healthcare  organizations  is  widely  accepted  the                approach,  that  the  implementation  of  the  overall  quality  can  be  achieved  through  two  main                moments. First, the quality assessment should be evaluated from the point of view of \"relevant                associates\"  (including  not  only  providers  of  care,  funders,  policy  makers  and  health                administrators, but also users) and secondly based on explicit criteria, that among others reflect                the  core  values  of  a  society.  In  an  effort  to  evaluate  the  quality  of  services,  marketers  have                developed nineteen models during the 1984-2003 period [24]. These models essentially have a                key purpose - to highlight service quality components, so that administrators or managers can                further improve them.                      The quality of services in the health sector is divided into two main components: technical                and  functional  [13]  [20].  Technical  quality  (clinical  quality)  refers  to  characteristics,  such  as                education,  training,  staff diagnosis  skills,  their experiences,  etc.  Meanwhile,  functional  quality                refers to the way of providing services to patients (eg. behavior of the staff, communication of                doctors  and  nurses  towards  patients,  cleanliness  of  facilities,  quality  of  hospital  food,  etc).                Because  most  patients  do  not  have  the  opportunity  to  make  an  accurate  assessment  of  the                technical attributes, patient-centered quality measurement models, focus more on the functional                qualities perceived by the patient, to reach an assessment of health services [3]. The literature                has increasingly emphasized the importance of the patient's perspective, and many researchers                strongly believe that the quality of health care needs to be studied from the patient's point of                view [5] [27]; considering it as an important indicator of quality in health care services [6] [19].                      The SERVQUAL quality service is one of the most important models. This method is based                on  the  assumption  that  quality  of  service  is  a  function  of  the  differences  between  customer                expectations and perceptions that it has for these elements. It focuses on five quality dimensions                - the model is the result of some research projects of Parasuraman et al,. [20] [21] [22]. Initially,                the  model  was  based  on  10  quality  service  dimensions,  which  were  later  reduced  to  5                dimensions.  This  model  focuses  on  the  differences  between  patient  expectations  and                perceptions for each of the 5 dimensions of quality. Although a widely used method of quality                assessment in various industries, the criticisms related to it were numerous, particularly with                regard to the large number of questions, difficulties of administration, data replenishment, etc.,                [6] [7]. From literature review, it appears that this model has been used in many researches in                                                               131","some service industries, and its has been applied also in several different countries around the                world.                   3  Materials and Methods                       Primary quantitative data were collected through a questionnaire, designed according to                the SERVPERF method [6]. First part asks for general information on sociodemographic data i.e.                age  and  gender.  The  second  part  consists  of  five  sections,  aimed  at  measuring  the  perceived                quality of the patients with a total of 23 questions. Likert scale was used, from 1 (unacceptable)                to  5  (fully  agree).  This  section  has  five  dimensions,  first  measures  the  quality  of  tangible                elements  and  consists  of  six  statements.  The  second  dimension  relates  to  the  elements  of                seriousness and consists of five statements. Third dimension is about readiness and response,                and is made up of four statements. The fourth dimension has five statements and is dedicated to                elements  related  to  security  and  trust.  The  last  dimension  has  three  questions  and  assesses                empathy or sensitivity.                      Study  included  115  patients,  who  received  health  services  at  the  Regional  Hospital  in                Durres  (Albania).  The  main  condition  for  participation  was  the  age  of  patient  (over  18)  and                staying for treatment at the hospital minimum one night. Questionnaires were filled by patients                themselves, or by a relative of patient, who has stayed with him, attending the service for at least                one night. Only pediatric department was excluded from the study.                   4  Results and Discussion                       Actually, the Albanian health system is mainly public and the state is the main provider of                the  most  of  the  health  care  services  offered  to  the  population  as  in  the  field  of  promotion,                prevention,  diagnosis  and  treatment.  According  to  the  Albanian  Ministry  of  Health,  public                healthcare spending in 2016 reached $355 million. Albanians spend approximately 6.8 % of GDP                on  healthcare,  583  euro  per  capita  [29],  divided  almost  evenly  between  public  and  private                services. Most of the hospitals in Albania are public, categorized according to legislation (Law                No. 9106, dated 17.07.2003, On Hospital Service in the Republic of Albania, amended) in daily                hospitals; b) hospitals at the municipal level; c) regional hospitals; d) tertiary hospitals. The first                private hospital in Albania was founded in 2007, but the number has grown and today there are                11  private  hospitals in  the country, mainly  concentrated  in Tirana.   Meanwhile,  there  are  45                public hospitals located in different cities in Albania.                      This  survey  was  conducted  with  the  patients  of  the  Durres  regional  Hospital,  with  a                capacity of 340 beds - the second largest regional hospital in Albania. It is a state-run healthcare                institution  with  an  independent,  non-profit  budget.  The  Health  Insurance  Institute  (HII)                concludes a contract with the hospital in Durres, which defines the methods of data retention,                the  calculation  of  expenses,  the  procedures  for  their  submission,  the  payments  and                reimbursements, according to the methods approved by both parties. This is the first case of                such financing of a public hospital In Albania, where all the costs of the hospital are carried out                by the HII, while resource allocation is managed by the board of hospital itself. With the release                of the financial result, the hospital represented by the Administrative Board, has the right to                propose to the HII changes in the payroll system, representing this way a lot of challenges or                defiance for its administrators, where the patient centered strategy should be on focus.                      The  main  purpose  of  the  study  consists  on  assessment  of  the  general  satisfaction  with                hospital  services  in  Durres  Hospital,  as  one  of  the  largest  in  Albania.  The  second  purpose                consists on rating of hospital health services, based on patient perceptions through five quality                dimensions, deriving from SERVPERF method.                      The  first  dimension  measures  the  quality  of  tangible  elements  and  consists  of  six                statements,  such  as  general  conditions  of  hospital  settings,  equipment,  auxiliary  materials,                cleanliness of premises, personnel appearance. The second dimension relates to the elements of                seriousness, and consists of 5 statements, such as: the hospital does the right thing in the first                                                               132","attempt to provide the services, offers them at the time it has promised, insists on keeping and                processing accurate, error-free data.                      The third dimension is about readiness and response, and is made up of 4 statements, such                as: quick delivery of the service, timely response to patient requirements, staff is always ready to                assist  the  patient,  etc.  The  fourth  dimension  has  5  statements  and  is  dedicated  to  elements                related to security and trust, and contains:  the preparation and possession of appropriate staff                knowledge, staffing, security of the patients from the services received, etc. The sixth dimension                has 3 questions and assesses empathy or sensitivity, where assertions tend to focus on giving                individual attention to patients by the staff or the hospital as a whole.                 4.1 Age and Gender                      Regarding the age of the patients involved in the study, from the questionnaire analysis it                is noted that 17% of them are of 18-30 years of age, 25% of them belong to 30-45 age group,                31% of respondents are aged 45-60 (this is the dominat group) and 27% of the age over 60                years. Likewise, most of patients are males: 53%, compared to women who accounted for 47%                of total.                 4.2 Evaluation of Hospital Services Based on Quality Dimensions                      Here follows the discussion of data regarding the quality components, according to Cronin                and Taylor. More specifically, graphical data will be presented regarding the assessment that                hospitalized  patients  in  different  pavilions  at  the  Durres  Hospital  have  done  for  hospital                services, focusing on each constituent statement of each of the 5 dimensions.                 4.2.1 Tangible elements                      As seen from the Fig. 1, the constituent elements of the first dimension, which are related                to the tangible elements, have a rating of 2.5 (from the maximum of 5). The general conditions of                the hospital premises have the highest rating for this dimension. It appears from this result that                the hospital offers somewhat good conditions, but there are still no attractive premises. In the                hospital  it  appears  that  even  the  materials  related  to  the  service  are  not  entirely  visually                appealing.  Estimates  for  these  two  elements  are  the  lowest  compared  to  others,  respectively                2.5353 and 2.5647 points.                                  Figure 1: Evaluation of First Dimension Elements - Tangible Elements                                Note: P.1 - General conditions of hospital facilities. P.2 - The hospital has modern attitudes. P.3 - The facilities in hospitals                are visually appealing. P.4 - The materials related to the service are visually appealing. P.5 - Cleanliness of premises,                floors, toilets, etc. P.6 - The hospital staff has correct appearance.                Source: Authors.                                                                         133","4.2.2 Reliability                      The  Fig.  2  depicts  the  situation  in  hospital  according  to  patient  perceptions  about  the                elements of reliability, as another component of quality. Similarly as in the first component, all                the elements are valued above the average 2.5, and in some cases even with a few points above                it. The lowest average, with 2.5859 for this component, is related to the hospital's claim to do the                right thing in the first attempt. As it is noticed, the hospital in the patients' view seems to be                trying  to  accomplish  the  right  things  from  the  first  time,  but  does  not  always  realize  that                objective.                                   Figure 2: Evaluation of Elements of Second Dimension – Reliability                               Note: P.7 - The hospital promises to do something at a certain time and it does so. P.8 - The hospital offers its services at                the time / schedule it is promised to do. P.9 - When you have a problem, the hospital shows a sincere interest in solving it.                P.10 - The hospital insists on maintaining, processing, and disseminating accurate and error-free data. P.11 - The hospital                does the right thing with the first time / attempt.                Source: Authors.                       The medically superior element, with 2.9868, is related to the sincere interest shown by                the hospital in solving the patient's problems, as perceived by the patients involved in the study,                seems to be relatively high. As seen from the analysis of the responses, the element of time has a                special attention on the part of the hospital. This is because a considerable part of the patients                who participated in the study thinks that the services are mainly offered at certain times and                when  the  hospital  promises  to  do  something  at  a  certain  time  it  does  so.  This  is  further                strengthened since both assertions have a focus on time, they are estimated almost the same                average  rating  of  2.79  out  of  5  possible.  Apparently,  the  least  appreciated  element  by  the                patients involved in the study is the fact that the hospital fails to make the right thing with the                first attempt.                  4.2.3 Responsiveness                      The  third  quality  dimension  consists  of  questions  that  tend  to  reflect  reality  about  the                responsiveness shown by hospital staff (Fig. 3). All elements in this component are rated at an                average of over 3 points out of 5, which means that this element is appreciated by the patients                when they evaluate the quality of the services received, while staying in the hospital. The most                valued element of this dimension, with a high average of 3.3976, is related to the high readiness                shown by staff to help patients in need. The other two elements, also valued by patients with                small differences between them, are also focused on time. More specifically, they estimate that                the  staff  in  most  cases  knows  and  precisely  states  when  the  necessary  services  will  be                performed, estimated at 3.1958, as well as evaluating the staff's ability to respond in a timely                manner to patient requests 3.1847. However, the element with the lowest average estimate in                this  dimension,  but  with  small  difference  from  the  other  claims,  with  3.0588  is  the  quick                delivery.  Given  the  estimates  of  readiness-related  assertions, staff seems  to  do  the maximum                effort, but other conditions and factors seem to have an impact on the failure to provide services                in every case.                                                                 134","Figure 3: Evaluation of Elements of Third Dimension – Responsiveness                              P.15                                                                         3.1847                            P.14                                                                                             3.3976                           P.13                                                            3.0588                           P.12                                                                          3.1958                               2.8       2.9        3        3.1       3.2       3.3       3.4                 Note: P.12 - The staff tells you exactly when the necessary services will be conducted. P.13 - Staff provides services quickly.                P.14 - Personnel is always ready to help. P.15 - Staff responds to your requests.                Source: Authors.                  4.2.4 Assurance                      Fig. 4 illustrates the situation with respect to the fourth quality dimension - assurance, and                the beliefs perceiving the patients during their stay in the hospital. It seems that this component                generally  has  a  considerably  overarching  estimate,  where  all  the  elements  have  an  average                rating.  The  element  that  has  the  highest  rating  in  this  dimension,  with  3.2237  relates  to  the                hospital staff courtesy, followed by confidence, with a significant positive estimate of 3.1015.                The lowest average in this dimension: 2.7827, is the assertion about safety that patients feel                from hospital services. The assertion with the appropriate medical staff's knowledge to respond                to the variety of patients' questions as well as the assertion that the skills and knowledge of the                staff relate to the patient, are evaluated by patients respectively with 2.8795 and 2.951 points                out of 5 possible. These values demonstrate that patients appreciate the courtesy of the medical                staff and generally have confidence in the skills of the medical staff in this hospital.                                  Figure 4: Evaluation of Elements of Fourth Dimension – Assurance                            P.20                                                                2.8975                        P.19                                                                                           3.2237                        P.18                                                      2.7827                        P.17                                                                                 3.1015                        P.16                                                                    2.951                            2.5      2.6     2.7     2.8     2.9      3       3.1     3.2     3.3                 Note: P.16 - Preparing and mastering the expert medical knowledge about your treatment creates confidence in you. P.17                - Personnel brings confidence to you. P.18 - You feel safe with the services you receive from the hospital. P.19 - Hospital                staff is constantly courteous with you. P.20 - Hospital staff has the right knowledge to answer all your questions.                Source: Authors.                 4.2.5 Empathy                      The  fifth  quality  dimension  consists  of  three  questions,  which  tend  to  assess  the                perception of patients on empathy and sensitivity during hospital stay (Fig. 5). Even in this case,                all the elements are valued above the average of 2.5 and converge at similar level. The element                with highest average: 2.876 relates to the individual attention, that staff provides to the patients.                                                                135","Approximately, at the same level, the second element evaluated by patients with 2.876 concerns                the provision of services on an appropriate time schedule. The lowest average rating for this                dimension:  2.752,  is  the  assertion  that  the  hospital  in  general  has  toward  each  patient.  The                patients hospitalized estimate with considerable scores the staff attention demonstrated to them                as patients.                                    Figure 5: Evaluation of Elements of Fourth Dimension – Empathy                                      Note: P.21 - The hospital staff gives you individual attention. P.22 - The hospital   has individual attention to every                patient. P.23 - The service timetable delivery is suitable.                Source: Authors.                 4.3 The evaluation of Durres hospital service quality                      After the compilation of all answers to presents questions (Fig. 6), one could notice that                the patients receiving health service during the stay in this hospital generally evaluated them as                acceptable with an average rating of 2.8978 points out from 5. As seen from the graph above,                each  of  the  five  quality  dimensions  was  rated  aggregately  above  the  average  2.5  points.  The                more estimated dimension is that of responsiveness with an average rating of 3.21 points out of                5  possible.  It  is  followed  by  assurance  dimension  rated  at  2.99.  Empathy  and  reliability  are                estimated almost the same, with small differences, respectively 2.81 and 2.80. It should be noted,                when  examining  all  dimensions  in  an  effort  to  evaluate  the  quality,  that  there  is  a  positive                consideration and assessment that patients perceive from the part of hospital staff, especially                their attention to the patients, their behavior and efforts to help and meet patient requirements,                whenever possible. Patients, in the entirety of the quality of health care services received during                their hospitalization, seem to estimate the tangibles as poorest with 2.67 points.                      The tangibles weighted as one of the lowest quality dimensions by the patients, it is not                new for these hospitals, even in another study conducted in the same hospital in 2015, patients                rank tangibles as the last, with lowest scores, of five quality dimensions [15]. Elements of this                dimension relate mainly to infrastructure, through which the hospital carries out its health care                activity to the patients and apparently, no evident improvement is made by hospital.                                                                                 136","Figure 6: Evaluation of Quality Dimensions                                   Source: Authors.                      On the other hand, it is worth to emphasize that another research revealed that patient                hospitalized in public hospital in Albania, evaluate tangible dimension as an important factor                positively correlated with the satisfaction with the service quality [16]. This highlights the fact                that  hospital  management  should  consider  and  demonstrate  a  serious  engagement  on                investments to better conditions, refinement equipment’s, facilities and cleanliness. If there is a                will to increase the general visual image of the hospital more investments are needed, in order                to improve them and their maintenance.                  5  Conclusion                       One of the easiest ways to improve the service quality in healthcare centres is to know and                use the patient knowledge regarding the healthcare facilities [28]. The elaborated results of this                research made it possible to present a general view out of the quality assessment of the health                services  that  patients  received  in  public  hospitals,  to  further  undertake  a  more  detailed                assessment of the five dimensions of quality of the services provided in the methodology. The                patients receiving health service during the stay in Durres hospital generally evaluated them as                acceptable  with  an  average  rating  of  2.8978  points  out  from  5.  Concluding  the  analysis,  it  is                evident that from the point of view of patients, the most valued elements are the responsiveness                and assurance, followed by reliability, empathy and as the last one are considered the tangible                elements.  It  is  worth  emphasizing  that  besides  the  value  that  this  work  brings  through  the                theoretical review of the field literature, the reflection of the perceived reality of the patients on                the quality of hospital services, has a particularly practical value from a managerial perspective,                as the results of this the study might serve hospitals managers to evince those weaknesses of the                service and to further undertake those initiatives that serve as a starting point for improving the                future quality of service, thereby improving the overall performance of the hospital.                  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Available on:                     https://ec.europa.eu/health/sites/health/files/state/docs/2018_healthatglance_rep_en.pdf                                                                                                                                   139","How to Evaluate the Effectiveness of Science-policy Interface:                                           A Postmodernist Approach                                                     MICHÁLEK Tomáš                               Faculty of Social and Economic Sciences, Comenius University in Bratislava, Slovakia                                                  tomas.michalek@fses.uniba.sk                 Abstract                 The effectiveness of science-policy interface, and especially its evaluation, remains an elusive concept in                the  SPI  literature.  Many  authors  work  with  the  so-called  CRELE  model  which  connects  the  credibility,                relevance  and  legitimacy  but  they  fail  to  really  operationalize  this  model.  This  article  explores                postmodernist approaches via a conceptual analysis of the SPI theory. Building on a constructivist position                of postmodernism, the principal argument is that if the social constructions of roles are being similar, the                effectiveness of SPI will be higher than if the roles are constructed differently. We conceptualize the social                constructions of roles with a combination of values and processes on one side and scientific information,                actors, boundaries and boundary work on the other. The paper is focused on a theoretical discussion and                methodological framework development for a future research. First, we clarify why it is relevant to use a                postmodernist methodology. Then, we use it for a theory analysis of the SPI literature. In the conclusion,                we propose a set of indicators that could be tested in a future empirical research.                Keywords: science-policy interface; effectiveness; knowledge brokering; boundary work; postmodernism; social construction.                 JEL Classification: Z190                    1  Introduction                       The effectiveness of science-policy interface (SPI), and especially its evaluation, remains                an  elusive  concept in  the  SPI  literature.  Many  authors  work  with  the so-called  CRELE  model                which connects the credibility, relevance and legitimacy but they fail to really operationalize this                model. Other authors have their specific understandings of the effectiveness of SPI but it often                does  not  deal  with  possible  ways  of  its  evaluation.  This  article  wants  to  contribute  to  this                theoretical  discussion  with  its  own  approach  to  the  question  of  effectiveness  –  the  approach                based on postmodernism. Focusing on a conceptual analysis of the SPI theory, we would like to                find out what a postmodernist approach can bring to the study of the effectiveness of SPI and its                evaluation.                      Building on a constructivist position of postmodernism, the principal argument is that we                can  evaluate  the  effectiveness  of  SPI  by  better  understanding  and  comparing  the  social                constructions of roles of the involved actors, both on the science and policy side of the interface,                producers and users of the scientific information. The theory shows that it is not possible to                adequately define the concepts of credibility, relevance and legitimacy. It means different things                to different people. We argue that these different understandings are actually the only way how                to evaluate if a transfer of scientific information has been successful or not. It is not relevant to                find a clear definition of the credibility, relevance and legitimacy. It does not matter what they                are.  What  really  matters  is  how  the  involved  actors  understand  it  (values)  and  how  this                influences  their  actions  (processes),  in  our  case  –  how  their  understandings  of  values  and                processes improves or impedes on SPI. If their social constructions of roles are being similar, the                effectiveness of SPI will be higher than if the roles are constructed differently. The point is that                we cannot find more than this.                                                                     140","2  Methodology of postmodernism for the theory analysis of science-policy interface                       The analytical tool which is used for the conceptual analysis of the SPI theory are notions                of values and processes. A research question for the conceptual analysis of the SPI theory is what                kind of indicators of effectiveness can be extracted from the SPI theory by searching for notions                of values and processes which are the dominant categories in the postmodernist approach. The                main reason behind the decision to use postmodernism when trying to better understand the                effectiveness of SPI is its take on nature of reality, especially its emphasis on values (ontology)                and processes (epistemology). Ontology contemplates about the nature of reality which depends                on values. Epistemology tries to understand processes of getting to know the reality. It tries to                answer the question: How can we know the world? Which is also a crucial question for SPI: How                can policymakers know the world which is more and more relying on science, technology and                innovations?  And  how  these  processes  of  getting  to  know  the  world  can  be  effective?  Post-                modernism sees the world around us in a specific way. A belief that we can influence the world                with our knowledge is central not only to modernism, but positivism, empiricism and science as                such. But not for postmodernism which perceives our reality as a fluid phenomenon (processes)                which  is  also  different  depending  on  from  where  we  are  looking  (values).  This  ontological                position can  be  regarded  as  a  translation of  Einstein’s  theory  of  general relativity into social                sciences. We can never really grasp the reality given it is fluid in nature (processes). It is being                continually constructed and reconstructed. It is a process based on values – not unlike politics,                policymaking and SPI itself.                      Postmodernism is not very popular as for some authors it equals to academic speculation                and nihilism especially because of its emphasis on values and processes. Postmodernists are said                to try to deconstruct narratives but not to explain their relation to the topic. Postmodernists are                said to refuse a discipline of writing which they perceive as just another form of control. “To                deconstruct  conventional  wisdoms  is  one  thing,  to  state  that  we  can  function  without  any                conventions is quite another” [10]. For Parker [10], postmodernism has no practical use because                it  focuses  “only”  on  the  role  of  language  and  discourse  (values).  Meaning  is  never  stable                (processes). It does not make any sense to try to devise empirical tools to study the reality as it                would be just another part of our construction of the world and can never be used to find out the                objective reality [10].                      But  understanding  of  the  concepts  of  change  (processes)  and  chaos  (values)  plays  an                important role in our approach to SPI. For Chia [2], we construct the world around us and create                organizations  in  order  to  understand  it  and  make  it  more  predictable  and  less  chaotic;  e.g.                through a language which is broken into many parts using alphabet. Knowledge is often almost                “like a product or commodity that can be 'accumulated', 'stored' and 'transferred' in the form of                unique word-configurations that we call a theory” [2]. Therefore, deconstructing these concepts                and categories (values and processes) is at the core of postmodernism. The concepts are the                only reality there is. Postmodernism should be seen as an alternative style of thought. “Contrary                to the commonly held view, order and organization do not reflect the law of things but their                exception” [2]. And this should be especially important for policymakers as they can learn more                about underlying societal needs (values) and consequently better align them with their policies                (processes).                      A  further  step  is  done  by  Gergen  and  Thatchenkery  [5]  who  see  the  benefits  of                postmodernism  in  safeguarding  rigorous  research  methods  and  in  increasing  objective                knowledge  and  they  do  so  using  notions  of  values  and  processes.  “It  is  not  technological                capability (or “knowing how”) that is called into question by postmodern critique but the truth                claims placed upon the accompanying descriptions and explanations (the “knowing that”)” [5].                This is a big step from the Parker’s position who could not see any benefit of postmodernism for                methodology. Gergen \& Thatchenkery [5] stipulate that even though any methodology cannot be                used to prove something to be truth (question of values), it can answer to more practical needs                such  as  the  intersection  of  local  knowledge  and  social  action  (question  of  processes).  They                replace  rational  agency  (values  excluded)  with  communal  rationality  (values  included),                empirical  knowledge  (values  out)  with  social  construction  (values  in),  and  language  as                                                               141","representation  (no  processes)  with  language  as  action  (processes).  In  what  they  call  a                conceptualization  of  research,  Gergen  \&  Thatchenkery  [5]  maintain  that  the  constructivist                approach  brings  several  new  functions  and  forms  of  research,  such  as  technologies  of                sensitization,  innovative  practices  of  giving  more  voice  to  marginalized  groups  or  dialogic                methods  –  many  of  which  are  used  in  the  SPI  literature.  Given  critical  reflexivity  of                postmodernism,  organizations  should  also  assume  a  role  of  giving  cultural  explanations  and                forming cultural meanings (values) in order to explain existing modes of human activity and to                clarify who benefit from them (processes). In a globalized world, there is no single answer to any                problem (values), left alone the fact that a problem will evolve in time (processes). “The very                conception  of  a  science  in  the  postmodern  context  is  one  that  emphasizes  continuing                interchange, continuing reflection and transformation” [5].                      It is not a surprise that this postmodernist approach can be also traced in the theoretical                approaches dealing with the science-policy interface. It is, actually, a precondition for them as                they all deal with epistemological questions and reflexive methodologies. Using sciento-metrics                analyses,  Spruijt  et  al.  [13]  identified  five  clusters  of  authors  dealing  with  the  science-policy                interface: post-normal sciences, science and technology studies, science policy studies (Mode 2                Science), politics of expertise and risk governance authors. They all deal with high stakes and                epistemological  uncertainties  (values).  To  answer  them,  they  use  interdisciplinary  approach,                extended public and stakeholders’ participation and transparency mechanism (processes). They                long for more socially robust knowledge [8]. In line with postmodernism, they do not consider                language  to  be  a  neutral  medium  and  knowledge  to  be  always  objective  (values).  They  use                discourse  analysis  in  order  to  answer  the  questions  of  legitimacy  of  research,  especially                scientification  of  society  and  politicization  of  science  (processes).  Researchers  must                acknowledge  social  construction  and  hidden  normativity  of  knowledge.  Politics  of  expertise                deals with the power relationships between experts and policymakers. The authors study here                how  core  beliefs  of  experts  influence  their  policy  preferences  and  how  they  form  coalitions.                Therefore, values and processes are central to SPI and our understanding of its effectiveness.                      Epistemological  shift  from  modernism  to  postmodernism  resides  mostly  in  the                understanding of relativity (questions of values and processes). Continual changes (processes)                and local embeddedness (values) prevent any theory to be universally applicable. Modernism                tried  to  find  an  objective  reality  (values  and  processes  excluded),  postmodernism  tries  to                understand the social construction of reality (values and processes included). In doing so, it tries                to uncover implicit regime of values, which modernism took for granted, and processes where                these values interact.                  3  Findings and discussion of how values and processes are reflected in the theory of                    science-policy interface                       In the previous chapter, we have identified a set of criteria (or variables) against which we                can analyze the SPI literature when searching for the effectiveness and its possible indicators. In                doing so, we have analyzed the SPI theory by searching for notions of values and processes and                identified the following concepts:                 3.1 Scientific information                      When  analyzing  SPI,  many  authors  deal  with  the  notion  of  scientific  information  or                knowledge if you will. This comes as no surprise as scientific information is the raison d'être of                SPI. But the nature of this information is important to us when applying the variables of values                and processes. Policymakers often ask scientists to advise them (to provide them with scientific                information) on complex issues, such as biotechnology or artificial intelligence, where, however,                research cannot provide a profound advice given these issues are very recent and insufficiently                studied. Spruijt et al. [13] define these complex issues as “uncertain and potentially risky issues                that merit a transdisciplinary approach, which indicates that these risky issues are embedded in                wider environmental, social, economic and political systems” [13]. This definition includes both                                                               142","values and processes as described above. Even though the world around us, in a postmodernist                understanding,  is  permanently  being  constructed  and  reconstructed,  there  exists  a  natural                longing for stability and prediction of successful science-policy knowledge transfer, or in other                words, for an effective science-policy interface.                      The nature of scientific information as seen through values and processes is also reflected                in the CRELE attributes of credibility, relevance and legitimacy. Credibility is believability and                trustworthiness  of  the  scientific  information  to  an  end-user  (policymaker).  It  is  practically                secured by a scientific method that has been used. Heink et al. [6] did a conceptual analysis of                the CRELE attributes and concluded that they are good for reflection on the effectiveness but not                for  its  evaluation.  Based  on  an  empirical  semantic  analysis  of  the  relationship  between  the                CRELE attributes, they identified many ambiguities in the concept. Their main objection is that                personal dispositions are taken for granted (values). Credibility is what information is, how it is                produced and presented (processes) which is in a real world influenced by confirmation bias                (values) and availability heuristics [6]. Relevance or salience is a question of time, scope and                scale. “Information that is timely and informs decision makers about problems that are on their                agendas have high salience” [1]. Relevance depends on a user and context (values). Problematic                is  also  its  relation  to  novelty.  The  last  attribute  is  legitimacy  which  can  be  defined  as  “the                condition of being in accord with established principles” [6]. For Heink [6] legitimacy is maybe                the most ambiguous concept. It can be seen as acceptance (if it is accepted after a decision was                taken),  acceptability  (if  it  is  in  line  with  the  accepted  procedures)  or  justification  (if  it  is                politically right). All three attributes of CRELE are intersections of values and processes. Values                are often conceptually separated from knowledge yet knowledge is based on values. Is not any                evidence just a belief that something is a fact? Processes are, on the other hand, accepted as an                important attributes of credibility, relevance and legitimacy.                 3.2 Actors                      Actors  are  another  concept  in  SPI  greatly  involved  in  values  and  processes.  Actors  are                often described as experts. Spruijt et al. [13] identified several factors that influence the role of                an  expert,  namely  type  of  issue,  type  of  knowledge  of  the  expert,  core  values  of  the  expert,                organization  in  which  the  expert  works,  context,  and  changing  beliefs  of  experts.  For  them                values are dominant variable in understanding the role of experts. Cash et al. [1] link actors to                the  CRELE  attributes  differently.  Individuals  are  not  independent  actors.  “Actors  are  more                inclined to judge information as salient, credible, or legitimate when others already judge it as                such”  [1].  In  this  statement,  processes  play  a  more  important  role.  Processes  of  delivering                information  between  knowledge  producers  and  knowledge  users  by  proxy,  by  which  they                understand a scientific process, participants and also consensus. Spruijt et al. [13] argue that                there is a gap between theoretical approaches and empirical studies on expert roles. Similarly,                Dunn et al. [4] stipulates that the role of actors, networks and personal interrelationships is not                covered sufficiently in the literature.                      A  very  influential  work  about  the  self-understood  roles  in  SPI  is  the  book  The  Honest                Broker  by  Roger  Pielke,  Jr.  [11]  who  presents  four  ideal  types  of  experts’  engagement  in                policymaking. According to him, scientists can choose if they want to be pure scientists, science                arbiters,  issue  advocates  or  honest  brokers.  This  is  a  decision  based  on  values  which  directly                influences processes of delivering the scientific information to its audiences. Pielke assumes a                postmodernist approach as he understands the limits of human cognition (values). He vows for                institutionalization  of  science-policy  interface  as  a  way  to  circumvent  them  (processes).                “Because advocacy is often a default role and it is so seductive, there is a need to support the                institutionalization  of  mechanisms  of  science  arbitration  and  honest  brokering”  [11].  On  the                other hand, Pielke does not recognize knowledge brokers as a separate group. For him, scientists                engage in knowledge brokering on top of their main duties. For others, nevertheless, knowledge                brokers  are  unique  entities.  “Knowledge  brokers  are  people  or  organizations  that  move                knowledge around and create connections between researchers and their various audiences…                but  they  also  produce  a  new  kind  of  knowledge:  brokered  knowledge”  [9].  Given  its                interdisciplinary nature, knowledge brokers can be various entities, such as individual experts                                                              143","(e.g.  policy  entrepreneurs,  science  journalists)  or  organizations  (e.g.  academies  of  sciences,                technology transfer offices).                  3.3 Boundaries                      The next concept identified in SPI theory with values and processes are boundaries. For                Cash et al. [1], (values and processes) boundaries are “barriers and gaps in knowledge-action                systems  [which]  demarcate  the  socially  constructed  and  negotiated  borders  between  science                and policy, between disciplines, across nations, and across multiple levels” such as functional                activities,  political  jurisdictions  and  organizational  scales  [1].  They  identified  these  different                perceptions and points of emphasis in the analysis of water management in the U.S. Great Plains.                Language or jargon is an example of a barrier between such groups. Spruijt et al. [13] describe                also a “science-policy gap” which stems from different preferences (values) of policymakers and                scientists and which creates boundaries between them. Policymakers prefer certain solutions                while  scientists  can  offer  them  only  probable  explanations.  Science-policy  interface  should                bridge this gap, which is, however, often an uncertain exercise with an open end (processes).                      Boundaries are also created by institutions and organizations which are a translation of                values and processes into a set of formal and informal rules [1]. Dandridge, Mitroff \& Joyce [3]                studied the organizational culture and symbolism which refers to the symbols that the members                of an organization use when referring to feelings, images and values. These can be either stories                or myths, ceremonies or ritualized events, logo and anecdotes or jokes. According to the authors,                these are of the same importance as traditional topics such as reward systems, organizational                structures,  individual  use  of  power  etc.  From  the  perspective  of  symbolic  interpretivism,                Dandridge, Mitroff \& Joyce [3] see three main functions of symbols, namely in their capacity to                describe the system (values), to control the energy flow within it and to maintain the system and                its modifications (processes).                 3.4 Boundary work                      Boundary work, [7] boundary spanning, [12] or knowledge brokering [9] combine values                and processes in yet another concept. For Cash et al. [1], boundary work stands for balancing                trade-offs and working with tensions and complementarities. “What makes boundary crossing                difficult is that actors on different sides of a boundary perceive and value salience, credibility,                and legitimacy differently” [1]. Pülzl and Rametsteiner [12] identified two processes in boundary                spanning: transfer and transaction. Transfer is a linear process, transaction a collaborative one.                Dunn, Bos \& Brown, [4] who had studied Melbourne’s water sector, broke the linear process into                two  separate  processes  depending  on  its  initiator.  In  the  science-push  model,  the  agenda  of                research is set by scientists only, without any involvement of society. This model is in line with                positivist approach and methodology. The main motivation for research is to find knowledge,                not to apply it, which is somehow similar to the Pielke’s pure scientist. It is a linear process. This                model is considered to be outdated as it deals only with the supply of information, works with                fixed boundaries between science and policy and expects science to be neutral – in doing so it                overlooks “values, ethics, organizational culture, regulatory environment, resources, bargaining                and  entrenched  commitments”  [4].  In  the  policy-pull  model,  the  agenda  of  research  is  set  by                policymakers who commission scientists to research an issue and provide evidence for better                addressing a problem. It is also a linear process where knowledge is transferred directly from                scientists to policymakers. On the other hand, in the co-production model, an agenda of research                is  set  jointly  by  scientists  and  policymakers  with  involvement  of  stakeholders  and  citizens.                Research questions and methods are being defined in a continuous dialogue between them. This                model “requires mutual trust, respect, reciprocity, participation and commitment from all those                involved” [4].                      Cash et al. [1] combine the concepts of boundaries and boundary work in what they call                boundary  organizations  but,  interestingly,  they  stipulate  “that  is  often  individuals  who  have                legitimacy or credibility on both sides of a boundary that are especially useful in making this                bridge”  [1].  They  also  list  processes  that  any  boundary  work  should  include  (based  on  a                                                               144","combination  of  values  and  processes):  accountability,  use  of  boundary  objects,  participation,                mediation,  translation,  coordination  and  complementary  expertise.  Individuals  in  a  boundary                work are knowledge brokers who combine concepts of actors and boundary work.                      Within the identified concepts of scientific information, actors, boundaries and boundary                work, we can thus further identify possible indicators which can be tested in a future research.                These  indicators  are  listed  in  Table  1  below.  Based  on  the  postmodernist  methodology,  they                represent a combination of values and processes used to identify the core concepts in the SPI                theory. An indicator either combines both notions of values and processes or relates to only one                of them. Sometimes, however, the line between these two categories is blurred.                                                  Table 1: Identified indicators                         Scientific information   Actors          Boundaries      Boundary work                         Complex issues      Pure scientists      Organizational   Science-push transfer                                                                 culture                        Credibility         Science arbiters                     Policy-pull transfer                        Relevance           Issue advocates      Language and    Co-production                                                                 jargon                        Legitimacy          Honest brokers                       transaction                                                                 Organizational   Translation                                            Knowledge brokers    scales                                            Networks and personal   Political    Mediation                                            interrelationships   jurisdictions   Trade-offs                                                                 Functional                                                                 activities                 Source: Author.                  4  Conclusion                       My research seeks to contribute both to the interdisciplinary research of science-policy                interface  and  also  to  postmodernism  on  which  ontological  and  epistemological  positions  it                stands. Within the scope of this paper, I have used the notions of values and processes as an                analytical tool for the conceptual analysis of the SPI theory. My research question was to find                possible indicators of effectiveness which can be extracted from the SPI theory and which can be                further tested in a future empirical research. Postmodernism identified values and processes as                the predominant factors in understanding the world around us. Existing SPI theory [13] pointed                to a gap between theoretical approaches and empirical studies on expert roles in the process of                scientific advice to policymaking, which is understood here as a practice of boundary work [7]                and knowledge brokering [9] that deals with complex issues and uncertainty [13]. We want to                bridge this gap with our take on the effectiveness which, given our postmodernist approach, we                understand differently than it has been defined in the SPI literature. Heink et al. [6] defined the                effectiveness in the context of SPI as “the ability to influence the behavior of intended audiences                by  enhancing  their  knowledge  of  the  consequences  of  their  decisions.”  [6].  For  Cash  et  al.,                effectiveness is “how problems are framed, how concerns are addressed and how policy options                are considered” [1]. For Pülzl and Rametsteiner [12], the effectiveness depends on the model of                SPI interaction.                      I  claim  that  we  can  evaluate  the  effectiveness  of  SPI  by  better  understanding  and                comparing the social constructions of roles of the involved actors, both on the science and policy                side of the interface, producers and users of scientific information. After applying the criteria of                values and  processes on  the  SPI  theory,  I  have  identified  four  areas of  possible indicators  of                effectiveness. I have conceptualized social constructions of roles with combination of values and                processes on one side and scientific information, actors, boundaries and boundary work on the                other.  Through  this  matrix  I  have  created  a  list  of  indicators  based  on  which  I  will  test  my                                                                145","hypothesis which says that if the social constructions of roles are being similar, the effectiveness                of SPI will be higher than if the roles are constructed differently. I will test this hypothesis with                qualitative in-depth interviews in the selected case studies. Having said that, I will not test the                quality of indicators themselves. My goal is not to prove which indicators contribute to higher                effectiveness of SPI. My claim is that if the understanding of an indicator is the same, scientific                information  will  be  transferred  from  knowledge  producers  to  knowledge  users  effectively                regardless  of  the  fact  that  the  indicator  in  question  scores  high  or  low  in  the  credibility,                relevance  and  legitimacy  model, or  any  other.  My  point is  that a  high  level  of understanding                between the involved actors on bad quality indicators is actually better for the effectiveness than                a  low  level  of  understanding  on  good  quality  ones.  I  claim  that  what  really  matters  is                understanding on values and processes as such.                 4.1 Future research                      For  the  purposes  of  my research,  I  will  need  to  compare  the  social construction  of  the                involved actors. These actors will be individuals as individuals create social constructions. As I                will need to compare the social constructions of individuals from the both sides of knowledge                transfer, knowledge producers and knowledge users, I will need to select two categories of these                individuals for each particular case study. The first category of the analyzed individuals, the so                called knowledge producers, will come from the field of boundary work as defined in the theory                [1].  These  individuals  could  be  working  either  as  individual  knowledge  brokers  or  policy                entrepreneurs, or they can be employees of boundary organizations as defined in the theory.                The  second  category  of  the  so  called  knowledge  users  will  come  from  the  pool  of  decision-                makers  associated  with  the  first  category  of  actors.  These  decision-makers  must  be  jointly                involved in particular case studies with the individuals of the first category. I will identify the                pairs  of  individuals  from  the  first  and  second  category  whose  social  constructions  will  be                compared in order to prove my hypothesis.                      I intend to collect empirical data from qualitative in-depth interviews with the identified                individual  actors  from  both  the  knowledge  producers  and  users  side.  The  interviews  will  be                transcribed  and  analyzed  following  the  methods  of  iterative  coding  and  qualitative  content                analysis.  I  expect  the  result  of  this  research  to  be  a  model  for  comparison  of  the  social                constructions of the involved actors at science-policy interface with which we would be able to                better understand concepts and social constructions that exist around particular science-policy                interfaces and to better evaluate the effectiveness of these processes. We would be able to better                understand framing of an issue and roles of the involved experts and organizations. With this in                hand, practitioners would better understand which particularities are of importance and they                would  work  more  with  them.  Consequently,  this  should  enable  better  aimed  communication                between  knowledge  producers  and  knowledge  users.  They  should  also  be  able  to  better                understand processes and factors that influence knowledge producers and knowledge users (e.g.                individual  psychological  characteristics,  social  group  norms,  organizational  culture)  and  the                nature of scientific information itself.                   Acknowledgements                       This article has been elaborated as one of the outcomes of research project supported by                the  Ryoichi  Sasakawa  Young  Leaders  Fellowship  Fund  (SYLFF)  of  the  Tokyo  Foundation  for                Policy Research (2018-2019).                                                                          146","References                [1.]  CASH, D., CLARK, W.C., ALCOCK, F., DICKSON, N.M., ECKLEY, N., JÄGER. J. 2003. Salience, Credibility,                     Legitimacy and Boundaries: Linking Research, Assessment and Decision Making. KSG Working Papers                     Series. Available on: http://nrs.harvard.edu/urn-3:HUL.InstRepos:32067415                [2.]  CHIA, R. 2003. Organization Theory as Postmodern Science. The Oxford Handbook of Organization                     Theory. Available on: https://www.researchgate.net                [3.]  DANDRIDGE, T. C., MITROFF, I., JOYCE, W. F. 1980. Organizational Symbolism: A Topic to Expand                     Organizational Analysis. Academy of Management Review; 5(1): 77-82.                 [4.]  DUNN, G., BOS, J.J., BROWN R.R. 2018. Mediating the science-policy interface: Insight from the urban                     water sector in Melbourne, Australia. Environmental Science and Policy; 82: 143-150.                [5.]  GERGEN, K.J., THATCHENKERY, T.J. 2004. Organization Science as Social Construction. Postmodern                     Potentials. The Journal of Applied Behavioral Science; 40(2): 228-249.                [6.]  HEINK, U. ET AL. 2015. Conceptualizing credibility, relevance and legitimacy for evaluating the                     effectiveness of science-policy interfaces: Challenges and opportunities. Science and Public Policy; 42:                     676-689.                [7.]  HOPPE, R. 2009. Scientific advice and public policy: Expert advisers and policymakers discourses on                     boundary work. Poiesis Prax; 6: 235-263.                [8.]  JASANOFF, S. 2003. Technologies of Humility: Citizen Participation in Governing Science. Minerva;                     41: 223-244.                [9.]  MEYER, M. 2010. The Rise of the Knowledge Broker. Science Communication; 32(1): 118-127.                [10.] PARKER, M. 1992. Post-Modern Organizations or Postmodern Organization Theory. Organization                     Studies; 13(1): 1-17.                [11.] PIELKE, JR., R. 2007. The Honest Broker: Making Sense of Science in Policy and Politics. Cambridge:                     Cambridge University Press.                [12.] PÜLZL, H., RAMETSTEINER, E. 2009. Indicator development as ‘boundary spanning’ between                     scientists and policy-makers. Science and Public Policy; 36(10): 743–752.                [13.] SPRUIJT, P., KNOL, A.B., VASILEIADOU, E., DEVILEE, J., LEBRET, E., PETERSEN A.C. 2014. Roles of                     scientist as policy advisers on complex issues: A literature review. Environmental Science and Policy;                     40: 16-25.                                                                                               147","Innovative Ways of Citizen Participation                                          in Delivering Public Services                                                                    a                                MIKUŠOVÁ MERIČKOVÁ Beáta , MUTHOVÁ Nikoleta               b                                     Faculty of Economics, Matej Bel University, Banská Bystrica, Slovakia                                      a                          b                                       beata.mikusovamerickova@umb.sk,  nikoleta.muthova@umb.sk                Abstract                 The development of new technologies, social media and web 2.0. enable, inter alia, to address the problem                of ineffective  providing of  public goods (free-rider problem). Thanks to growing  connectivity  it is  now                easier than ever for individuals to collectively contribute with ideas, time, expertise, or funds to public                policy projects. This collective action is crowdsourcing. Crowdsourcing is the practice of engaging crowd                for a public interest, primarily online through social media and crowdsourcing platforms, and leverage                their networks for greater financial support and advocacy initiatives with a social impact. The goal of the                paper is to introduce the crowdsourcing as the possibility to correct public service delivery failure and to                identify the crowdsourcing development factors. The method of survey experiment is used to demonstrate                the provision of public goods through crowdsourcing in community centre. The outcomes of research can                be useful for government in public service charging and for non-governmental organizations in donations                opportunities identifying.                Keywords: Citizen; Crowdsourcing; Participation; Public services.                 JEL Classification: C93, D12, D64, H41                    1  Introduction                       Innovative answers how to solve this public sector failure, i.e. how to produce and finance                public goods, intended to enhance public values such as effectiveness, efficiency, and legitimacy,                can  be  found  through  collaboration  with  different  stakeholders,  delivering  interesting  social                innovations  [17].  This  inefficiency  rate  can  be  reduced  by  introducing  alternative  ways  of                securing public goods based on voluntary cooperation, crowdsourcing.                      Crowdsourcing  [11]  is defined as  an  open  call,  essentially  through  the internet,  for  the                provision of financial resources either in form of a donation or in exchange for some form of                reward and/or voting rights, in order to support initiatives for specific purposes. In the context                of this paper, we work with the definition that crowdfunding is an emerging source of funding                involving open calls to the public, generally via the Internet and ICT, to finance projects through                donations and monetary contributions in exchange for a reward, product pre-ordering, lending,                or  investment.  Crowdsourcing  is  then  also  receiving  a  non-monetary  contribution  (e.g.,                information or input) into a task or project by using the services of a large number of people,                typically via the Internet.                      Crowdsourcing has been used for various projects in the profit and non-profit sectors; in                this paper, we focus on its use in the public sector to solve the public-sector failures in the field                of community development.                      In addressing public sector failures in the field of community development, it is necessary                to change the behaviour of individuals, households, companies and public organizations. If we do                not perceive the individual as purely rational (homo oeconomicus), i.e. a person who is driven                exclusively  by  \"economic\"  motives  in  order  to  achieve  the  greatest  possible  material  or                monetary gain who would choose the free-rider strategy, but perceive their bounded rationality,                bounded willpower and bounded self-interest, then it is possible to achieve desirable results by                means of suitable settings of the conditions in which an individual decides.                                                                  148","Bounded  rationality  [15]  reflects  the  limited  cognitive  abilities  that  constrain  human                problem solving. Within bounded rationality, we identified several factors acting on individuals                [7]: messenger, incentives, norms, defaults, salience, priming, affect, commitments and ego.                      Demographic  and  behavioural  similarities  between  the  individual  asking  for  help  and                recipient can improve the effectiveness of the request (messenger) [4], [7], [8].                      Incentives such as fear, fiscal policy, the size of the public sector and information can affect                how individuals respond to incentives. Crowdsourcing uses positively tuned instructions, which,                as it were, force the \"altruism\" or highlight the benefits of collaboration on the individual and                thus  achieve  a  higher  degree  of  voluntary  engagement,  as  well  as  public  policy-making                experiments with negatively tuned instructions by means of sanctions. Regarding the perception                of risk [7], also suggests that it is important for individuals to have an overview or know what                their money was used for, or when their money was used. Individuals want to know what they                can do rather than what prevents them from doing so. Campaigns set through crowdsourcing                are time-limited, and those involved are always informed about the results.                      Also, social and cultural norms such as social rules, moral duty, religious duty, conscience                and relationship to the recipient beneficiary affect in positive or negative way the willingness of                people to voluntarily pay or help. People often take their understanding of social norms from the                behaviour of others, which means that they can develop and spread rapidly [7], [12].                      The  situation  where  we  can  encounter  the  effects  of  this  factor  is,  for  example,  when                contributing to a \"charity\" collection. For example, if a given NGO has a set, or default monthly                amount  of  voluntary  contributions,  it  may  happen  that  individuals  will  not  increase  their                contributions  retrospectively  [7].  Crowdsourcing  and  especially  crowdfunding  determines                different support options and varying amounts of financial contributions to eliminate the default                effect.                      Salience  explains  why  unusual  or  extreme  experiences  are  more  prominent  than  less                constant experiences [7]. Peak moments or final impression can influence whole events. In other                words, individuals prefer three hours of steady discomfort in dentist over the one who gave us                sharp pang of pain, because that pain is particularly salient [7].                      According  to  [7],  the  questions  if  an  individual  is  ultimately  influenced  by  a  particular                behaviour depends on the environment – priming [1], [9], where the individual is influenced by,                what the individual sees, hears or feels when it comes to spreading the message or, in the sense                that an individual imitates what they see or hear [6]. The reason for this behaviour, imitation, is                that the individual has a \"need to belong\" [2], [3], [13], i.e. does not want to be alone, wants to be                accepted by society. Social networks make this largely possible, crowdsourcing also contributes                to community building.                      Affection is a powerful force in decision-making. People in good mood make unrealistically                optimistic  conclusion,  whilst  those  in  bad  mood  make  unrealistically  pessimistic  conclusion.                Research even proves that appropriately chosen words for success such as winning, succeeding,                overcoming, mastering, and others lead to better results than the use of aggressive words such                as defeating competition, and reaching the goal [4], [6].                      The individuals seek to be consisted with their public promises and reciprocated acts. If                the promise is linked to financial or social costs (damage to reputation), an individual is more                willing to fulfil his obligations [7].                      Individual behaviour is also limited by selfish interests. Bounded self-interest incorporates                the comforting fact that people are often willing to sacrifice their own interests to help others                [15].  The  individual  acts  in  order  to  have  the  best  possible  feeling  about  themselves  (ego).                Individuals tend to behave in a way that supports the impression of positive and consistent self-                image [7].                      The paper focused on factors that influence the willingness of individuals to voluntarily                pay  for  public  goods  and  whether  there  are  mechanisms  that  increase  their  willingness  to                voluntarily pay.                                                                   149","2  Material and Methods                       The goal of the paper is to introduce the crowdsourcing as the possibility to correct public                service delivery failure and to identify the crowdsourcing development factors.                      During the experimental survey, we cooperated with the community centre. Therefore we                have chosen community centre as a public good in our experimental survey. A frequent problem                of experiments is a non-representative selected sample that does not allow generalisation of the                achieved  results.  The  experiments  usually  focus  on  testing  the  responses  and  behaviours  of                university  students.  The  reason  for  the  use  of  students  is  the  low-cost  of  setting  up  the  test                group  and  the  assumption  of  greater  interest  and  motivation  when  testing  students  [16].  In                contrast, the advantage of the survey experiment is that the experiment is administered to a                representative  population  sample  [10],  [16].  A  survey  experiment  involves  the  (random)                manipulation of one or more features of the survey instrument (vignette), such as the phrasing                of question prompts (voluntary and involuntary payment), the ordering of response categories,                or  the  informational  content  of  a  hypothetical  scenario  (highlighting  the  positive  effects  of                implementing the project). Although survey experiments are extremely useful tools, they are not                a panacea for the major challenges to causal inference [5], [16]. This is because manipulation of                one feature of the scenario will generally change subjects’ beliefs about other features of the                scenario [5].                      The research hypothesis: The willingness of the consumers to pay voluntarily for public                goods is dependent on the payment mechanism.                      At the beginning of the experimental survey, we introduced the project published on the                crowdsourcing platform www.dobrakrajina.sk called \"Community\".                      The role of the respondents was to evaluate the benefit of establishing of the community                centre and the services, which the centre provides. Respondents were therefore required to set a                prize  for  the  services  provided  by  a  community  centre.  In  our  contingency  scenario,  we                introduced  the  community  centre  as  a  centre  that  encourages  active  citizen  participation  in                public decision-making, helps to formulate and defend their natural interests, creates space for                effective co-operation between citizens, self-government and business communities (with a goal                of development of such communities) in order to develop communities. We have informed them                that  from  the  city’s  point  of  view,  the  main  problem  is  the  lack  of  a  leaders  and  financial                resources. At the same time, we have highlighted the positives, respectively qualitative changes                that could occur in case of support for community development by individuals. We used the CVM                (contingent  valuation  method)  using  the  WTP  method  to  evaluate  the  benefits.  We  asked                respondents  whether  they  are  willing  to  voluntarily  support  such  community-based  projects                from their own net monthly income, or whether they are willing to support the type of projects                in form of a local fee if the city or municipality chooses to do so, or if they would be willing to pay                in case the state would have used a coercion in form of taxes. We then asked them what would                be the time interval for which they would be willing to contribute and also what total amount                would they contribute to such a project. In pivotal valuation, we used open survey questions. We                tried  to  investigate  how  many  individuals  would  be  willing  to  contribute  to  the  project,  for                which we asked a set of auction inquiry questions. At the same time, we asked them about the                factors that influenced their decision to support the project or not.                      Finally, we asked respondents about the socio-demographic characteristics (gender, age                category, the highest achieved education, economic activity, the average net monthly earnings,                number of household members, and number of dependent children).                      The basic sample, as a set of statistics, in this case, consists of residents of Slovakia who                meet  the  required  characteristics.  The  basic  sample  is  very  extensive,  as  it  is  comprised  of                4,429,608.5 inhabitants; we, therefore, determined the selection sample that comprised of 368                Slovakia  citizens.  We  obtained  the  selected  sample  using  quota  sampling  according  to  the                following  statistical  attributes:  gender,  age  group  and  educational  attainment,  whereby  its                structure  corresponds  to  the  basic  sample.  We  translated  the  obtained  data  using  numerical                codes and furthermore statistically processed the data using the following statistical methods:                                                                150","·  Chi-square test (tests the representativeness of the selected sample),                      ·  Spearman  correlation  coefficient  and  Cramer’s  V  (verification  of  dependence  of  the                         characteristics  of  the  consumers'  gender,  age,  level  of  education,  the  average  net                         monthly  earnings,  the  number  of  members  of  the  household,  number  of  dependent                         children).                      ·  Multiple  response  analysis  for  evaluation  of  the  benefits  of  community  centre  for                         individuals.                       For  evaluation,  we  used  IBM  SPSS  Statistics  19  statistical  software,  for  testing,  we                considered the significance level of 0.05.                  3  Results and Discussion                       We have set the main research hypothesis in work, which we will try to verify in the next                part.  The  main  research  hypothesis:  The  willingness  of  the  consumers  to  pay  voluntarily  for                public goods is dependent on the payment mechanism.                      We used the chi-square test to verify the selectivity of the sample in relation to the base                file.  We  found  that  the  selected  sample  is  representative  for  all  sorting  characteristics,  e.g.                gender,  age  category  and  the  highest  achieved  education  (p-value  0,959;  0,973;  0,559).  The                results found in the survey can be generalised for all inhabitants of Slovakia.                              Table 1: The selected sample for measuring willingness to pay for public goods                                                                             Selected sample   Basic sample                                     Classification symbol                                                                                   %               (%)                                                             Male                 48.91           48.78                 Gender                                                            Female                51.09           51.22                                                            18-24                 10.60           10.34                                                            25-34                 19.29           18.85                 Age group                                  35-44                 20.38           19.92                                                            45-54                 16.85           16.26                                                             55+                  32.88           34.63                                                          Elementary              15.49           18.39                                                   Secondary without final exams   29.35          28.29                 Education                                                    Secondary with final exams    37.50           36.31                                                            Tertiary              17.66           17.10                                                            Student               8.77              -                                                           Employee               52.33             -                                                      Self-employed person        11.78             -                 Economic activity                    Parental or family leave    2.47              -                                                      Age and invalid person      16.99             -                                                          Unemployed              7.67              -                                                           Guardian               0.55              -                                                           To € 330               14.44             -                                                          € 331 – 500             19.62             -                                                         € 501 – 700 EU           22.62             -                 Net earnings                                                         € 700 – 1,000            15.80             -                                                        More than € 1,000         9.26              -                                                    I not interested in answering   18.26           -                 Source: Authors.                       At the beginning of the experimental survey, we asked respondents whether they have                ever visited the community centre. Only 68 respondents of 368 answered positively, meaning                they  labelled  answer  “yes”.  48  respondents  visited  the  community  centre  in  consequence  of                someone's  recommendation  (for  example,  parents,  friend  /  girlfriend,  priest,  and  other                acquaintances).  Respondents  most  often  visit  the  centre  with  their  friends  (48.5%  of                respondents), alone (29.4%) or with their child / children (11.8%). By visiting the community                centre,  the  respondents  were  able  to  create  a new  friendship  (55.9%  of  cases),  gain  a new                knowledge  (29.4%),  skills  (19.1%),  they spend  their  free  time  more  efficiently  (32.4%),  they                                                              151","were not alone (14.7%), they could relax (25.0%). Only in 10.3% of cases respondent choose the                possible “I gained nothing”.                      In the next part, we will focus on the willingness of individuals to adopt a certain rate of                community service charge on community development projects. We noticed that respondents                could voluntarily contribute if rates of coercion changed. In the first case, the degree of coercion                was the lowest. Respondents had to decide whether they would voluntarily pay for the services                of the community centre in their municipality from their net monthly income. We assumed that                if community development facilities exist in the municipality, individuals will act as a free rider,                they will use goods they haven’t paid for. In this case, there is no risk of a reduction in the utility                of the consumption of a good of which the individual is not interested, because his consumption                is not mandatory.                      In the second case, the degree of coercion was higher. In this case, we asked respondents                “Are you willing to support the project of community development in your municipality, if the                municipality set a fee for community centre services?”. Unlike the first case, it is assumed that an                individual consumes only the goods he or she is genuinely interested in, respectively he shows                preferences in the consumption of a public good. If he or she is interested in an event or an                activity carried out by a community centre, they will have to pay for joining a community centre.                      In the last, third, part the level of coercion was the highest. Individuals did not have the                option of avoiding paying for a community centre, because the state as a paternalist ordered                individuals to contribute to this project a certain amount of funds in the form of an increase in                tax burden over a period of 5 years. With this mechanism, the value of an individual utility may                fall because of the consumption of a good that individual is not interested in.                      The following table (Table 2) shows the willingness of individuals to voluntarily pay for                community centre according to selected mechanism.                                            Table 2: Comparison of selected mechanisms                                                            Voluntarily    Partly voluntarily   Involuntarily                 Willingness  to   Contributed                 152               172                95                 pay            Not contributed                216               196               273                                One time                      27.63%           25.00%                                Annually                      30.26%           41.86%                 Regularity   of   Semi-annually              18.42%           13.37%                 contribution                                Monthly                       20.39%           18.02%                                Other                         3.29%             1.74%                Source: Authors.                       The  results  in  the  table  show  that  the  respondents  most  often  chose  the  annual                contribution period (118 respondents in total). In the case of the last mechanism, we did not ask                respondents  how  often  they  would like  to  contribute  regularly,  because  the  regularity  of  the                contribution was given in the phrasing of the question itself (every month during the 5 years).                For each mechanism, we asked respondents how much they are willing to pay for a community                development project. The following table (Table 3) contains the basic descriptive statistics for                selected mechanisms.                                     Table 3: Basic descriptive statistics for willingness to pay in €                    Mechanisms         Description     Average   Median   Std. deviation   Min   Max   Total                 Voluntarily       Free rider           35.85   20.00       62.16     0.10   500.00   5,342.00                 Partly voluntarily   Utility maximization   42.02   15.00   126.66   0.05   1,500.00   7,228.05                 Involuntarily     Forced consumption   41.22   20.00       67.97     0.05   500.00   3,915.50                Source: Authors.                       Significant correlations were observed between selected mechanisms (Table 4).                                                                    152","Table 4: Correlations between selected mechanisms                                         Voluntarily           Partly voluntarily           Involuntarily                 Voluntarily               1,000                 Partly voluntarily        0.796**                    1                 Involuntarily             0.617**                 0.519**                       1                Source: Authors.                Legend: ** Correlation is significant at the level 0.01 (2-tailed)                      We  asked  the  respondents  what  influenced  their  decision  to  voluntarily  pay  for                community  development  project.  The  factors  which  affected  the  decision-making  process  of                respondents are shown in the following tables (Table 5 and Table 6).                              Table 5: Motives for voluntary payment for community development project                                                                                 Partly                  Factors              Reason                 Voluntarily                     Involuntarily                                                                               voluntarily                  Incentives   The state doesn’t solve the problem   14.47%     14.53%           18.95%                            Feeling  satisfied  with  promoting                   Affect                                      35.53%           30.23%           34.74%                            good things.                            My family, friends and acquaintances                  Priming   are  paying,  therefore  I  am  doing  it   4.61%    6.98%           9.47%                            too.                            The project caught me. It is a current                  Defaults                                      9.21%           13.37%           18.95%                            problem in Slovakia.                            When  we  cannot  help  ourselves,                  Salience                                     14.47%           16.86%           16.84%                            nobody can help us.                 Messenger   I want better life for my relatives.   7.89%        6.98%           1.05%                   Norms    The society should deal with it.   13.16%           11.05%           0.00%                    Ego     I would like to make myself visible.   0.66%         0.00%           0.00%                            Other                               0.00%            0.00%           0.00%                Source: Authors.                       The main reason why individuals chose to voluntarily pay for community project is warm-                glow effect. This reason chose almost 140 respondents. Only the reason “I want better life for my                relatives” had significant influence on the amount of payment (p-value 0,019, rs = 0,192).                                 Table 6: Motives for non-payment for community development project                                                                                    Partly                   Factors                  Reason                 Voluntarily                  Involuntarily                                                                                  voluntarily                   Priming   The project does not interest me.        9.26%         12.76%         5.86%                             I do not see why I should make a \"job\" of the                   Salience                                          22.22%         21.94%        17.95%                             state or municipality                    Affect   I do not believe in such a project      16.67%         19.39%         6.96%                   Defaults   I am not interested in answering.      15.28%         18.37%        13.92%                    Norms    I voluntary pay for other activities, projects.   8.33%   6.63%       2.56%                  Messenger   I do not need a community development   9.26%         13.78%         0.00%                     Ego     I do not need to make myself visible.   12.04%         7.14%          0.00%                 Commitment  I do not see why the state should command   0.00%      0.00%         27.11%                      s      anything                             The tax burden is too high; the state should                  Incentives                                          0.00%         0.00%         22.71%                             better reallocate financial resources.                             Others                                   6.94%         0.00%          2.93%                Source: Authors.                       The main reason why individuals would not voluntarily pay for community development                project is that they do not see why they should do a \"job\" of the state or municipality.                      We  examined  that  there  is  a  relationship  between  the  characteristics  of  individuals                (gender,  age  category,  the  highest  obtained  education,  economic  activity,  earnings)  and  their                interest  to  support  the  project  in  an  analysis  of  the  factors  affecting  the  willingness  of                                                                153","individuals to voluntarily pay for public goods. The results are interesting from the point of view                of the relevant organisation of fundraising activities, which would get closer to Pareto efficiency,                respectively answer the question \"how is it necessary to change the way funds are raised from                the  contributors  to  increase  their  contribution?\".  In  the  case  of  dependency  factors,  it  is                necessary to stimulate, respectively set experiment parameters to act to increase the willingness                of individuals to pay for the selected project. In our survey, we have stimulated the willingness                of individuals to pay by highlighting positive impacts on the society by implementing the project.                      For younger individuals, a satisfactory feeling of giving a voluntary payment is important,                while for the elderly it is important to have a better life for their relatives (p-values 0.050, 0.027,                rs = -0.159, 0.180). Individuals with higher education will voluntarily pay for the project while                addressing the current issue, while individuals with lower education will choose to contribute                because \"When we can’t help ourselves, nobody can help us.\" (p-values 0.023; 0.028; rs = 0.184; -                0.178).  For  the  individuals  with  higher  income  is  important  whether  the  project  solves  the                current problem in society or not (p value 0.012, rs = 0.204). For lower-income individuals, a                state's compulsion to pay for a community development project is a systematic solution of the                problem (p-value 0.037; 0.037; rs = 0.215; 0.215). The dependence between socio-demographic                factors (age category, the highest obtained education, earning) were evaluated by Spearman's                correlation coefficient. We used Cramer V for evaluation relationship between gender, economic                activity and willingness of individuals voluntarily pay for community project. According to the                results of some  experiments,  women  are  more socially  oriented  than  men  are, and  therefore                realize that the need for community development is a social problem that needs to be solved (p-                value 0.021, Cv = 0.176). The economic activity of the individuals influenced the reason “I want a                better life for my relatives” (p-values 0.040, 0.003, Cv = 0.277, 0.321).                   4  Conclusion                       The  goal  of  the  paper  was  to introduce  the  crowdsourcing  as  the  possibility  to  correct                public  service  delivery  failure  and  to  identify  the  crowdsourcing  development  factors.                Crowdsourcing  can  be  successful  only  on  condition  that  the  activities  the  project/campaign                offers are beneficial for the community, thus contribute to society’s sustainable development.                For  the  public  good,  for  which  we  conducted  a  survey,  we  set  up  community  development                project.  Another  condition  for  success  is  to  build  a  community  and/or  create  a  network  of                contributors who are willing to contribute in monetary or non-monetary form so the campaign                would be fulfilled and the project realised. In our case, we introduced to individuals three ways                in which they can voluntarily pay for) a community development project.                      The  most  efficient  mechanism  was  the  \"partly  voluntary\"  mechanism  when  the                municipality set up a fee for access to activities undertaken by the community centre. In this                case, the consumer pays only for the goods he actually consumes and benefits from.                      Crowdsourcing builds on many principles used in creating effective public policies, there                are several joint factors discussed in this paper (messenger, incentives, norms, defaults, salience,                priming, affect, commitments, ego) [7].                      Individuals  were  influence  by  all  factors  except  for  ego  factor  in  the  case  of  voluntary                mechanisms. For an individual, for example, it is important to become part of a certain group of                people by helping them.                      If we take a mechanism where the decision of an individual is partially voluntary, besides                the  factors  of  ego  and  defaults,  the  decision  of  individuals  is  influenced  by  all  factors.  For                example if there are certain activities an individual is interested in, he / she may not necessarily                ask to pay, but does so arbitrarily in his / her own interest [14].                      In a situation where an individual is forced by the state to contribute to some activity in                the form of an increase in the tax burden, his decision is influenced only by the commitment                factors. Individuals were aware that if they did not meet their obligations to the state, they could                incur additional financial costs. On the other hand, the activity carried out through community                development projects should contribute to increasing the welfare of the individual.                                                               154","Yet, crowdsourcing uses the power of a crowd and thus has more effective results than                just implementing public policy.                   Acknowledgements                       The paper was prepared within the project of the Czech Science Foundation \"Alternative                service delivery arrangements\" (GA19-06020S).                   References                [1.]  AARTS, H., DIJKSTERHUIS, A. 2003. The silence in library: environment, situational norm, and social                     behaviour. Journal of Personality and Social Psychology; 84:18-28.                [2.]  BAUMEISTER, R. F., LEARY, M. R. 2000. The need to belong: On the automaticity of higher mental                     processes. Psychological Bulletin; 126(6): 925-945                [3.]  CAPORAEL, L.R., DAWES, R.M., ORBELL, J.M., VAN der KRAGT, A. 1989. Selfishness examined:                     Cooperation in the absence of egoistic incenives. Behavioral and Brain Science; 12:683-739.                [4.]  CIALDINI, R. B. 2009. Influence. The psychology of persuasion. HarperCollins e-books.                [5.]  DAFOE, A., ZHANG, B., CAUGHEY, D. 2015. Confounding in survey experiments. Draft. Presentation at                     the annual meeting of The Society for Political Methodology. Available on                     http://www.sas.rochester.edu/psc/polmeth/papers/confounding.pdf                [6.]  DIJKSTERHUIS, A., BARGH, J. A. 2001. The perception-behaviour expressway: Automatic Effects of                     Social Perception on Social Behaviour. In Zanna (Ed). Advances in experimental social psychology; 33:                     1-40.                [7.]  DOLAN, P., HALLSWORTH, M., HALPERN, D., KING, D., VLAEV, I. 2012. Influencing behaviour: the                     mindspace way. Journal of Economic Psychology; 33(1):264-277.                [8.]  DURANTINI, M.R., ALBARRACÍN, D., MITCHELL, A. L., EARL, A. N., GILLETTE, J. C. 2006.                     Conceptualizing the influence of social agents of behavior change: A meta–analysis of the                     effectiveness of HIV–prevention interventionists for different groups. Psychological Bulletin,                     132:212–248.                [9.]  GREITEMEYER, T. 2009. Effects of song with prosocial lyrics on prosocial behaviour: Further                     evidence and a mediating mechanism. Personality and Social Psychology Bulletin, 35(11):1500-1511                [10.] GUTERBOCK, T. M. 2010. Survey experiments: Past, present, future. Annual Conference Harvard                     Program in Survey Research. Available on                     https://webcache.googleusercontent.com/search?q=cache:gFx9mH0WPxsJ:https://psr.iq.harvard.e                     du/files/psr/files/guterbock_2010_psr_conference_on_survey_experiments.ppt+\&cd=6\&hl=sk\&ct=c                     lnk\&gl=sk                [11.] KLEEMANN, F., VOß, G. G., \& RIEDER, K. 2008. Un(der) paid innovators: The commercial utiliza-tion                     of consumer work through crowdsourcing. Science, technology \& innovation studies; 4(1):5-26.                [12.] LARKIN, CH., SANDERS, M., ANDRESEN, I., ALGATE, F. 2018. Local Descriptive Norms and Salience of                     Enforcement Action: A Field Experiment to Increase Tax Collection. (April 29, 2018). Available on                     http://dx.doi.org/10.2139/ssrn.3167575                 [13.] LEARY, M. R., BAUMEISTER, R. F. 2000. The nature and function of selfesteem: Sociometer theory. In                     Zanna, M. P. (ed). Advances in Experimental Social Psychology; 32: 1- 62.                [14.] MASCLET, D., NOUSSAIR, C., TUCKER, S., VILLEVAL, M. C. 2003. Monetary and nonmonetary                     punishment in the voluntary contributions mechanism. The American Economic Review; 93(1):366–                     380.                [15.] MULLAINATHAN, S., THALER, R.H. 2000. Behavioral Economics. MIT Dept. of Economics Working                     Paper No. 00-27.                [16.] MUTZ, D. C. 2011. Population-Based Survey Experiments. Princeton: Princeton University Press.                                                                 155","[17.] VOORBERG, W.H., BEKKERS, V.J., TUMMERS, L. G. 2015. A systematic review of co-creation and co-                     production: Embarking on the social innovation journey. Public Management Review; 17(9):1333-                     1357.                                                                                                                                                 156","Optimization for Minimal State: Case Study of Bureaucracy                                 Ratio in Czech Armed Forces 1997 -2017                                                     MÜLLNER Vojtěch                                   Faculty of Military Leadership, University of Defence, Brno, Czech Republic                                                       mullnerv@unob.cz                 Abstract                 The  limited  possibilities  to  compare  the  inputs  with  the  outputs  build  a  barrier  for  the  efficiency                assessment in some segments of the public sector. The sphere of external safety undoubtedly ranks among                those segments of the public sector. The alternative way of assessment can be formed by the analysis of                alternative  aggregates.  The  efficiency  of  the  economic  management  of  public  funds  is,  among  others,                determined  by  the  personnel  structure  optimization  which  can  be  one  of  the  alternative  indicators.                Optimizing of personnel structure was one of the transformation goals of Czech Armed Forces. By use of                personnel optimization indicator which is based on the ratio between soldiers and civil employees was                possible to track the dynamic of transformation as well as the transformation goal fulfilment. The rate of                personal optimization ratio drop in time of transformation, which had been caused by the change of the                system and was replaced by the increase in the utilization of the apparatus in the following years. Since                2009, the proportion of the supportive bureaucratic apparatus has been exceeding the values from the                late 1990s and it still shows increasing tendencies. Due to this result we can evaluate the fulfilment of one                several pre-transformation goals.                Key words: external safety, efficiency, transformation, army, utilization                 JEL Classification: G3; H5; N4                    1  Introduction                      As a specific economic segment, the public sector itself is broadly diverse. From the view                of its function, each area of this sector is unique and it is not possible to determine its value with                exactitude [3]. The non-definable link between both the value and the price of services provided                is typical namely in the areas which represent the functions of a so-called minimal state [8], [6].                Traditionally,  the  minimal  state  consists  of  internal  and  external  safety,  judiciary  and  the                bureaucratic apparatus of the state [21]. The discontinuity between the services and their value                restricts the use of the tools, which are commonly applied in the private sector for measuring the                economy of performance and spent funds. In order to identify the changes in performance and                the  results  of  structural  changes  within  the  public  sector,  we  have  to  work  with  alternative                indicators. These alternative indicators are not limited to the comparison between inputs and                outputs, but they use the nonfinancial aggregates between the functioning of the institution and                its performance [4].                      The nonfinancial aggregates are one of the options how to state the goal and measure its                fulfillment or to track the dynamic of structure transformation. This work will apply one of the                nonfinancial  indicators  to  the  Ministry  of  Defense,  which  is  representative  of  minimal  state                segment  and  has  undergone  a  substantial  system  change  during  twenty  recent  years.  This                aggregate  is  based  on  the  optimization  of  personnel  structure  of  Ministry  of  Defense,  which                consist  not  only  bureaucratic  and  supportive  apparatus,  but  all  armed  forces.  One  of  the                transformation goals, which were state by Czech Armed Forces in pre-transformation strategy,                was to optimize the personnel structure. They state, “in peacetime the number of professional                soldiers decreases to 34,000 – 36,000 and the number of civilian employee will be less than 10 000”                [14]. If we track the fulfillment of this goal, we can state that the final rate between the civilian                employee and soldier should be higher than 3.4 soldiers per civilian employee. With the respect                to this goal, we will use the personnel rate to track the dynamics of transformation. The aim of                                                               157","this work is to track transformation of Czech Armed Forces by using personnel structure ratio                and to show the degree of fulfillment of the state goal.                      The structural change, which is the reason for tracking the dynamic of change, consisted                the  transformation  of  the  army  with  compulsory  military  service  into  the  professional  army.                Based  on  available  data,  the  indicator  should  illustrate  the  change  in  the  utilization  of  the                apparatus before the transformation and in the decade following the transformation. The army                is an ideal item for applying alternative indicators because it is traditionally considered a non-                productive part of economy with a specific role in society [10]. Both the specific position and                function of the army naturally create a barrier for applying the tools, which are commonly used                for efficiency and performance measurements in the private sector.                      If we want to avoid assessing the efficiency of the funds spent on military activities, we can                focus  on  the  personnel  structure  optimization.  Ministry  of  Defense  has  two  main  groups  of                employee.  The  first  group  are  armed  forces  and  the  second  are  civilian  who  represent  the                bureaucratic  and  supportive  apparatus.  The  cost  of  bureaucratic  and  supportive  apparatus                accounts for more than 20 percent of all costs. In the longer term, we can follow the changes in                the utilization of such isolated segment of the Ministry. In the longer term, the utilization rate of                the supportive bureaucratic apparatus is an important indicator in the context of the structural                transformation of the army with compulsory military service into the professional army. In the                long run, this indicator should depict the extent of change in the utilization of the supportive                bureaucratic  apparatus  in  the  context  of  the  transformation.  The  indicator  is  followed  in  the                period  of  twenty  years,  starting  in  1997  and  finishing  in  2017.  In  the  initial  stages  of  the                analyzed period we can speak about the independent Czech Army which came into existence in                1993  by  splitting  the  Czechoslovak  Army  into  the  Czech  and  Slovak  Armies.  The  1990s  can                illustrate  the  situation  before  the  beginning  of  professionalization.  The  process  of                professionalization  started  with  gradual  decrease  in  the  number  of  the  compulsory  military                servicemen at the beginning of the third millennium. It culminated on 22 December 2004, when                the last compulsory military servicemen were discharged from the army and only professional                soldiers  remained  [15].  Proceeding  from  the  indicator’s  development  of  the  values  after  the                transformation, it is possible to confirm the influence of the transformation on the utilization of                the supportive bureaucratic apparatus and so the degree of goal fulfillment.                  2  Material and Methods                       The  measurement  of  the  personnel  optimization  rate  of  the  supportive  bureaucratic                apparatus and professional soldiers, as well as the measurement of its changes in the course of                time, is based on the data of the Ministry of Defense. These data depict the personnel structure                in the defense department. The key sources of information about the personnel structure are the                following documents: Personnel Size of the Defence Department in 1992–2017 [17] and the NATO                document  called  Defence  Expenditure  of  NATO  Countries  (2010–2017)  [22],  which  contains                information about the share of expenditures on individual NATO armies’ areas. If we have a look                at  the  structure  of  the  Ministry’s  expenditure,  we  find  out  that  more  than  half  consists  of                personal costs [22]. The data about both the Ministry’s and army’s personnel structures refer to                the proportion between the military and civilian personnel. In the civilian personnel, it ranged                from 24 percent to 44 percent in 1997–2017 [17].                      The method of this article lies in comparison of the pre-transformation goal and the reality                in time. This indicator is based on the following hypothesis: If the proportion between soldiers                and  supportive  bureaucratic  apparatus  is  low,  there  are  idle  capacities.  However,  to  be                methodologically  correct,  we  must  also  admit  the  weaknesses  of  this  hypothesis.  The  first                weakness is the issue of delegating activities between the military personnel and the supportive                bureaucratic  apparatus.  Here,  we  are  not  able  to  define  the  accurate  extent  of  the  military                personnel’s independence when administering bureaucratic affairs. But we will accept the state                goal of pre-transformation document, that the ratio should be higher than 3.4 soldiers per one                civilian  personnel.  Another  restriction  lies  in  the  absence  of  the  ideal  value  for  the  ratio  of                                                               158","soldiers to the employee of the supportive bureaucratic apparatus. One extreme example can be                its idle capacity; the second can be insufficient staffing.                   3  Results                       Personal  costs  are  the  biggest  part  of  the  Ministry’s  expenditures.  In  1997–2017,  they                ranged  between  50  and  62  percent  [22].  We  can  only  talk  about  the  statistical  relationship                between  the  amount  of  funds  and  the  number  of  staff  since  2004,  when  the  statistically                significant correlation of 0.65 was identified. The relationship analysis of allocated funds to the                staff  number  indicates  the  role  of  mandatory  expenditure  in  the  budget  of  the  Ministry  of                Defense. The development of the staff numbers in the Ministry, as well as its budget, is depicted                in graph n. 1. Proceeding from the partial analysis of the importance of personal expenses, we                confirm the hypothesis about the existence of the relationship between the funds allocated for                the Ministry and the number of staff in the Ministry’s department. Due to this fact, the higher                rate of the supportive bureaucratic apparatus’ utilization can be understood as saving personal                expenses.                             Graph 1: The Budget of the Ministry of Defense and the number of staff 1997–2017                    90,00                  80,00                  70,00                  60,00                  50,00                  40,00                   30,00                  20,00                  10,00                   0,00                                              budget of Ministry of Defense (in bilions)                                          number of staff of Ministry of Defense (in thousands)                 Source: Author.                       Until  2004,  the  Ministry’s  staff  had  been  divided  into  professional  soldiers,  civilian                employees and compulsory military servicemen. From 2005 to 2014, after the transformation of                the Czech Armed Forces into a fully professional army, there were only two categories of staff:                professional soldiers and civilian employees. On the basis of the Act on Civil Service No. 234/2014                Coll. [23], a new category was introduced on 1 July 2015: the category of the state employee. For                the purpose of our analysis, this category is—in terms of function—identical with that of the                civilian employee.  For  this reason,  both categories  have  been  included  in the category of  the                civilian employees since 2015.                      The development of the Ministry’s staff number by individual categories is depicted by                graph n. 2. The total number of soldiers had noticeably decreased until 2004. This situation was                caused by the gradual reduction of compulsory military servicemen by 2004, when compulsory                military  service  was  cancelled.  Since  2004,  the  category  of  professional  soldiers  has  been                identical with the category of all soldiers. Since 1997, the number of professional soldiers has                exceeded 20,000. It reached its peak in 2007, when the total number of professional soldiers was                                                               159","24,334 [17]. In the category of civilian employees who represented the supportive bureaucratic                apparatus,  we  observed  almost  steady  staffing  in  1997–2003,  irrespective  of  the  total  army                count. After 2004, the decreasing trend of this staff category was clearly visible. The cause of this                reduction  could  be  found  mainly  in  the  structural  change  of  the  army,  as  well  as  in  the                optimization of the supportive bureaucratic apparatus’ utilization.                                                  Graph 2: Staffing (1997–2017)                   60000                   50000                    40000                   30000                   20000                   10000                        0                                            professional soldiers                                        civilian employee                                        professional soldiers and compulsory military servicemen                 Source: Author.                       The number of military personnel assigned to an employee of the supportive bureaucratic                apparatus  can  be  constructed  as  a  ratio  to  all  the  soldiers,  as  well  as  a  ratio  to  professional                soldiers  only.  In  order  to  clarify  these  differences,  in  graph  no.  3  we  give  the  values  of  the                indicator for both categories in 1997–2017. If we look at the values of the indicator before the                structural change and after the transformation of the army, it is obvious that the system change                of 2004 caused a short-term reduction of the supportive bureaucratic apparatus’ utilization in                the  relationship  to  the  number  of  all  the  soldiers.  However,  the  utilization  of  the  apparatus                increased  again  in  the  following  period.  The  lowest  values  of  the  apparatus’  utilization  were                reached  in  2004,  when  there  were  1.24  soldiers  per  one  civilian  employee.  In  contrast,  the                apparatus’ utilization in 2017 was 3.08 soldiers per one civilian employee. If we compare the                year 1997 (when there was the army of an old type) with the year 2017 (when there is a fully                professional  army),  the  differences  in  the  indicators  make  0.48  soldiers  per  one  civilian                employee. If we compare the pre-transformation goal of rate between the civilian employees and                soldiers, which says that, the ratio should be higher than 3.4 we can say that the rate from 2017                is close to this goal but does not fulfill it. The dynamics of transformation shows the positive                development of this ratio, which can reach the fixed rate of 3.4 in future.                                                                             160","Graph 3: The number of military personnel per one civilian employee 1997 – 2017                   3,50                   3,00                   2,50                   2,00                   1,50                   1,00                   0,50                   0,00                                         the number of professional soldiers per one civilian employee                                       the number of all military personnel per one civilian employee                 Source: Author.                  4  Discussion                    For completeness of the study is necessary to open discussion about the predictive value of                alternative  indicators  in  context  of  public  sector  transformation.  Naschold  and  Otter  [19]                differentiate several types of public transformation due to the core and speed. One extreme case                of transformation is natural transformation, which is connected with environment development                and  is  not  primarily  planed.  Planned  transformation  has  from  its  own  substance  several                consecutive  phases.  Authors  show  how  important  is  to  track  the  transformation  due  to  the                different dynamic, which can affect the effect of transformation. Wilson, Roscigno and Huffman                [24] focused on the personnel transformation due to the equation of civil rights in USA track the                dynamics  by  using  few  nonfinancial  indicators  and  shows  how  important  this  analysis  was.                Criticism  of  non-financial  aggregates  see  the  weak  point  in  the  facts  that  in  general  are  this                aggregate based in one-criterion evaluation [5].                    In fact, the rate of professional soldiers and civilian employee is also one-criterion method,                but the purpose of using it is not to evaluate whole process of transformation, but to track the                fulfillment  of  one  of  the transformation  goals.  Wilson,  Roscigno  and  Huffman  study  [24]  also                shows  how  problematic  could  be  the  transformation  process  without  determination  of                milestones. Inflexibility of public sector could be the main barrier of new system implementation                [9]. The case study of Czech Armed Forces transformation shows the dynamic change, which is                consistent with one of its goals.                       In  the  case  study,  we  have  to  accept  facts  that  the  activities  of  the  armed  forces  are                derived  from  strategic  objectives  and  existing security  situations  [7]. The  number  of military                personnel is kept on the level, which is based on the long-term plans and strategic documents                prepared by the Ministry of Defense. These documents are The Security Strategy of the Czech                Republic [18], The White Paper on Defence [11], Long-term Perspective for Defence 2030 [12], The                Concept of the Czech Armed Forces 2025 [13], or The Defence Strategy of the Czech Republic [16].                Based  on  these  documents,  it  is  possible  to  regard  the  number  of  military  personnel  as                exogenously  given  to  a  certain  extent.  This  fact  also  determines  the  minimum  financial                requirements for the saturation of personal costs. Unlike the permanent military profession, the                supportive  bureaucratic  apparatus  shows  bigger  dynamics,  and  it  is  possible  to  judge  its                                                               161","efficiency  on  the  grounds  of  its  utilization  and  performance.  In  the  context  of  the  detected                results,  it  is  possible  to  agree  with  the  study  of  Rosse  Babbage  [1].  He  considers  the                transformation of armed forces not only a strategic issue, but mainly an economic one.                    The detected values indicate potential savings, which result from the higher utilization of                the  supportive  bureaucratic  apparatus.  The  savings  in  this  sector  should  be  seen  as  rather                relative, because we deal with a non-productive part of economy, where, unlike in the private                sector, reducing the size of the supportive bureaucratic apparatus does not necessarily mean                absolute savings [2]. To save costs, the speed of process change is also important, which is more                rigid in the public sector than in the private sector [10]. Precisely rigidity and relatively low                operability are the reasons why it is not possible to reach such high savings through the change                of the system in the public sector as in the private sector [3]. Another important aspect of the                transformation is also the willingness to accept the change, which is motivated by profit in the                private sector but only by responsibility for public funds in the public sector [20].                   5  Conclusion                       The detected values in the utilization of the supportive bureaucratic system tell us, on the                one hand, nothing about the specific structure of the Ministry. On the other hand, they illustrate                the  dynamics  of  change  which  occurred  due  to  the  structural  transformation  and  which  was                reflected in the established trend of the next decade. On the basis of one criterial assessment, we                can regard the transformation from the army with compulsory military service to a professional                army  as  successful,  even  despite  the  relatively  long  period  in  which  the  utilization  gradually                increased. The pre-transformation goal state the rate between professional soldiers and civilian                employee higher than 3.4, but the rate ten years after transformation was just little bit over 3. In                the context of personal structure optimization, we focused on the one criterial evaluation which                was based on the tracking the dynamics of fulfillment one of the pre-transformation goals. We                can  abstract  from  the  results  the  conclusion  that  the  higher  utilization  of  the  supportive                bureaucratic apparatus can be seen as relative savings of costs. The efficiency rate of a specific                segment of the public sector cannot be determined solely based on the utilization indicator of                the apparatus. The indicative value of the indicator is limited by its very narrow focus. On the                other hand, in the areas of the so-called minimal state, its application may be one of the few                options for monitoring changes in the functioning of a given public sector segment. If we admit                the  limits  and  consider  the  indicator  complementary  or  approximate,  it  can  be  successfully                applied.                      In  the  case  of  the  transformation  of  the  Czech  Army  from  the  army  with  compulsory                military  service  to  the  fully  professional  army,  it  is  possible  to  demonstrate  how  the                optimization of personnel structure has changed over time. The pre-transformation goal was not                fully achieved, but the trend seems to be positive and could be achieved in future. The relevance                of alternative indicators is in general in the possibilities to tracks the dynamics of change over                time.  The  indicator  shows  us  that  at  the  beginning  distortions  caused  by  the  transformation                were evident in the lower utilization of civil employees. In the following years, the utilization                rate  increased  until  2009,  when  the  same  level  of  utilization  as  before  transformation  was                reached. In the following years, we can see a further increase in the utilization rate up to the                highest  measured  value  in  2017.  If  we  assess  the  army  transformation  solely  based  on  the                utilization criterion, it is possible in the long run to regard the structural change in the context of                personnel optimization as successful and the alternative indicator as proper tool for tracking                and evaluating goal fulfillment.                                                                         162","References                [1.]  BABBAGE,  R.  2013.  Reform  in  Defence?  Governance,  Decision-Making  and  Policy  Formulation.                     Security Challenges; 9 (2): 121 – 129. www.jstor.org/stable/26462922                [2.]  BRETON, A., WINTROBE, R. 2008. The Logic of Bureaucratic Conduct: An Economic Analysis of                     Competition, Exchange, and Efficiency in Private and Public Organizations. Cambridge University                     Press. 208 p. ISBN 0521071720                [3.]  CREWSON, P.E. 1995. A comparative Analysis of Public and Private Sector Entrant Quality. American                     Journal of Political Science, 39 (3): 628 – 639 doi:10.2307/2111647                 [4.]  DUNLEAVY, P., CARRERA, L. 2013. Growing the Productivity of Government Services. Edward Elgar                     Pub., p. 384 ISBN-13: 978-1781956106                [5.]  DUNLEAVY, P. 2015. Public sector productivity: puzzles, conundrums, dilemmas and their solutions.                     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Financial Accountability and Management 21 (1) https://doi.org/10.1111/j.0267-                     4424.2005.00211.x                [10.] JURISCH, M.C., et al. 2013. Key differences of Private and Public Sector Business Process Change. e-                     Service Journal, 9(1): 3-27 DOI: 10.2979/eservicej.9.1.3                [11.] Ministerstvo obrany ČR, 2011. Bílá kniha o obraně. Ministerstvo obrany ČR. p. 167 ISBN 978-80-                     7278-564-3                [12.] Ministerstvo obrany ČR, 2015. Dlouhodobý výhled pro obranu 2030. odbor prezentační a produkční                     VHÚ Praha, p. 20 ISBN 978-80-7278-666-4                [13.] Ministerstvo obrany [online] Koncepce výstavby armády české republiky 2025. 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Available on                     http://www.mocr.army.cz/images/id_40001_50000/46088/Obrann___strategie_2017_-_CZ.pdf                [17.] Ministerstvo obrany [online] Vývoj skutečných počtů osob v rezortu MO v letech 1992 - 2017 Available                     on http://www.mocr.army.cz/dokumenty-a-legislativa/vyvoj-skutecnych-poctu-osob-v-resortu-mo-                     cr-v-letech-1992---2017-129653/                [18.] Ministerstvo zahraničních věcí České Republiky, 2015. Bezpečnostní strategie České republiky.                     Ministerstvo zahraničních věcí ČR. p. 23 ISBN 978-80-7441-005-5                [19.] NASCHOLD, F., OTTER, C. 1996. Public Sector Transformation: Rethinking markets and hierarchies                     in government. John Benjamins Publishing Company, Philadelphia, p.178 ISBN 90-272-1771-8                [20.] OSBORNE, D., PLASTRIK, P. 1997. Banishing Bureaucracy: The Five Strategies for Reinventing                     Government. Plume, p.416 ISBN-13: 978-0452279803                [21.] SAMPSON, G., 1978. Liberalism and Nozick’s “Minimal State“. Mind, 87 (345): 93 – 97                     https://www.jstor.org/stable/2253363                                                               163","[22.] NATO [online] Defence Expenditure of NATO Countries (2010 - 2017) Available on                     http://www.mocr.army.cz/dokumenty-a-legislativa/vyvoj-skutecnych-poctu-osob-v-resortu-mo-cr-                     v-letech-1992---2017-129653/                [23.] Zákon o státní službě č. 234/2014 Sb. [online] Available on https://zakonyprolidi.cz/cs/2014-234                [24.] WILSON, G., ROCIGNO, J., V., HUFMANN, M., L., 2012. Public Sector Transformation, Racial Inequality                     and Downward Occupational Mobility. Social forces, 91 (3): 975-1006                     https://doi.org/10.1093/sf/sos178                                                                                                                                          164","Consistency of Czech Foreign Policy and Export Tendencies                 towards States with Ongoing Conflict – Case Study Comparison                                                        PALA Tadeáš                                  Faculty of Economics and Administration, Masaryk University, Czech Republic                                                      415056@mail.muni.cz                 Abstract                 In democratic countries, the relationships between the procedures in both foreign policy and economic                exchange should resonate with each other. The opportunity to analyze this hypothesis is used in the case                of  the  Czech  Republic’s  export  to  two  countries.  Although  both  of  them  find  themselves  in  an  armed                conflict,  the  premise  of  the  Czech  Republic’s  political  approach  towards  each  of  them  is  extremely                different.  Ukraine  is  considered  the  state,  which  is  supported  by  both  the  Czech  Republic  and  the                European  Union,  whereas  the  Al-Assad  regime  in  Syria  is  often  politically  condemned  and  political                sanctions are imposed on it. The analysis of the data carried out by The Czech Statistical Office on the                statistical value of export confirms the following essential premise: the worsened political relationships                have a strong impact on the reduction of exports. This trend is less visible in the case of Ukraine, which is                politically supported. In the case of both countries, the factor expressing the development of the internal                situation  is  visible.  In  the  case  of  Syria,  a  certain  minimum  value  of  cooperative  willingness  has  been                identified which is not affected by political proclamations, but rather by an actual possibility to physically                export.                Keywords: the Czech export tendencies, foreign policy, Ukraine, Syria, an armed conflict.                 JEL Classification: F31; F51; N4                    1  Introduction                      Exporting is one of the indicators, which describe the relationships of individual countries                not  in  terms  of  economy,  but  also  in  terms  of  politics.  These  two  categories  are  closely                intertwined and, as a rule, corresponding correlation can be identified between them. In other                words, their consensus at the political level should express their mutual economic relations. This                rule  should  work  in  the  opposite  way,  too.  This  hypothesis,  of  course,  is  not  always  entirely                accomplished.  Nevertheless,  the  cases  where  there  is  a  clear  disregard  for  both  political  and                economic behavior between the two states are, as a matter of logic, virtually absent in practice.                What we can already see in reality is the situation, when one compares the rhetorical or other                external manifestations of one of the categories mentioned, which does not correspond to the                manifestations of the other. In particular, it is a situation where, at the political-declaratory level,                state  representatives  express  themselves  critically  or  skeptically,  but  at  the  economic  level,                there  is  a  good  cooperation.  Similarly,  there  may  be  situations  where,  despite  significant                rhetorical and declaratory attitudes at the political level, there is no proportional and adequate                cooperation at the economic level. [2]                      For  the  purpose  of  the  academic  analysis,  the  issue  of  this  potential  discrepancy  is                particularly interesting from the perspective of democratic countries, where society is supposed                to shape its economy and politics through elected elites. The role of political elites that shape                both foreign policy and economic exchange should logically be in accordance. At the same time,                society,  in  whose  interest  the  elites  act,  should  be  credibly  informed  about  the  situation  of                foreign  policy  and  economic  exchange.  [20]  The  cases  where  there  are  inconsistent                manifestations  between  economic  behavior  and  political  rhetoric  are  very  important  for  a                democratic society, because these cases reveal the suspicion that the elites may in some way                influence or modify the notion of reality.                                                                 165","1.1 Hypothesis and goal                In history of international relations, we can observe strong link between politics and economy.                Relationship  in  between  those  two  segments  is  mutual,  and  in  some  cases,  the  politics                dominantly influences economics and in some cases vice versa. In this paper, we aim to describe                cases,  when  politics  had  dominant  effect  on  economical  behaviour  of  participants  on                international trade. Good example of this practice may be adaptation of Truman´s doctrine of                deterring communism, which was later fallowed by economical initiative of Marshall´s plan.                Hypothesis: The political speech acts are produced by relevant representative institutions, it is                fair to assume, that their impact will meet its goals on levels of practical economy. This model                would refer to coherent political-economical complex, that would act interdependently – in this                case export agents would take in concern recommendations of political actors, to avoid or to                support certain trade partners.                The  main  goal  of  this  paper  is  deeper  analysis  of  export  flows  determinants  by  political                statements. Paper is to be understood as an exploration of lower levels of possible knowledge.                Other  goal  is  to  try  to  find  new  interesting  evidence  enabling  a  deeper  understanding  of                relationship between political rhetoric and trade consequences.                  2  Material and Methods                       For selecting the criterion, by which the states of cross-border trade will be analyzed, the                method of Extreme Case Sampling has been used. The qualitative approach that is applied in this                method compares two case reports that have inherently different characteristics. In principle,                they  can  best  show  the  course  of  changes  caused  by  transformations  in  the  environment.                According to Patton [19] an approach involving Extreme Case Sampling will be used that works                with unusual phenomena or with the sampling of politically significant cases. [11] In particular,                the choice was narrowed to two cases, which essentially differ from each other. Therefore, they                can express or deny the manifestation of the influence the Czech Republic’s behavior. As the two                extreme cases, the following two countries were selected: Ukraine and the Syrian Arab Republic.                Selecting these two reference objects is not random. Historically, they are long-term business                partners  of  the  Czech  Republic,  or  more  precisely,  they  were  long-term  business  partners  of                former  Czechoslovakia.  At  the  same  time,  they  are  the  states  that  have  been  affected  by  the                armed conflict in about a similar period and quite unexpectedly. These facts will serve to make                the comparison more accurate.                 2.1 Export Criterion                      As an indicator of the economic activity of the Czech party, export was logically used, since                it  probably  best  measures  the  willingness  of  the  Czech  party  to  trade  with  another  country.                Obviously,  exports  are  the  most  appropriate  instrument  after  statistical  processing  for  the                following reason: Compared to imports or trade balances, exports reflect the intentionality and                real interest of the Czech party to enter into the business relationship with the given country,                despite  possible  controversies.  An  optimal  tool  for  this  study  is  data  collected  by  the  Czech                Statistical Office, which collects information on foreign trade and provides information on its                statistical value.                  2.2 Time Delimitation                      Both armed conflicts take place at about the same time. The Syrian conflict started two                years earlier, in connection with the expansion of the so-called Arab Spring. A similar situation                took  place  in  Ukraine,  when  in  2013  the  so-called  Euromaidan  protests  triggered  both  the                suspension  of  the  government  of  Viktor  Yanukovych  and  the  subsequent  annexation  of  the                Crimea by the Russian Federation, as well as the armed conflict on Donbass. For the purpose of                this paper, the statistical data from the conflict period will be identically used in both cases. At                the same time, an indication of the situation of the year preceding the conflict will be appended,                                                                166","so that the trend is at least outlined and a potential change is recognizable. In the case of the                Syrian conflict, we will deal with the period between 2010 and 2018. In the case of the Ukrainian                conflict,  we  will  focus  on  the  period  between  2012  and  2018  (for  needs  of  comparison  with                Syrian case, there will be also years 2010 and 2011 visible in graph). As a comparison, there is                also a graph of Czech exports in total. This helps the reader to better understand the trends and                timeline.                 2.3 Theory of Securitization                      The relationship between political and economic sphere is well manifested in this case,                where we aim to identify the influence between political acts and economical behaviour. Roots                of this approach are based in international relations field theory of securitization. Securitization                (in  international  relations  studies)  was  presented  as  a  tool  how  to  interpret  new  security                phenomena after dissolution of bipolar world structure. Securitization, founded in environment                of Copenhagen school, consists from identification of potential existing problem – politicization –                „speech  act“–  and  securitization  itself  (than  possible  de-  securitization).  [4]The  speech  act  is                considered as fundamental aspect of this process, since it has the most effective impact on actors                of this process. Theory of securitization operates with four categories of possible actors.                      ·  A securitizing actor/agent: an entity that makes the securitizing move/statement;                      ·  An  existential  threat:  an  object  (or  ideal)  that  has  been  identified  as  potentially                         harmful;                      ·  A  referent  object:  an  object  (or  ideal)  that  is  being  threatened  and  needs  to  be                         protected;                      ·  An audience: the target of the securitization act that needs to be persuaded and accept                         the issue as a security threat. [3]                       In our case the roles of actors are in point of fact clear. A securitizing actor/agent in our                case is Ministry of foreign affairs, who represents and heralds the official statements outside                Czech environment. The Ministry of Foreign Affairs is the central body of the Czech Republic's                state  administration  for  foreign  policy,  in  which  it  creates  a  concept  and  coordinates  foreign                development  assistance  and  coordinates  external  economic  relations.  [17]  When  it  comes  to                identify  an  existential  threat,  there  is  more  relevant  choices  than  meets  the  eye-the  state  is                motivated by change of the international environment- specifically by the fact that former trade                associate country is in state of war. The threat in this case is not to get involved to supporting of                regimes gone rouge, because it may cause negative reactions of much more important partners.                A referent object, in which name are these steps being taken is of course starving population,                casualties of war, and principle of “justice“. The audience consist mainly from Czech businesses,                who are urged to obey states opinion. Partially, other states and international partners can be                also considered as audience of process of securitization, to make a good impression.                   3  Results                      This  contradiction  is  best  illustrated  by  relations  with  the  countries  that  are  viewed                internationally  as  controversial  or  problematic.  In  the  context  of  the  Czech  Republic,  it  is                necessary  to  proceed  from  the  fact  that  this  country  is  a  member  of  various  international                organizations. From a political perspective, these are mainly NATO and the EU. It is obvious that                membership in these organizations clearly does not mean that the views of all member states on                foreign policy and the economy are identical. However, it can be anticipated that, at least in the                fundamental issues based on the resolutions and directives adopted, the member states agree                with one another. For these member states, the so-called rogue states most often play the role of                the  biggest  enemy,  which,  in  general,  has  been  causing  problems  for  the  international                community  over  the  long-term  by  its  non-adaptability,  aggressive  politics  or  non-compliance                with the standards of international coexistence. [12] Other categories are states from competing                groupings. From a political point of view, they are mainly states and federations whose history is                                                               167","defined by the Cold War and its outcomes. The representatives of this category are generally                understood as states such as the Russian Federation or the People’s Republic of China, as well as                some factions and cartels such as OPEC and the like. The last category of the states with which                economic exchange is burdened by political circumstances, are the states that share a relatively                unfortunate characteristic—the existence of an armed conflict on its territory. The states that                have been pushed into violent internal disturbances or into armed conflicts with their neighbors                are generally perceived as not fitting for regular political or economic cooperation, especially                because  their  governments  are  weak  or  endangered.  Therefore, it  is  not clear  whether  these                governments really represent the interests of the population and whether they are capable of                meeting their commitments. It is precisely the above-mentioned armed conflict countries that                are  perceived  as  risky.  At  the  political  level,  they  are  often  criticized  and  treated  with  great                caution, considering the fact that there are extensive violence and the threat to human rights. At                the same time, however, there may be a paradox where these countries or regimes are willing to                conclude  very  lucrative  business  contracts  and  partnerships,  because  their  motivation  is                survival  alone  and  not  mutually  beneficial  transactions.  Newly  set  establishments  and                government  garnitures  can  find  themselves  in  a  similar  situation.  Although  not  yet                internationally  recognized,  they  nevertheless  de  facto  control  certain  territories  which  need                certain  strategic  commodities  that  the  new  establishments  are  willing  to  get  even  under                unfavorable conditions. At the same time, conflicts and, in particular, the following periods, offer                the reconfiguration of old and long-term economic structures and allow entry to new players. In                some cases, these conflicts even allow complete redefinitions of new partners. [13]                 3.1 Definitions of Both Countries - Ukraine                      The very beginning of the conflict in Ukraine is related to many problems. The divergent                tendencies of President Viktor Yanukovych’s garniture towards an association agreement with                the EU are usually mentioned as “the last straw that broke the camel’s neck.” The subsequent                overthrow of the government and the accession of the new pro-European one were welcomed                by the EU states. The EU, like the Czech Republic, perceives Ukraine as a country that seeks to                extricate itself from the external policy of the Russian Federation and sees it as a victim of a                violation  of  international  law.  At  the  same  time,  the  EU  identifies  Ukraine  as  a  victim  of                aggression, whether in the case of the annexation of the Crimea, or in the case of the conflict with                Russia which is backed by the self-proclaimed republics. The Czech Republic with its declaration                published already in 2014 [15]                      ”Given  its  historical  experience  of  the  1930s,  the  Czech  Republic,  besides  other  things,  is                particularly  sensitive  to  the  current  Russian  conduct.  It  will  never  agree  with  undermining  the                territorial integrity of Ukraine, or with the annexation of the Crimea.” [15]                      Thus,  the  Czech  Republic  has  joined  other  Western  and  EU  states  that  have  strongly                condemned the Russian Federation’s move and backed up Ukraine. Ukraine has been politically                endorsed throughout the conflict by Western countries, the EU and the Czech Republic, despite                the statements of some pro-Russian politicians. Thus, Ukraine can be considered a country in an                armed  conflict  which  is  supported  by  the  policy  of  international  organizations  of  which  the                Czech Republic is a member, as well as by the Czech Republic itself.                 3.2 Definitions of Both Countries – Syria                      The  relations  between  the  Czech  Republic  and  Syria  have  been  greatly  affected  by  the                ongoing conflict. The Czech Republic has shared the approach of the international organizations                whose member it is, and criticized the situation in Syria, as well as the Assad regime. Despite the                fact that the Czech Republic, as one of the few countries, still maintained diplomatic relations in                the form of an embassy, it proceeded mainly from administrative and bureaucratic causes by                providing services to friendly countries such as the US or other EU countries [9]  It was the EU as                a  whole  which  joined  the  sanctions  that  were  directed  against  the  regime  structures  that                supported the Assad regime. Even the representatives of the Czech Republic, such as Foreign                Minister Lubomír Zaorálek, expressed a rather strict view [16] towards President Assad:                                                               168","“President Assad cannot represent the future of Syria. However, in order to stop the violence,                it will be necessary for all Syrian representatives except for extremists to sit behind the negotiating                table.” [14]                      Widespread  criticism  from  Western  politicians  affected  Bashar  al-Assad  and  his                establishment, especially after alleged chemical attacks. [7] The Czech Republic, the EU [5] and                others  take  a  very  cautious  stand  on  the  political  future  of  the Syrian  Arab  Republic, mainly                because of their unwillingness to accept the continuation of the government of the Assad regime.                This regime is suspected of war crimes and crimes against the civilian population. On the other                hand, both the Czech Republic and the EU cautiously approach the movement of the “rebels”                whom  the  hopes  were  initially  pinned  on.  Nevertheless,  it  turned  out  that  the  “rebels”  were                unable to defeat the regime, constructively negotiate about the future and remain inadequately                un-radicalized.                      Syria is therefore considered to be the second extreme, a country that is at war, but its                representatives lack the political support of the Czech Republic as well as of other international                groupings  of  which  the  Czech  Republic  is  a  member.  On  the  contrary,  the  Syrian  regime  is                ostracized, sanctioned, and at some stages of the conflict even considered a political opponent.                 3.3 Comparison                      Export  statistics  for  Ukraine  indicate  an  interesting  trend.  To  a  large  extent,  they  are                copying the development of the armed conflict, with 2014 and 2015 being the most intense in                terms of armed clashes and conflict dynamics. [8] With a certain degree of approximation, the                graph can be interpreted in a way that political and economic relations tend to be similar. It is                understandable that in the most difficult times of the conflict the interest in economic exchange                declined, but in 2016 it was growing again and the trend was showing positive growth. This                makes it possible to conclude that the Czech Republic is interested in cooperating with Ukraine                in foreign trade. Despite the fact that the conflict in Ukraine has not ended, export values are                slowly approaching pre-war years, which may indicate that Czech exporters have managed to                restore old contacts or that new business partners from the Czech environment have been able                to  adapt  to  the  specific  situation  in  Ukraine.  When  focusing  on  the  factors  observed  and                excluding  other  potential  influences,  it  can  be  argued  that  both  the  political  and  economic                approach of the Czech Republic towards Ukraine is to a large extent congruent and follows a                similar trend, even in the case of the conflict.                                              Graph 1: Exports to Ukraine 2010-2018                                      Source: Author – based on Czech Statistical Office [6].                       In the case of exports to Syria, there is a significant decline correlating with the escalation                of  the  armed  conflict.  The  imposition  of  both  sanctions  and  embargo  [10]  has  hit  exports                harshly. It is also important to perceive the context of the conflict itself: the years in which the                smallest export occurred were those that were of the utmost importance for the development of                                                               169","the conflict. In 2015, there was the intervention of the Russian Federation in favor of the Assad                regime that was considered by some to be too weak at the time. [1] Therefore, it is possible to                assume that the stabilization of the Assad regime by a foreign party has stopped a steep fall in                exports  and  de  facto  fixated  the  value  of  Czech  exports  at  a  certain  minimum  level.  When                analyzing this phenomenon, it is obvious that economic activity is, of course, copying political                attitudes towards a country that is in \"disfavor.” However, there is a certain bottom which seems                to adapt itself to the real-life, pragmatic situation of a conflict-stricken country rather than to                political  rhetoric  or  political  circumstances.  In  the  case  of  minimal  stabilization,  trading                continues, albeit to a lesser extent.                                               Graph 2: Exports to Syria 2010-2018                                      Source: Author – based on Czech Statistical Office [6].                  4  Discussion                       Policy is not to be considered as an only determinant of quality of exchange. This paper                strives  to  focus  only  on  part  of  complicated  relationship  between  policies  and  economical                behaviour, in this case on the aspect of possible influence of political recommendations towards                economical agents. We keep in mind, that there exist bunch of other evident or latent factors,                such  as  condition  of  economy,  political  transition,  geography,  distance,  etc.  In  this  case  both                compared cases were chosen in consideration of fact, that armed conflict is understood to be an                extreme  manifestation  of  political  behaviour.  Following  this  logic,  we  may  achieve  the  best                possible demonstration of possible relationship mentioned in hypothesis. However, we still keep                in  mind,  that  possible  findings  are  only  partial,  and  can  be  presented  as  supporting  new                evidence, and not as a some undisputable finding. Inspiration for this paper was also an example                of study named The political determinants of international trade. This study was testing three                arguments describing relationship between politics and trade flows. One of the hypotheses was                weather: “The greater the degree of common interests between a pair of states, the greater will                be their trade flows.” [18] This aspect is relevant for our paper since we compare 2 countries,                towards  which  the  political  attitude  of  Czech  Republic  differs  significantly.  Ukraine  is  being                described  as  an  ally,  however  Syrian  regime  is  often  titled  in  rather  aloof  matter.  The  other                relevant hypothesis from mentioned study, relevant for this paper, is weather: In a multipolar                system,  trade  between  allies  should  not  differ  from  trade  between  non-allies.  Of  course  this                study is based on experience of long lasting bipolar system, but still analyses similar matters as                our paper. „Our evidence indicates that other factors are more important than alliances. Prime                among these are joint democracy and the similarity of policy interests between the states. “The                results offered in discussion of this study state: “We have found evidence about the effect of                politics on international trade at the level of overall trade flows. We use a broader sample of data                with  greater  variation  and  more  appropriate  methods  for  that  data  than  do  existing  studies.                Further support for these arguments must be found at lower levels of analysis than aggregate                                                              170","trade  flows.”  [18]This  statement  was  understood  as  a  motivational  basis  for  our  lower  level                analysis, with its specification on certain detail aspects of possible relationship, rather than on                main trends and explanations.                  5  Conclusion                       Our data analysis was supposed to prove or disprove the following hypothesis: The mutual                economic  relations  of  the  two  states  should  also  express  their  political  congruence  and  vice                versa. In this context, the following question must also be answered: To what extent is the fact                that the country is finding itself in an armed conflict relevant in this respect? After performing                the analysis, we can conclude: Having focused only on the factors observed (exports and time                trends), and having overcome the potential additional effects, we can identify the trend in the                cases of Ukraine and Syria which confirms that the political approach will greatly influence the                willingness  to  export  from  the  Czech  Republic  to  a  given  country.  Positive  political  mood                indicates  greater  enthusiasm  to  continue  business  cooperation,  while  negative  political                atmosphere  minimizes  the  interest  in  exporting  to  a  minimum.  Apart  from  this  anticipated                development, we have identified the following: In addition to external political mood, the real                situation in the country and the conflict phase also significantly affect the willingness to export.                In  some  cases,  this  factor  may  logically  appear  to  be  hardly  influenced  by  external  political                relations. The study has found some general tendencies and opens up the possibility of exploring                deeper issues that are needed for even clearer outcomes. The comparison of the two countries is                based  on  the  logical criteria  of  the conflict’s  similarity  over  time.  Main  goal  –  adding  of  new                evidence in wider discussion about politics dependence towards trade flows – was successfully                undertaken. The new evidence is to be understood as a piece of mosaic, that may offer a better                understanding  of  this  great  issue.  Of  course  this  paper  explains  only  minor  part  of  complex                problematics  and  should  be  followed  by  other  academic  research,  for  example  by  additive                replications for other similar cases. Analysis of other aspects than export would also be very                beneficial for further research, and would make this new evidence much more robust.                   Acknowledgements                      This  article  has  been  elaborated  as  one  of  the  outcomes  of  research  project:                (MUNI/A/1106/2018)                  References                 [1.]  ATLANTICCOUNCIL,  2018.  [online]  Three  Years  Later:  The  Evolution  of  Russia’s  Military                     Intervention  in  Syria  Available  on  <https://www.atlanticcouncil.org/blogs/syriasource/three-                     years-later-the-evolution-of-russia-s-military-intervention-in-syria>                [2.]  BASLEY, T. 2007. The New Political Economy. The Economic Journal; 117(585):570-587                [3.]  BUZAN, P., WÆVER, O. DE WILDE, J. 1998. Security: A New Framework for Analysis. Boulder,                     Colorado: Lynne Rienner.                [4.]  CABADOVÁ WAISOVÁ, Š. 2004. Od národní bezpečnosti k mezinárodní bezpečnosti. Global Politics:                     časopis pro politiku a mezinárodní vztahy. SOCIETAS 2001, (2004):66-86.                [5.]  COUNCIL OF THE EU, 2017. [online] Declaration by the High Representative on behalf of the EU on                     the alleged chemical attack in Idlib, Syria. Available on                     <https://www.consilium.europa.eu/en/press/press-releases/2017/04/06/hr-declaration-                     idlib/pdf>                [6.]  CSO. 2019. [online] External Trade Database in cross-border concept. Available on                     <http://apl.czso.cz/pll/stazo/STAZO.STAZO?jazyk=EN>                                                                  171","[7.]  EEAS. 2018. [online] Syria: EU calls for accountability after yet another chemical attack Available on                     <https://eeas.europa.eu/topics/sanctions-policy/42657/syria-eu-calls-accountability-after-yet-                     another-chemical-attack_en>                [8.]  EEAS. 2018. [online] EU-Ukraine relations, factsheet. Available on                     <https://eeas.europa.eu/headquarters/headquarters-Homepage/4081/eu-ukraine-relations-                     factsheet_en>                [9.]  EEAS. 2018. [online] The EU and the crisis in Syria. Available on                     <https://eeas.europa.eu/headquarters/headquarters-                     homepage_en/22664/The%20EU%20and%20the%20crisis%20in%20Syria>                [10.] FRIEDRICH EBERT STIFUNG. 2016. [online] The role of the EU in the Syrian conflict. Available on                     <https://www.feseurope.eu/fileadmin/public/editorfiles/events/Maerz_2016/FES_LSE_Syria_Turk                     mani_Haid_2016_02_23.pdf>                [11.] HENDL, J. 2008. Kvalitativní výzkum: základní teorie, metody a aplikace. 2., aktualiz. Vyd., Praha:                     Portál.                 [12.] HENRIKSEN, T. H. 1999 Using power and diplomacy to deal with rogue states. Stanford, Calif.:                     Hoover Institution on War, Revolution, and Peace, Stanford University.                [13.] LE BILLON, P. 2001. The political ecology of war: natural resources and armed conflicts Political                     Geography; 20(567):561-584                [14.] MINISTRY OF FOREIGN AFFAIRS OF THE CZECH REPUBLIC. 2015. [online]: Ministr Zaorálek: Náš cíl                     je zastavit krveprolití v Sýrii. Available on                     <https://www.mzv.cz/representation_brussels/cz/udalosti_a_media/ministr_zaoralek_nas_cil_je_za                     stavit.html>                [15.] MINISTRY OF FOREIGN AFFAIRS OF THE CZECH REPUBLIC. 2016. [online]: Prohlášení MZV                     k rozhodnutí Ruské federace o připojení Krymu. Available on                     <https://www.mzv.cz/jnp/cz/udalosti_a_media/prohlaseni_a_stanoviska/archiv_prohlaseni_a_stan                     ovisek/archiv_2014/x2014_03_19_prohlaseni_mzv_k_rozhodnuti_ruske.html>                [16.] MINISTRY OF FOREIGN AFFAIRS OF THE CZECH REPUBLIC. 2018. [online]: Prohlášení ČR k aktuální                     situaci v Sýrii. Available on                     <https://www.mzv.cz/jnp/cz/udalosti_a_media/prohlaseni_a_stanoviska/x2018_04_14_prohlaseni_                     cr_k_syrii.html>                [17.] MORROW, J.D., SIVERSON R., M., TABARES, T., E. 1998. The Political Determinants of International                     Trade: The Major Powers, 1907-90. The American Political Science Review; 92(3):649-661                [18.] MINISTRY OF FOREIGN AFFAIRS OF THE CZECH REPUBLIC. 2019. [online]: Vznik a působnost                     Ministerstva zahraničních věcí. Available on                     <https://www.mzv.cz/jnp/cz/o_ministerstvu/vznik_a_pusobnost_ministerstva.html>                [19.] PATTON, M. 1990. Qualitative evaluation and research methods, Beverly Hills, CA: Sage.                [20.] ROHRLICH, P. E. 1987. Economic Culture and Foreign Policy: The Cognitive Analysis of Economic                     Policy Making. International Organization; 41(90):61–92.                                                                                      172","Does Czech Republic Suffer from Baumol´s Cost Disease?                                                      PALIČKOVÁ Irena                                   Faculty of Economics, VŠB - Technical University Ostrava, Czech Republic                                                     irena.palickova@vsb.cz                 Abstract                 This paper deals with Baumol´s cost disease theory. This theory is usually used to explain the different                dynamics of some sectors of the economy, particularly public sector and to explain the growing share of                the public sector in total resources. The aim of the paper is to verify the validity of Baumol´s theory on                data  from  the  Czech  economy  using  the  time  series  from  1995  –  2017.  It  was  found  that  the  Czech                economy shows some symptoms of Baumol´s cost disease. These include, in particular, the growing share                of the tertiary sector in total gross value added and employment, declining trend in labor productivity in                the tertiary sector, declining expenditure on goods and rising spending on services spent by households. It                was  also  confirmed  that  wage  growth  in  the  tertiary  sector  is  determined  by  wage  growth  in  the                secondary sector, which is in line with Baumol´s theory. Although the share of the public sector in total                resources in the Czech Republic is increasing, the share of public expenditure in GDP has a decreasing                trend. This may be due, inter alia, to the faster growth rate of GDP recently.                Keywords: Baumol´s cost disease; gross value added; productivity of labor; public expenditure; wage .                 JEL Classification: E24; H50                    1  Introduction                       The government in the Czech Republic often addresses the issue of salary increases in the                public  sector  (education,  health,  social  services,  culture…)  These  are  the  sectors  affected  by                market failures which undoubtedly bring benefits to society but without the support of public                budgets would not stand in the competitive sphere. The characteristic feature of these industries                is  the  fact  that  their  labor  productivity  stagnates  over  time.  In  this  context,  Baumol  gives an                example connected with live performance. “A half hour horn quintet calls for the expenditure of                2.5 man hours in its performance, and any attempt to increase productivity here is likely to be                viewed with concern by critics and audience alike.” [1] It is known, from the economy that the                wage  growth  should  correspond  to  the  increase  in  labor  productivity  to  avoid  inflationary                pressures.  If  labor  productivity  in  the  public  sector  stagnates,  wages  should  stagnate,  too.                However,  this  would  mean  that  such  a  teacher,  nurse,  theatrical  actor  or  musician  would  be                livelier and legitimately worried about the existence and future development of these sectors.                What  determines  the  growth  of  wages  in  the  public  sector  is,  according  to  Baumol´s  theory,                productivity in the productive sector. Wages in the public sector are, therefore infected by wage                growth in the productive sector. This is why the disease is talked about. The unbalanced growth                model attempts to explain growth of public expenditure relative to the gross domestic product                and has the potential to explain the different dynamics of some sectors of the economy. Although                this theory has existed for more than half a century, it retained its basic idea. The aim of the                paper is to verify the validity of Baumol´s theory on data from the Czech economy. The article                gives the answer to the question whether the Baumol´s cost disease affects the Czech Republic                or does not.                                                                         173","2  Material and Methods                 2.1 Material and methods                      J.  W.  Baumol  first  published  the  Unbalanced  Growth  Model  in  Macroeconomics  of                Unbalanced Growth: The Anatomy of Urban Crisis (1967). The model envisages the division of                the economy into two sectors – a progressive sector that produces long-term growth and human                work is seen as a means to achieve output and a non-progressive sector involving activities with                stagnant or slightly growing productivity, with human work being usually the final output. Other                prerequisites for the model are:                      1.   Production costs are limited to labor costs only.                      2.   Rate of wage growth is the same in both sectors due to labor mobility.                      3.  Growth  rated  of  wages  is  derived  from  the  rate  of  productivity  growth  in  the                progressive sector. These limitations can be written as follows:                                                 Y 1t = aL 1t                            (1)                                                          rt                                                Y 2t = bL 2te                        (2)                                                        rt                                                W t = We                           (3)                      In  this  paper,  economy  is  divided  into  four  sectors  –  primary  sector  (A-B),  secondary                sector  (C-F),  market  tertiary  sector  (G-N)  and  non-market  tertiary  sector  (O-R)  according  to                NACE 2 classification. It is worked with time series in the paper. Data, from the period of 1995-                2017, are drawn from the Czech Statistical Office and Ministry of Finance websites. Employment                is measured by the number of working hours per sectors. Labor productivity is calculated as                production  of  different  sectors  per  working  hour.  For  calculation  of  the  share  of  public                expenditure  in  GDP,  annual  data  on  general  government  expenditure  by  function  were  used.                These data are in line with the international COFOG standard and the Eurostat national accounts                data transfer programme. The paper is based on the use of applied economics, empirical and                analytical methods are used. Linear trends and regression coefficients were used for orientation                and support of the statements about the processes taking place in the Czech Republic.                 2.2 Literature overview                      Baumol´s model has been followed by a number of authors and endeavoured to enrich it                somewhat.  They  have  often  come  to  conclusions  similar  to  those  of  Baumol,  namely  that                economic growth can lead to an increase in the share of the public sector in the total resources                of the economy. J. Robinson responded to the fact that the cost of providing services in the model                remains the same, while the cost of producing the secondary sector can be reduced due to higher                productivity. [14] According to M. Keren, public sector deficit financing would only occur if the                elasticity of municipal taxes were lower than the unitary rate. [8] D. Leslie extended the model to                another sector. He does not divide the economy into labor productivity, but according to the                nature  of  outputs,  whether  private  production  of  goods,  private  production  of  services  and                public service production. Like Baumol, the growth rate of productivity is slower than that of                commodity  production,  as  well  as  a  consistent  wage  growth  rate.  D.  Leslie  also  takes  into                account changes in real consumer incomes, so the growth of wages in public production is not                considered to be clearly risky. If the cost of public service provision increases more quickly than                real household income, then governments can cover this deficit with rising tax revenues, as it                can be assumed that the rise in personnel costs stimulates growing productivity, for example,                the  commercial  production  of  goods.  The  main  problem  of  public  services  stems  from  the                impossibility of reflecting the real demand of consumers. For generating public sector, therefore,                in the end, the maximum amount of money that the mechanism of the economies can afford may                be provided in principle to provide long-term stability. [9]                                                                 174","Similarly, N. Oulton develops the model of brokerage (commercial and financial). It deals                with the nature of the output of the service sector, which it attaches to crucial importance and                divides the services into those whose output is the final product and the intermediary services.                Based  on  this  breakdown,  it  draws  on  three  models  in  which  it  analyses  the  impact  on                productivity  growth  rates.  [11]  M.  C.  Harvey  criticizes  the  model  for  being  supply-oriented.                According  him  the  analysis  must  incorporate  both  supply  and  demand  aspects  in  order  to                explain the mechanisms that determine production and employment in the different economic                sectors  really.  [7]  B.  Chapman  draws  attention  to  the  mathematical  and  logical  errors  of  the                original model. Independent errors are found in the derivation of Baumol´s propositions and in                the analysis of static externalities. [3]                      J.  W.  Baumol himself has  also  revised  the  model several  times.  In  2012,  he  applied  his                theory and its implications, for all practical purposes, to health care. With his theory explained                the  exploding  cost  of  health  care  in  the  US.  The  good  news,  according  to  Baumol,  is  that                progressive sectors churn enough purchasing power for people to be able to afford rising health                care bills, the bad news is that he sees these other sectors, with sizable productivity gains and                lower costs, as also making  weaponry  and  environmental “bads” increasingly  affordable,  and                thus posing significant threats to human welfare. [2] Equally, J. Hartwig explained increasing                trend in the share of health care expenditure in GDP in all OECD countries. [6]                   3  Results and Discussion                       The most important symptoms of Baumol´s cost disease are:                      ·  deindustrialization and growth of public sector,                      ·  movement of the labor factor from the secondary sector to the tertiary one,                      ·  productivity of labor in the public sector does not grow,                      ·  public sector wage growth is determined by the wage growth of the secondary sector,                      ·  expenditure on goods in relation to GDP decreases while expenditure on services, such                         as health or education, in relation to GDP, increases,                      ·  growth of public sector expenditure in relation to GDP.                       Deindustrialization is a natural consequence of the process of economic development in a                highly developed economy and it affects economic growth, employment and industrial relations.                Prusvic in his article mentions the analysis of A. S. Anderson, who dealt with the influence of                globalization  on  deindustrialization  of  OECD  countries.  His  analysis  has  combined                deindustrialization with the foreign direct investment flow. It leads to the displacement of labor                from industrial production and the shift of investment from industrial production to services.                [13] Also, the Czech economy has undergone a gradual decline in the share of the secondary                sector in  total output  of the  economy in favour  of  services.  Due  to  the  transformation of  the                Czech economy in the 1990s, we recorded a decline in output in GDP also in the primary sector.                This is evident from the development of the share of gross value added of different sectors in                total gross value added in Figure 1. This share declined from 6.6 % in 1995 to 3.0 % in 2017 in                the primary sector, in the secondary sector it declined from 39.8 % to 36.3 % but it increased                from 39.6 % to 43.5 % in the market tertiary sector as well as in the non-market tertiary sector,                where this share increased from 15.5 % to 16 %.                                                                             175","Figure 1: Gross value added                                           Source: [5], author.                       The  deindustrialization  process  is  linked  to  the movement of  the  labor  factor  from  the                secondary  to  the  tertiary  sector.  In  the  transforming  economy,  this  process  helps  reduce                structural unemployment resulting from sectoral changes in the national economy. The Figure 2                shows the development of the share of employment in the different sectors of the economy in                total employment. Until 2004, employment was the highest in the secondary sector, since 2004                employment is the highest in the market tertiary. In the reference period, the share of working                hours in the primary sector decreased from 7.1 % to 3.9 %, in the secondary sector it decreased                from the 38.6 % to 36.6 %. On the contrary, this share increased in the market tertiary sector                from 35.2 % to 40.4 % and in the non-market tertiary sector from 17.5 % to 19.4 %.                                                     Figure 2: Employment                                           Source: [5], author.                                                                     176","The share of labor productivity of different sectors in total productivity is shown in Figure                3.  The  highest  share  is  occupied  by  the  secondary  sector,  with  labor  productivity  having  a                growing  trend  here.  In  other  sectors,  this  share  is  even  declining.  The  lowest  productivity  is                shown by the non-market tertiary sector. The average rate of growth in labor productivity is 6.3                % in the secondary sector, 5.6 % in the market tertiary sector, 5.2 % in the primary sector and                the lowest, 3.7 %, is in the non-market tertiary sector.                                                  Figure 3: Productivity of labor                                           Source: [5], author.                      The tertiary sector or service sector is labor-intensive and its feature is the dominance of                personnel costs  in  the  cost  portfolio.  [12]  Assuming  the  same  salary  and wage  trends  in  the                economy  as  a  whole,  which  corresponds  with  the  growth  of  the  labor  productivity  in  the                secondary sector, there must be an increase in labor costs in those sectors that do not achieve                such  productivity  growth  with  the  overwhelming  majority  of  them  in  the  tertiary  sector.                According  to  J.  W.  Baumol,  this  will  lead  to  the  relative  cost  per  unit  of  output  in  the  non-                progressive activity sector being raised without limits, while in the technologically progressive                sector it will be constant. The Figure 4 shows the evolution of average gross monthly wages in                the  different  sectors  of  the  economy.  The  growth  rate  of  wages  is  the  same  in  all  sectors,                averaging 6 %.                                                                                          177","Figure 4: Average gross monthly wage                                            Source: [5], author.                      Given that the tertiary sector cannot increase its productivity, but its wages are rising due                to  rising  wages  in  the  secondary  sector,  the  service  sphere  is  becoming  more  and  more                expensive. Services that are deemed necessary become the most expensive; there is no decrease                in demand for them. J. W. Baumol sees the cause of that industrial goods fall into a category of                inferior goods in the developed economy. [1]                      In Figure 5 we can see that the share of expenditure on goods in GDP was above the share                of expenditure on services in GDP, until 2001. While the share of expenditure on goods has a                decreasing trend, (it decreases from 24.2 % in 1995 to 20.6 % in 2017) and the share of service                expenditure is growing (from 20.6 % in 1995 to 22.6 % in 2017).                                         Figure 5: Expenditure on goods and services to GDP                                            Source: [5], author.                                                                    178","The growing share of public expenditure in GDP in terms of the Czech economy has not                been established. This share averaged around 43 % in the period under review. Even though                public expenditure continues to grow, their share of GDP is declining as can be seen from the                Figure 6. This is due to strong GDP growth and the boom in the Czech economy.                                                Figure 6: Public expenditure to GDP                                           Source: [5], [10], author.                  Conclusion                       The aim of the paper was to verify Baumol´s theory on the Czech data and it was found                that the Czech economy shows some symptoms of Baumol´s cost disease. Deindustrialization, as                measured by the share of gross value added of different sectors in total gross value added, was                reflected in a decline in the primary and secondary sectors and the growth of the tertiary sector,                particularly the market sector. Employment has also evolved in the same way. The share of labor                productivity of different sectors in total productivity was growing only in the secondary sector,                again in line with Baumol´s theory. In the tertiary sector, this share should stagnate, but we can                see even decreasing trend. The largest decline in productivity of labor was recorded by the non-                market tertiary sector, which means the public sector. It should be noted that productivity of                labor in it declines despite receiving subsidies from the state budget. This means that if they did                not get these subsidies, the fall in productivity of labor would be even greater.                      According to Baumol´s theory, wage growth is determined by the sector with the highest                growth rate of productivity of labor, and that is the secondary sector. Czech data shows that the                growth rate of wages in all sectors is the same. In the Czech Republic, it has also been noted that                household expenditure on goods in relation to GDP is decreasing while expenditure on services                in  relation  to  GDP  is  increasing,  despite  the  fact  that  services  are  becoming  more  and  more                expensive. This finding is in line with Baumol´s theory, too. Baumol´s theory is most commonly                used to explain the growth in the share of public expenditure on GDP. However, this share has                decreasing  trend  in  the  Czech  Republic.  Although  the  sum  of  public  budget  expenditure                increases, its share on GDP is decreasing. This is due to the faster growth rate of GDP in the                Czech Republic recently. To the same conclusion came Prušvic [13] who introduced a declining                dynamics of labor productivity in the model of the private service sector. This caused a decline                in the public sector´s share of GDP.                      In conclusion, the Czech data confirmed the growing share of the public sector in total                resources (measured by the share of gross value added) but did not confirm the growing share                of public spending on GDP.                                                               179","In  my  further  research,  I  will  focus  on  the  symptoms  of  Baumol´s  cost  disease  in  the                Visegrad countries or in all countries of the European Union and make some comparison. By                regression, I will verify another Baumol´s finding that economic growth leads to an increase in                the share of public sector in total resources, particularly to the growth of public expenditure on                health and education.                   References                 [1.]  BAUMOL,  W.  J.  1967.  Macroeconomics  of  Unbalanced  Growth:  The  Anatomy  of  Urban  Crisis.                     American Economic Review; 57(3):415-426.                [2.]  BAUMOL, W. J. 2013. The Cost Disease: Why Computers Get Cheaper and Health Care Doesn´t. New                     Haven: Yale University Press.                [3.]  CHAPMAN, B. 2003-2010. Baumol´s Disease: The Pandemic That Never Was. Melbourne: Monash                     University. Available on                     https://www.researchegate.net/publication/267424836_Baumol´s_Disease_The_Pandemic_That_Ne                     ver_Was.                [4.]  COBB, K. 2017. Baumol´s Cost Disease, Productivity and the Future of Growth. Available on                     httpe://www.resilience.org/stories/2017-06-04/baumols-cost-disease-productivity-future-                     growth/.                [5.]  Český statistický úřad, 2018. [online] Government finance statistics (GFS). Available on                     http://www.czso.cz.                [6.]  HARTWIG, J. 2008. What Drives Health Care Expenditures? Baumol´s Model of “Unbalanced Growth”                     Revisited. Journal of Health Economics; 27(3):603-623.                [7.]  HARVEY, M. C. 1998. Productivity Gaps and “Cost Illness”: Contributions and Limits of Baumol´s                     Unbalanced Growth Model. Review Economique; 49(2). Available on                     https://www.researchgate.net/publication/249761663_Productivity_Gaps_and_Cost_Illness_of_Will                     iam_J_Baumol´s_Unbalanced_Growth_Model.                [8.]  KEREN, M. 1972. Macroeconomics of Unbalanced Growth: Comment. American Economic Review;                     62(1):149.                [9.]  LESLIE, D. 1993. Advanced Macroeconomics: Beyond IS-LM. London: McGraw-Hill Book Co Ltd.                [10.] Ministerstvo financí ČR. 2018 [online] Vládní finanční statistika. Available on                     https://www.mfcr.cz/cs/verejny-sektor/makroekonomika/statistika-vladniho-sektoru/2007-                     2017/vladni-financni-statistika-13196#5.                 [11.] OULTON, N. 1999. Must the Growth Rate Decline? Baumol´s Unbalanced Growth Revisited. Oxford                     Economic Papers; 53(4):605-627.                [12.] PODAŘIL, M. 2013. Koncept Baumolovy choroby a jeho význam pro veřejnou ekonomii. Brno: ESF MU.                [13.] PRUŠVIC, D., BOREŠ, M. and J. VELIKOVSKÝ. 2006. Příčina růstu veřejných výdajů – mechanismus                     modelu nevyváženého růstu. Praha: VŠE. Available on https://www. kvf.vse.cz/wp-                     content/uploads/2010/…/1168943974_sb_prusvic_bores_velikovsky.pdf.                [14.] ROBINSON, J. 1969. Macroeconomics of Unbalanced Growth: A Belated Comment. American                     Economic Review; 59(4):633.                                                                               180","A Question of State Aid for Sectoral Development in the EU                                                      PODSIADLO Piotr                                               Cracow University of Economics, Poland                                                   piotr.podsiadlo@uek.krakow.pl                 Abstract                 The article presents the conditions of admissibility of State aid in the European Union, taking into account                the rules applicable to the sectoral aid for enterprises. Pursuant to Article 107 par. 3 (c) of the Treaty on                the Functioning of the European Union (TFEU), State aid may be compatible with the internal market in so                far  as  it  is  intended  to  facilitate  the  development  of  certain  economic  activities.  Thus,  aid  that  is                determined according to sectoral criteria may be permissible where this leads to the development of that                sector.  While  many  aid  schemes  are  sectoral  in  nature,  the  European  Commission  has  not  sought  to                develop a sectoral approach in the development of its State aid policy. In general, the main state aid policy                instruments governing horizontal aid, such as the guidelines on regional State aid or the guidelines on                environmental  protection,  draw  no  distinction  between  different  sectors,  other  than  to  restrict  their                application  in  certain  circumstances.  Nevertheless,  certain  sectors  have  been  subjected  to  different                treatment under the State aid rules. In particular, sectors that suffered from over-capacity, such as motor                vehicles, synthetic fibres and textiles were subject to individual treatment by the Commission. The article                offers an analysis of State aid granted  by EU Member  States is carried out under  the provisions of the                Treaty on the functioning of the European Union and the rules of State aid admissibility on the basis of the                implementing sectoral regulations. The analysis made it possible to verify the influence of State aid on                economic growth in EU Member States, which provided State aid for sectoral development in the years                2000-2017.  The  analysis  was  based  on  a  linear  regression  model.  The  response  variable  (dependent                variable  Y)  is  the  size  of  the  GDP,  while  the  explanatory  variable  (independent  variable  X)  is  the                expenditure on State aid for sectoral development.                 Keywords: economic growth; enterprises; the European Union; sectoral development; State aid                JEL Classification: E62, K20, K33                    1  Introduction                       The subject of competition policy usually involves private restrictions of competition – i.e.                concerning possible restrictions of competition by companies – such as through the abuse of                market  power,  through  cartels  and  collusive  behavior,  and  through  horizontal  and  vertical                mergers. A specific characteristic feature of European competition policy is the so-called State                aid control based on Article 107 of the Treaty on the Functioning of the European Union (TFEU).                It  relates  to  possible  distortions  of  competition  through  State  subsidies  to  private  or  public                companies that are in active or potential competition with other companies. Article 107 par. 1 of                the TFEU issues a general ban on State aid. There are, however, exceptions to the rule defined in                Article 107 par. 3 of the TFEU, which allow aid under certain conditions. These categories of                exceptions exist in so-called regional, horizontal and sectoral aid.                      The purpose of this article is to analyse the State aid provided by EU Member States to                finance  sectoral  development,  specifically  the  aid’s  impact  on  economic  growth  of  these                countries. Economic  growth  is  measured  by  the size of  gross  domestic  product  in  real  terms                (GDP), a synthetic measure of the state’s economic well-being. For this article, the years 2000-                2017  were  adopted  as  the  test  period,  i.e.  the  period  during  which  the  two  most  important                development strategies - the Lisbon Strategy and the \"Europe 2020\" Strategy - of the European                Union were implemented (taking the year 2017 as the closing period of observation was due to                the available annual data on State aid, which is published by Eurostat.). It was posited that the                amount of sectoral State aid provided by the EU Member States should be positively correlated                with the size of the economic growth of these countries. If GDP is positively correlated with the                                                               181","size of State aid for sectoral development, then positive economic growth among Member States                occurs as State aid is increased.                  1.1 Literature Review – Sectoral Aid                      From the economic point of view relating to State interventionism it ought to be noted that                State aid  can  be  a  justified  action  mainly  because  of  the  social  prosperity  if free  competition                market mechanism does not bring satisfactory results [2, 4, 10]. In this case, a well-planned State                intervention  may  improve  the  allocation  of  production  factors,  reduce  the  irregularity  in  the                market functioning and enable the achievement of common interest [7, 15]. The major criterion                for  providing  State  aid  should  be  rationality,  which  is  the  highest  determinant  of  the                admissibility of using the aid measures [3, 11]. It results from the fact that in a market economy                the competition is essential for the proper functioning of the market and protecting the interests                of its participants [12, 13]. State aid should not violate it unless its violation will be compensated                by positive market phenomena that were caused by providing the aid. With the use of the aid                instrument  the  State  realizes  the  objectives  that  are  considered  a  priority  for  socioeconomic                development [18].                      Pursuant  to  Article  107  par.  3  (c)  TFEU,  aid  in  support  of  the  development  of  certain                economic activities can be deemed compatible with the internal market, provided they do not                adversely  affect  trading  conditions  to  an  extent  contrary  to  the  common  interest  [17].  The                importance of sectoral aid is on the decline, after the 1980s and 1990s saw a notable increase in                sectoral  aid  in  both  the  production  and  service  industries  as  a  result  of  the  economic                developments – as well as the particular political circumstances in Germany – during that period                [1]. The development of the individual sectors in this respect still varies, however, significantly                between the Member States. The European Commission has basically looked with disfavor on                sectoral  aid  for  a  long  time  now  [9].  It  generally  presumes  that  sectoral  aid  will  distort                competition  more  seriously  than  horizontal  aid.  Sectoral  aid  constitutes  an  exception  to  the                principle  of  inter-sector  neutrality.  Of  course,  sectoral  aid  may  also  serve  on  occasion  to                compensate for undesirable sectoral effects of horizontal aids.                      The European Commission had published as early as 1978 general principles for sectoral                aid together with criteria to be applied in connection with the review of planned aid [8]. The                principles included:                      Firstly, for sector-specific aids, a principle of necessity applies. It is a precondition of every                State aid that conditions in the affected industry make intervention absolutely imperative.                      Secondly, the objective of sector-specific aid aimed at supporting economic sectors with                structural  problems  must  be  the  long-term  structural  restoration  of  viability  to  the  affected                sector. The undertakings and branches of production that benefit from State aid are thus to be                put in a position that it is reasonable to assume they will in the future be capable of maintaining ,                in the face of genuine competition, without State aid. This must be demonstrated in prognoses.                Sector-specific  aids  aimed  solely  at  preserving  the  status  quo  or  postponing  decisions  or                adjustments which are inescapable from an economic standpoint are thus impermissible. Sector-                specific  aids  must  seek  to  ease  the  required  adjustment  to  changed  market  conditions,  for                example  through  reductions  in  capacity  and  the  restoration  of  competitiveness.  Sectoral  aid                may, no more than any other kind of aid, serve as a mere pretense for operational aid.                      Thirdly,  sectoral  aid  is  generally  permitted  only  in  degressive  form  and  for  a  limited                period  of  time.  It  must  be  connected  with  the  restructuring  of  a  whole  branch  of  industry  –                unless granted only for a short period of time.                      Fourthly,  the  aid  intensity  must  be  proportionate.  It  must  limit  the  distortion  of                competition to a minimum. Only in this fashion are the distortions of competition associated                with the State aid acceptable.                      Fifthly,  sectoral  aid  may  not  result  in  the  simple  shifting  of  industrial  problems,  for                example from one Member State to another.                      Sixthly, in connection with structural adjustments, funds may under certain circumstances                be granted for the purpose of alleviating the short-term social costs of such adjustments. Closely                                                                182","monitored operational aid may be conceivable as a crisis measure for narrowly limited periods                of time.                      Seventhly, sectoral aid obligated to pursue the goal of creating as much transparency as                possible in the public financing of the industry affected and thereby to ensure, on a community-                wide level, that competition in the sector is not distorted by one-sided measures.                      This principles basically continue to apply. In the assessment of sectoral aid, moreover, the                general  principles  developed  for  horizontal  aid  (aid  pursuing  trans-sectoral  objectives)  also                apply [16].                      In the case of sectoral rules, the European Commission has identified certain economic                sectors such as coal mining, fishing, agriculture and various other branches of industry that are                considered “sensitive” due to many years of economic problems and are therefore excluded from                the  general  ban  on  State  aid.  The  rules  that  apply  to  these  sectors  are  altogether  very                heterogeneous [14].                      For a group of so-called „sensitive“ sectors, which were historically confronted with severe                structural problems and thus were classified as „sensitive“, some special considerations must be                kept in mind. The following sectors are currently deemed „sensitive“: iron and steel, synthetic                fibers,  motor  vehicles  and  shipbuilding.  The  provision  in  the  area  of  „sensitive“  sectors  are                generally more restrictive than the provisions for other sectors. Investment aids that lead to an                increase in production capacity are generally possible only to a very limited extent, or are even                prohibited. Aid is often permissible only where it is connected with a decrease in capacity. In                almost all sectors, there is an obligation to notify large individual aid grants individually.                      Among the others sectors with special regulations is any industry the promotion of which                is a policy concern of the European Union, and the granting of aid to which the Commission                deems to have a special incentive effect. This is the case, for example, in growth industries and in                the area of environmental protection.                      An  exceptional  form  of  sector  specific  rules  were  the  coordinated  action  to  implement                adequate  support  schemes  and  ad  hoc  measures  to  tackle  the  financial  crisis  and  to  assure                stability  in  the  banking  sector  and  the  broader  financial  system  in  2008/2009.  In  order  to                safeguard  financial  stability,  since  September  2008,  Member  States  have  set  up  guarantee                umbrellas, risk shields and recapitalization measures for the financial sector.                      Moreover,  there  are  sector-specific  legal  frameworks  in  the  agricultural  sector,  the                fisheries sector and the transport sector. In the agricultural sector, the provisions of State aid                apply only to a limited extent, because the Treaty provides that State aid in this field is subject to                the normal competition rules. In the transport sector, special provisions concerning State aid                apply for air, rail, inland waterway and maritime transport, while the general rules apply to road                transport.                      There  are  also  sectors  subject  to  no special  regulations,  for  which  the  Commission  has                however  announced  specific  principles  for  the  application  of  the  competition  provisions.  In                particular, the postal, public health and audio-visual sectors, and, until the financial crisis 2008,                also the financial sector belongs in this category.                  2  Material and Methods                       From the perspective taken in this paper, adopted measure of economic growth is the size                of gross domestic product in real terms (GDP), which is a synthetic measure of the economic                situation in the State [19]. As a test period the years 2000-2017 were adopted, i.e. the period of                implementation of the two most important development strategies of the European Union - the                Lisbon strategy and the \"Europe 2020\" strategy; taking the year 2017 as the closing period of                observation was due to the available annual data on State aid, which is published by Eurostat [5,                6]. The thesis was accepted that the amount of State aid for sectoral development provided by                EU Member States should be positively correlated with the economic growth of these countries.                The  response  variable  (dependent  variable  Y)  is  the  size  of  GDP  in  real  terms,  and  the                explanatory  variable  (independent  variable  X)  is  the  expenditure  on  sectoral  State  aid.  The                                                               183","positive correlation of GDP with the size of sectoral aid would mean that with increasing State                aid  provided  in  this  form  there  is  positive  economic  growth  of  the  Member  States  and  their                competitiveness increases.                      Statistical analysis will be carried out based on two source tables.                      The  first  shows  the  calculations  for  the  linear  regression  model  concerning  the  slope                parameter (directional factor β). The factor b of the regression function II is the estimator of the                parameter  α  β  of  regression  function  I.  The  standard  error     is  the  standard  error  of  the                estimator b of the parameter β. The designations \"Lower 95% \" and \"Upper 95%\" concern lower                and upper limits of so-called confidence interval of numerical values for parameter β, where this                parameter is with a probability of 95%. t Stat is a test of the occurrence of a linear relationship                between  expenditures  on  State  aid  for  sectoral  development  and  the  size  of  the  GDP.  This                statistical  test  makes  it  possible  to  verify  the  authenticity  of  the  null  hypothesis  that  the                parameter of regression function I type β is equal to zero, and the alternative hypothesis that it                is not equal to zero (  : â = 0;   : â ≠ 0). The acceptance of the null hypothesis that parameter β                = 0 would mean that the increase in the value of expenditure on sectoral State aid by € 1 does                not  cause  any  changes  in  the  size  of  the  GDP.  This  in  turn  means  the  lack  of  a  relationship                between expenditure on State aid for sectoral development and the size of the GDP. In other                words,  the  acceptance  of  the  null  hypothesis  means  the  lack  of  the  influence  of  sectoral  aid                provided  by  the  Member  States  of  the  European  Union  on  the  size  of  their  GDP.  Given  the                perspective taken in this paper, it will be essential to reject the null hypothesis in favor of the                alternative - that is, there is a significant statistical relationship between expenditure on State                aid and the size of the GDP. From the tables of critical values of t-Student it is seen that ±  =                ±2.120 for α = 0.05 and n - 2 = 16 degrees of freedom. The null hypothesis can be rejected in                favour of the alternative hypothesis only when:   <   or   >  , that is when – < – 2.120 or                + > +2.120.                      The p-value is the probability of making a type I error. This would involve, based on the                results of the test, the rejection of the hypothesis that the value of parameter β is zero, when in                fact it is zero in the entire population. In other words, a type I error is a rejection of a real null                hypothesis. The higher the value of the t-test means, the lower the probability of a type I error                occurring. In general, it is assumed that if the p-value is less than 0.05, the null hypothesis can be                rejected in favour of the alternative hypothesis, and thus it can be it can be claimed that there is                a statistically significant relationship between the expenditure of EU Member States on State aid                for sectoral development and the size of the GDP of these countries.                      The  second  table  contains  regression  statistics,  including  the  correlation  coefficient,                determination coefficient, standard error and the parameters of the F test - that is, the value of F-                test and the probability of making a type I error, when it is verified that expenditure on State aid                does not impact the size of the GDP (the irrelevance of state aid expenditure in the regression                model). Similar to the t-test described above, the F-test is used to test the significance of linear                regression coefficient β evaluation. Statistic F with F-Snedecor distribution of    and    degrees                of freedom is used to check this test. When rejecting the null hypothesis F >   of no relation                between  expenditure  on  State  aid  and  the  size  of  the  GDP  and  accepting  the  alternative                hypothesis of the existence of a statistically significant relationship between the variables. From                the table of critical values of the F-Snedecor for   = 1 (1 independent variable) and   = n – 2 =                16 degrees of freedom and α = 0.05 we read     = 4.49. Thus, the alternative hypothesis can be                adopted only when: F > 4.49.                  3  Results and Discussion                       The most important statistical test in the simple regression analysis is a test of whether                the regression coefficient equals zero. If it can be concluded that the directional coefficient of the                real regression line in the population equals zero, it will mean that there is no linear relation                between expenditure on State aid and the size of GDP, or expenditure on State aid and the size of                                                               184","GDP are not linearly dependent. Therefore, there should be a test to determine the occurrence of                the linear relation between expenditure on State aid for sectoral development in the Member                States and the size of their GDP. Table 1 shows the statistics on this test.                       Table 1: State aid for sectoral development and GDP – analysis of variance: the line \"variable X\"                               Regression    Standard                 EU  Member                                 t Stat                 States         coefficient    error         tb         p-value     Lower 95%    Upper 95%                                   b            Sb                 Austria         -934.92      687.84       -1.35921    0.192931      -2393.08     523.2367                 Belgium         373.23        94.95      3.930849     0.001194      171.9451     574.5059                 Bulgaria        -673.91      369.56       -1.82354    0.086958      -1457.36     109.5276                 Cyprus          -28.87        2.93        -9.84023     3.44E-08     -35.0865     -22.6485                 Czech                 Republic        1271.92      300.04      4.239189     0.000625      635.8677     1907.976                 Denmark         466.46       141.97      3.285675     0.004658      165.5032     767.425                 Estonia         1223.32      452.05      2.706142     0.015575      265.0101     2181.628                 Finland         1039.34      259.24      4.009218     0.001012      489.7824     1588.904                 France           -0.66        13.10       -0.05069    0.960203      -28.4355     27.10744                 Germany         -118.74       19.43       -6.11212     1.5E-05      -159.931     -77.5605                 Greece          111.32        52.65      2.114288     0.050541      -0.29577     222.926                 Hungary         -24.33        17.23       -1.41232     0.17701      -60.8486     12.18932                 Ireland         -323.66       71.03       -4.55652    0.000323      -474.241     -173.078                 Italy           -36.66        21.53       -1.70217     0.10807      -82.3057     8.995689                 Latvia           24.59        7.49       3.280494     0.004709      8.701258     40.4883                 Lithuania       2192.33      800.28      2.739451     0.014546      495.8106     3888.853                 Malta           -52.36        10.33       -5.06995    0.000114      -74.2486     -30.4647                 Netherlands     193.99       395.34      0.490681     0.630314      -644.122     1032.109                 Poland          -26.47        23.11       -1.14508    0.269016      -75.4739     22.5342                 Portugal        -13.09        3.53        -3.70694    0.001914      -20.5757     -5.60412                 Romania         -175.77       66.23       -2.65405    0.017325      -316.157     -35.3741                 Slovakia        -382.75      123.43       -3.10109    0.006864      -644.399     -121.102                 Slovenia        -46.64       427.07       -0.10921    0.914394      -951.982     858.702                 Spain           -116.72       16.79       -6.94992     3.27E-06     -152.322     -81.1172                 Sweden          447.05       414.31      1.079044     0.296567      -431.234     1325.342                 United          -1583.1      410.33       -3.85799    0.001392      -2452.91     -713.188                 Kingdom                 EU 28           -153.55       42.41       -3.61989    0.002301      -243.465     -63.6247                Source: The author’s own calculations.                      Table 1 shows that for seven Member States (Belgium, Czech Republic, Denmark, Estonia,                Finland, Latvia, Lithuania), the regression coefficient takes a positive value. Consequently, the                increase  in  expenditure  on  State  aid  for  sectoral  development  by  €1  is  accompanied  by  an                increase  in  GDP  by  average:  €373.23,  €1271.92,  €466.46,  €1223.32,  €1039.34,  €25.59  and                €2192.33. Margin of error is: €94.95, €300.04; €141.97, €452.05, €259.24, €7.50 and €800.28.                Bearing  in  mind,  however,  the  confidence  interval  for  the  regression  coefficient,  it  is  nearly                certain (95% probability) that an increase in sectoral State aid of €1 will cause GDP to rise in the                following  countries:  Belgium  from  €171.95  to  €574.51,  Czech  Republic  from  €635.87  to                €1907.98, Denmark from €165.50 to €767.43, Estonia from €265.01 to €2181.63, Finland from                €489.78 to €1588.90, Latvia from €8.70 to €40.49 and Lithuania from €495.81 to €3888.85. It                should also be noted that the probability of type I error (p-value), involving the rejection of a                true null hypothesis that, in the case of these seven countries providing State aid for sectoral                development  do  not  significantly  affect  the  size  of  the  GDP  of  the  countries,  is  below  the                accepted level of significance, i.e. 0.05. The consequence is that the result of the study in relation                to these countries, may be considered important, and thus the null hypothesis can be rejected in                favour of the alternative hypothesis.                      Also  for  9  Member  States,  i.e.  for  Cyprus,  Germany,  Ireland,  Malta,  Portugal,  Romania,                Slovakia,  Spain  and  United  Kingdom,  the  regression  coefficients  take  negative  values,  which                means that the expenditure on State aid for sectoral development have a negative impact on GDP                                                               185","of these countries. The increase in expenditure on sectoral State aid by €1 is accompanied by a                fall  in  GDP  -  respectively  –  with  an  average  of  €28.87,  €118.75,  €323.66,  €52.36,  €13.09,                €175.77,  €382.75,  €116.72  and  €1583.05.  Estimation  errors  are  respectively  €2.93,  €19.43,                €71.03,  €10.33,  €3.53,  €66.23,  €123.42,  €16.79  and  €410.33.  On  the  other  hand  taking  into                account the confidence interval for the regression coefficient it can be with a probability of 95%                said that the increase in expenditure for State aid of €1 will cause fall in GDP by the value of the                interval (€22.65; €35.09) for Cyprus, (€77.56; €159.93) for Germany, (€173.08; €474.24) for                Ireland,  (€30.46;  €74.25)  for  Malta,  (€5.60;  €20.58)  for  Portugal,  (€35.37;  €316.16)  for                Romania,  (€121.10;  €644.40)  for  Slovakia,  (€81.12;  €152.32)  for  Spain  and  (€713.19;                €2452.91)  for United  Kingdom.  For  these  countries  the  probability  of  making  a  type  I  error,                connecting with the rejection of a real null hypothesis concerning lack of relation between the                size of the State aid and the value of GDP, is very small and does not exceed the accepted level of                significance  of  0.05.  Identical  request  as  to  the  proposed  hypothesis  can  be  obtained  by                analyzing  the  value  of  F  test  and  F  significance.  Table  2  shows  the  F-test  parameters  and                regression  statistics  for  the  relationship  between  the  amount  of  State  aid  for  sectoral                development and the value of GDP in the EU countries.                            Table 2: State aid for sectoral development and GDP - regression statistics and F-test                                              Regression statistics                       Test F                 EU Member                 States           Correlation   Determination   Standard error       F         Significance F                                   indicator      coefficient                     Austria       0.321735        0.103514        47357.5       1.847456        0.192931                     Belgium       0.700915        0.491281       41556.14       15.45157        0.001194                     Bulgaria      0.414812        0.172069       11317.39       3.325283        0.086958                     Cyprus        0.926388        0.858194       1176.135       96.83006        3.44E-08                  Czech Republic   0.727328        0.529006       27078.32       17.97072        0.000625                    Denmark        0.634735        0.402888       27613.72       10.79566        0.004658                     Estonia       0.560346        0.313988       4560.235       7.323206        0.015575                     Finland       0.707920        0.501151       19279.64       16.07383        0.001012                     France        0.012671        0.000161       258831.8       0.002569        0.960203                    Germany        0.836743        0.700139       200621.9       37.35804        1.5E-05                     Greece        0.467308        0.218376       26326.45       4.470212        0.050541                    Hungary        0.332937        0.110847        18369.4       1.994652        0.17701                     Ireland       0.751510        0.564767       33634.17       20.76192        0.000323                      Italy        0.391563        0.153322       132761.4       2.897375        0.10807                     Latvia        0.634137        0.402129       4920.474       10.76164        0.004709                    Lithuania      0.565050        0.319282       7947.247       7.504589        0.014546                      Malta        0.785078        0.616347       1331.375       25.70437        0.000114                   Netherlands     0.121758        0.014825       85112.43       0.240768        0.630314                     Poland        0.275215        0.075743       92986.59       1.311208        0.269016                     Portugal      0.679727        0.462029       13775.25        13.7414        0.001914                    Romania        0.552880        0.305676       40227.65       7.043994        0.017325                     Slovakia      0.612706        0.375408       17767.00       9.616738        0.006864                     Slovenia      0.027292        0.000745       6432.851       0.011927        0.914394                      Spain        0.866702        0.751172       80985.31       48.30138        3.27E-06                     Sweden        0.260451        0.067835       69154.01       1.164337        0.296567                  United Kingdom   0.694215        0.481934       182691.7       14.88409        0.001392                     EU 28         0.670999        0.450239       1314746.0      13.10358        0.002301                Source: The author’s own calculations.                       In the case of Belgium, Czech Republic and Finland, one can speak of a strong correlation                of  aid  granted  in  the  agricultural  sector  with  the  amount  of  their  GDP  in  a  positive  sense.                Correlation indicators are equal, respectively 0.70, 0.73 and 0.71. But these models have a weak                fit to the empirical data, as its calculated coefficient of determination is 0.491281, 0.529006 and                0.501151. Therefore, variations in GDP in these countries were explained in 49.13%, 52.90%                and  50.12%  with  variations  in  expenditure  on  State  aid  for  sectoral  development,  while  the                remaining 50.87%, 47.10% and 49.88% result from the impact of other factors.                                                                186","In the case of Denmark, Estonia, Latvia, Lithuania, the values of the correlation coefficient                are  included  in  the  interval  (0.56;  0.63).  These  countries  are  characterized  by  weak  positive                relationship  occurring  between  the  amount  of  provided  State  aid  and  the  level  of  their  GDP.                Moreover, there can be no satisfactory adjustment of the regression line to the empirical data.                The  determination  coefficients  for  these  countries  equal:  0.402888,  0.313988,  0.402129  and                0.319282.                      In the case of Cyprus, one can speak of a very strong correlation of aid granted for sectoral                development with the amount of GDP in a negative sense. The correlation indicator equals: 0.93.                This model has a good fit to the empirical data, as its calculated coefficient of determination is                close to 0.90. For Cyprus determination coefficient is 0.858194. Therefore, variations in GDP in                this  country  were  explained  in  85.82%  with  variations  in  expenditure  on  sectoral  State  aid,                while  the  remaining  14.18%  result  from  the  impact  of  other  factors.  If  the  coefficient  of                determination takes the values less than 0.5, the regression explains only less than 50% of the                variation in GDP and predictions based on such a regression model may be unsuccessful because                the regression model explains then very little. This means that the predictions can be created                basing on the Cypriot model, because the regression model is characterised by a good fit                and  is  little  burdened  with  the  estimation  error,  which  provides  grounds  for  precise                forecasting.                      Germany, Ireland, Malta and Spain are characterized by occurring between the amount of                provided  State  aid  for  sectoral  development  and  the  level  of  GDP,  very  strong  and  strong                negative correlation - respectively 0.84, 0.75, 0.79 and 0.87. In the case of Germany and Spain,                for which the determination coefficient has the highest value, the variability of GDP in the real                terms  was  explained  in  70.01%  and  75.12%  by  variability  of  expenditure  on  State  aid  for                sectoral  development.  The  remaining  29.99%  and  24.88%  is  the  effect  of  random  and  non-                random factors (other non-aid variables, imprecise fit of a straight line to the empirical data                etc.).                      For  Ireland,  Malta,  Portugal,  Romania,  Slovakia  and  United  Kingdom  the  determination                coefficient  assumes  lower  values  and  amounts  to  0.564767,  0.616347,  0.462029,  0.305676,                0.375408  and  0.481934.  This  means  that  there  can  be  no  satisfactory  adjustment  of  the                regression line to the empirical data.                      For  all  countries  of  the  European  Union  (EU-28)  between  the  amount  of  State  aid  for                sectoral  development  and  GDP  in  the  real  terms,  there  is  a  negative  correlation  (r  =  -0.67).                However, the determination coefficient assumes lower values and amounts to 0.450239. This                means that there can be no satisfactory adjustment of the regression line to the empirical data.                  4  Conclusion                       State  fiscal  policy  and  its  consequences,  particularly  tax  policy  implemented  within  its                frames (specifying the implementation of public revenue) and State aid policy (depending on the                instruments of implementation - affecting both the expenditure and the revenue side of public                finance sector), are closely linked with the real economy. The issue here is primarily about the                relationship between the size of and changes in GDP, and changes in public funds. Changes in                GDP affect changes in the revenue of the State budget and of other public funds— that is, the                revenue  of  the entire  general  government  sector.  These correlations  result  from  the  fact  that                taxes and other public levies are part of GDP in revenue terms. Revenue generated in the process                of creating GDP thus affect its consumption, but this correlation is non-linear, because part of the                revenue  is  spent  on  monetary  savings  of  individuals  and  entities  operating  in  the  economic                system, mainly household savings. If these savings are to be transformed into demand for goods,                especially  goods  for  investment  purpose,  many  factors  will  come  into  play,  particularly  the                credit policy of banks or other financial system players whose function is to transform savings                into capital provided to enterprises.                      In the process of creation and distribution of GDP a significant function is performed by                the State, which by taking in the form of taxes and other public levies some part of the revenue                                                               187","generated  by  households  and  enterprises,  changes  the  structure  of  aggregate  demand  in  the                economy. The taxes imposed on enterprises limit their investment opportunities, but revenues                from  taxes  and  other  levies  are  directed  by  the  State  to  both  households  (social  assistance,                unemployment benefits, scholarships etc.) and to enterprises (State aid in the form of grants),                forming  the  basis  of  demand  for  consumer  goods  and  investment  goods.  State  expenditure                policy, which includes the policy of State aid to enterprises, can thus give an impulse to GDP                growth and increase the indicator GDP per capita (growth of competitiveness of the national                economy) even if the State spends more money than the accumulated revenue in the budget.                This situation means the appearance of budget deficits, which accumulation in the coming years                leads to the formation of public finance sector debt. The source of financing deficits, and as a                result  public  debt,  are  domestic  monetary  savings,  relatively  foreign.  This  process  is                accomplished by a loan taken out by the state in the form of debt securities, which buyers are                banks,  investment  funds,  insurance  companies,  etc.,  that  is,  institutions  that  accumulate                monetary savings of the economic system entities, mainly households. Fiscal policy therefore                plays  an  important  role  in  economic  growth,  especially  in  a  situation  where  enterprises,                commercial  banks,  for  various  reasons,  e.g.  increased  risk  of  capital  loss,  are  not  willing  to                support  real  economic  processes  (investment  processes)  and  economic  growth.  The  savings                accumulated  in  commercial  banks  and  other  financial  institutions  are  thus  borrowed  by  the                state,  which  creates  the  demand  for  consumer  goods  and  investment  goods,  consequently                stimulating the processes of economic growth.                      Sectoral aid may pursue various objectives. Aid for the benefit of the coal mining industry                and certain manufacturing sectors serve either mainly to cushion the social impact of structural                changes in connection with the decline of an industry, or to combat unfair price competition in                the  worldwide  dockyard  industry.  In  contrast,  the  majority  of  aids  in  certain  service  sectors                benefit those branches whose importance are steadily growing, such as tourism, or liberalized                sectors such as air transport and financial services.                      In  the  case  of  growth  industries,  the  Member  States  are  being  encouraged  to  provide                support particularly in the area of research and development. Of primary importance, however,                are  those  industries  experiencing  structural  crises  and  difficulties  in  adapting  to  a  changed                environment. This applies in particular to the shipbuilding industry. The European Commission                here takes the view that aid should be approved where it is necessary to promote or accelerate                essential  changes  or  developments  in  the  industry,  to  make  a  smooth  adaptation  of  specific                industrial activities possible, or at least to neutralize distortions of competition that have been                brought about by measures taken outside of the European Union.                      The  proposed  research  thesis  in  the  paper,  according  to  which,  both  in  relation  to  the                European Union and its individual Member States, the amount of expenditure on State aid for                sectoral development is positively correlated with the rate of GDP should be rejected. It cannot                be  considered  as  a  true  the  thesis  that  with  increasing  the  amount  of  sectoral  aid  the                competitiveness of the EU economy increases. It was incorrect to assume that this correlation                occurs for all Member States, because of the amount spent on State aid for sectoral purposes are                very different at the level of individual Member States. Different is also the proportion of aid                actually granted in the aid approved by the European Commission.                      The  above  outlined  description  of  the  relation  between  the  real  sphere  and  the  fiscal                sphere is necessarily greatly simplified. It provides a subject for theoretical investigation and                empirical analysis, while econometric models, which aim to quantify these relations, combine                them in a cause-and-effect structure. It is essential that these relations be ascertained with the                analysis  of  such  policy  aid  -  concerning  regional  goals,  sectoral  and  broadly  understood                horizontal goals - conducted within the framework of fiscal policy used by a given State or group                of  EU  Member  States.  Presented  in  the  article  regression  analysis  of  State  aid  with  sectoral                objective  in  the  field  of  development  and  GDP  contributes  to  comparative  studies  among                countries  conducting  fiscal  policy  in  the  conditions  of  the  single  monetary  policy  and  the                countries outside the euro area.                                                                  188","Acknowledgements                       The publication was financed from means granted to the Faculty of Finance and Law of                Cracow University of Economics, in framework of subsidy to keeping the research capacity.                  References                 [1.]  Bacon, K. 2009. European Community Law of State Aid, Oxford-New York: Oxford University Press.                [2.]  BIONDI, A. 2013. State Aid is falling down, falling down: An analysis of the case law on the notion of                     Aid. Common Market Law Review; 50(6): 1719-1743.                [3.]  BUMANE, I. 2017. Favourable tax regimes that constitute selective state aid from the perspective of                     the cjeu recent case law. European Research Studies Journal; 20(3): 231-245.                [4.]  CRAFTS, N. 2017. Brexit and State aid. Oxford Review of Economic Policy; 33: S105-S112.                [5.]  Eurostat, 2019. [online] GDP and main aggregates. European Commission. Available on http://                     appsso.eurostat.ec.europa.eu/nui/show.do?dataset=naida_10_gdp\&lang=en                [6.]  Eurostat, 2019. [online] Aid by main objectives. European Commission. Available on                     https://webgate.ec.europa.eu/comp/redisstat/databrowser/view/COMP_SA_X$COMP_SA_01/defau                     lt/table?category=COMP_MAIN                [7.]  FERČIČ, A., SAMEC, N. 2014. European Union state aid law and policy, and local public services. 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[12.] PISAPIA, A. 2015. The role of EU state aid policy in enhancing the development of the industrial                     sector. Privredna Kretanja i Ekonomska Polityka; 23(123): 45-64.                [13.] PODSIADŁO, P. 2016. Regional State Aid and Its Impact on the Competitiveness of the EU Member                     States. In: Kovářová E., Melecký L., Staníčková M. (Eds.): Proceedings of the 3rd International                     Conference on European Integration. Ostrava: VŠB-Technical University of Ostrava, Faculty of                     Economics, 771-781.                 [14.] QUIGLEY, C. 2009. European State Aid Law and Policy. Oxford-Portland: Hart Publishing Ltd.                [15.] STÖLLINGER, R., HOLZNER, M. 2017. State Aid and Export Competitiveness in the EU. Journal of                     Industry, Competition and Trade; 17(2): 203-236.                [16.] TOSHKOV, D. 2008. Embracing European Law. Compliance with EU Directives in Central and Eastern                     Europe. European Union Politics; 9(3): 379-402.                 [17.] Treaty on the Functioning of the European Union (TFEU). Consolidated version. Official Journal of                     the European Union C 202/2016.                [18.] TUNALI, Ç.B., FIDRMUC, J. 2015. State Aid Policy in the European Union. Journal of Common Market                     Studies; 53(5): 1143-1162.                [19.] WALASIK A. 2015. Wrażliwość dochodów jednostek samorządu terytorialnego na wahania cyklu                     koniunkturalnego. Kwartalnik Kolegium Ekonomiczno-Społecznego. Studia i Prace; 3/4 (23), Szkoła                     Główna Handlowa, Warszawa.                                                                  189","Costs and Benefits of the Dual Vocational Training System                                      and its Use in the Czech Republic                                                              a                                PROVAZNÍKOVÁ Romana , CHLEBOUNOVÁ Denisa                  b                                Faculty of Economics and Administration, University of Pardubice, Czech Republic                                       a                       b                                       romana.provaznikova@upce.cz,  denisa.chlebounova@upce.cz                Abstract                 Apprenticeship  in  the  Czech  Republic  suffers  from  poor  quality,  low  motivation  of  pupils  to  complete                successfully this type of  education, and high unemployment rate of  graduates.  Dual vocational training                system seems to be a possible solution to these problems. This system is increasingly seen as an important                educational  track  that  provides  youth  with  the  skills  necessary  for  a  smooth  transition  into  the  labor                market.  However,  the  practical  part  of  the  dual  system  provided  by  companies  brings  the  cost  for                companies that hire apprentices. Because apprentices become part of a company’s workforce, they also                generate a benefit from working productively. The aim of this paper is to analyze costs and benefits of the                dual system and to estimate the net costs of training hypothetical company in the Pardubice Region. Based                on the resulting net costs of this hypothetical company, company's investment in apprenticeships should                start  returning  in  the  second  year,  and  the  benefits  should  outweigh  the  costs  in  the  third  and  fourth                years, too. Further, by correlation and regression analysis, we found that there is a statistically significant                influence of length of practice in the company on youth unemployment rate and completion rate of upper                secondary school pupils. The importance of time spent in training company has been confirmed.                Keywords: dual vocational training system; apprenticeship; costs; benefits; training company                 JEL Classification: I220, H410, I290                    1  Introduction                      The  most  frequent  problems  of  upper  secondary  education  in  the  Czech  Republic  are                discussed in upper secondary vocational schools, especially in apprenticeships. In this type of                schools,  the  quality  of  teaching  is  very  low  and  this  education  is  very  uneconomical  or                inefficient: consumption of high finance without added value in the form of successful graduates.                There is a high degree of failure in this study, a high number of upper secondary school pupils                leaving this education system before passing a final exam [5]. Apprenticeship graduates show                the highest unemployment rate in the labor market [8]. Research [13] shows that one of the                most  frequent  employers'  demand  is  the  practice  of  applicants.  However,  apprentices  spend                little time in the real work environment in the Czech Republic. Practical training time takes an                average  of  63  -  68  days  in  the  1st  -  3rd  year  in  this  type  of  education.  As  a  disadvantage,                employers also indicate the length of time that graduates need to integrate when starting work.                      The solution to these problems can be the implementation of the dual vocational training                system. In this case, practical training would take place in the real economy, companies could                shape the apprentices' professional profile according to their needs and this preparation would                be the first real \"practice\" of apprentices. The dual system could ensure consistency between                supply  and  demand  in  the  labor  market.  According  to  Deissinger  and  Hellwig  [4],  the  dual                system  is  an  institutional  framework,  which  is  subdivided  into  two  learning  venues:  the                company or master providing on-the-job training (the actual apprenticeship) and the part-time                vocational school where the apprentice receives theoretical instruction. Germany’s dual system                of  training  provision,  which  has  a  long  history,  has  become  a  key  inspiration  for  vocational                training reforms around the world. Hamilton [6] and Senker [17] state that countries such as                France and Britain see the German system of vocational education and training as “a model to                copy”.  From  a  financial  point  of  view,  the  dualism  is  reflected  in  a  shared  responsibility  for                funding between companies and state governments.                                                               190","Vocational education and training (VET) provides useful skills to improve youth chances                of  a  successful  professional  career  [11].  In  particular,  by  aligning  the  initial  education  more                closely  to  particular  vocations  and  tasks  demanded  in  the  labor  market,  the  problem  of                mismatch, often seen as a main source of the high degree of unemployment in countries, may be                reduced [1].                      The  aim  of  this  paper  is  to  analyze  costs  and  benefits  of  the  dual  system  based  on                experience in countries where this system is used. Within this objective, the net costs of training                hypothetical small or medium-sized enterprise (SME) in the Pardubice Region will be estimated.                Length  of  practice  seems  to  be  a  key  factor  in  the  success  of  graduates  in  apprenticeship                education. By correlation and regression analysis, we find out whether there is a statistically                significant  influence  of  length  of  practice  on  youth  unemployment  rate,  GDP  per  capita,  and                completion rate of upper secondary school pupils.                  2  Material and Methods                       The substantial benefit of dual system is the smooth transition of young people between                school and employment, where young people often get their first jobs in companies where they                have practiced, which has impact on the youth unemployment rate. Another positive feature is                the high rate of successful completion of upper secondary education, and the country with a dual                system  also  achieves  higher  GDP  per  capita  (but  this  indicator  is  influenced  by  many  other                factors, including the mentioned unemployment rate). These statements are illustrated by the                following Table 1, which highlights the countries that use the dual system for their vocational                training.                                                Table 1: Benefits of the dual system                                     Relative youth           Completion rate                                                                           Employment rate of graduates of                       Country     unemployment rate   GDP per   of upper   upper secondary vocational schools                                     (15-24 years)    capita   secondary         (20-34 years) in %                                        in %                education (in %)                     Austria             1.8        44 152.2     94.4                   89.2                     Belgium             2.7        41 713.9     89.6                   72.2                     Czech Republic      2.7        31 808.6     77.6                   87.5                     Denmark             1.9        45 704.2     92.6                   82.8                     Finland             2.3        39 710.5     96.2                   77.0                     France              2.4        37 648.2     93.8                   64.0                     Germany             1.8        44 108.1     91.6                   91.3                     Hungary             2.6        25 842.4     87.4                   85.9                     Netherlands         1.8        48 020.0     93.4                   86.9                     Poland              3.0        26 154.7     85.2                   75.2                     Slovak Republic     2.3        29 931.0     83.8                   81.6                     Spain               2.2        33 729.2     80.2                   58.5                     Sweden              2.7        45 535.1     74.0                   87.8                     Switzerland         1.7       54 690.8      95.2                   85.1                     Great Britain       2.8        39 338.6     91.8                   82.0                Note: Completion rate of upper secondary education measures the number of pupils entering the upper secondary level                and complete this program within a given timeframe; Relative youth unemployment = share of unemployment rate by                age group 15-24 years old and unemployment rate by age group 15-64 years old.                Source: Education at a Glance 2017, Eurostat, OECD.Stat.                       To prove that the dual system (expressed as the time spent in practical training in the                company) is causing the aforementioned benefits, we used correlation and regression analysis,                where the dependent variable were selected relative youth unemployment rate, GDP per capita                and  completion  rate  of  upper  secondary  education  and  independent  variable  represents  the                                                               191","time  spent  in  practical  training  in  the  company.  According  to  Kubanová  [9]  the  correlation                analysis is used to determine the extent to which variables interact. The Spearman's correlation                coefficient was performed in this paper. Regression analysis is used to describe the dependence                of two or more numerical variables. It is a mathematical model that is expressed by a regression                function. We used simple regression model. Simple regression describes the dependency of the                explained variable on one independent variable (one regressor).                      An  important  contribution  to  the  state  is  also  the  involvement  of  more  actors  in  the                financing of the dual system. Vocational training in schools is funded from public sources, but                vocational  training  in  companies  is  paid  directly  by  employers.  In  Slovakia,  Germany,  the                Netherlands  and  Austria,  companies  can  reduce  the  corporate  income  tax  base.  E.g.  in  the                Netherlands, a company has the option of applying a tax allowance of € 2,500 for each job filled                by the apprentice, whereby companies spend € 8,400 on average per apprentice per course. So                the bulk of the company's training is still covered by the company itself. A similar situation exists                in  Austria  or  Germany,  where  most  of  the  costs  of  training  in  dual  education  are  borne  by                employers [3].                      For companies involved in dual education, it is important that they will earn a return to                their investment in training to compensate for costs, which they have to bear [18]. Training costs                (e.g. personnel expenses, training workshops, machines, materials, apprentices' remuneration,                etc.) must as far as possible be covered by the productive performance of apprentices within the                time of training. Dual education must be paid economically to the company at least from medium                and long term, so that companies are willing to offer places to this education.                                         Figure 1: Productive performance of apprentices (%)                                             Source: Rauner [16].                       From  this  picture  and  according  to  Potter  [14]  it  is  clear  that  competencies  and                productivity of apprentices increase over time. Companies that provide dual education, cover                their need for professional staff, are becoming more independent on the labor market, thereby                increasing their competitiveness. These companies are also gaining recognition and improving                their image.                      As  Lerman  [10]  says,  dual  system  provides  a  very  strong  signal  for  detecting  skills                shortages  identified  by  enterprises.  Also  valuable  is  employers’  increased  certainty  that                apprenticeship graduates know all the relevant occupational and company-specific skills, and                can work well alongside other skilled workers. The high level of occupational mastery achieved                                                                 192","by  apprentices  may  also  increase  the  pace  of  innovation  and  the  ease  of  implementing  new                technologies.                      When estimating the costs and benefits of training hypothetical company in the Pardubice                Region,  we  use  the  methodology  of  Hanushek,  Machin  and  Woessman  [7].  The  calculation  of                training  costs  suggests  that  they  are  mainly  determined  by  wages.  In  addition,  there  are                expenses  for  material,  infrastructure,  external  courses,  costs  for  hiring  and  administration  of                apprentices, and other (X). Briefly, the gross costs (C) of an apprentices (i) at a training site (j)                and in an apprenticeship year (t) comprise primarily the apprentice’s wages (aw), the trainers’                wages (bw), and the material expenses (X) involved in providing the training (see formula 1). We                consider that material expenses account for 15 % of total costs. We base on the situation, that                personnel  costs  already  constituting  about  85  %  of  the  total  gross  cost  of  training  in  most                countries with a dual system [19]. The number of training years is n. For simplicity, there is no                discounting.                                                                                                         (1)                       The  benefits  (B)  derived  by  the  company  from  training  during  the  training  period                comprises  the  production  generated  by  the  apprentices.  The  benefit  is  calculated  on  the                assumption  that  the  productive  work  done  by  an  apprentices  would  be  performed  by  either                skilled or unskilled workers. Allowance is made for the possibility that not all of the work of                apprentices is productive and that some apprentice time is spent on exercises. The benefit is                broken  down  into  production  activities  that  would  otherwise  be  performed  by  unskilled                workers  (PI)  and  skilled  workers  (PII).  It  is  assumed  in  the  first  case  that  the  apprentice’s                performance has the same value as that of the average unskilled employees. In the second case,                the value of the apprentice’s performance (relative productivity) is estimated by comparison to                that of fully skilled workers (γ). The values of the apprentice’s work has to be adjusted by a                relative productivity measure (we use the data from Figure 1), since apprentices are not yet as                efficient as a skilled worker with a vocational degree. Type I production is multiplied by the                wages paid to an unskilled workers (uw), while for type II the wages paid to a skilled workers in                the relevant occupation (pw) are used (we use the average annual wages in the Pardubice Region                for 2017 for auxiliary and unskilled work and for craft and repair work as a skilled work). As is                to  be  expected,  the  proportion  of  type  I  productivity  (α)  varies  according  to  the  year  of                apprenticeship  and  in  general  declines  as  the  apprenticeship  progresses,  while  the  share  of                skilled work, with higher apprentice productivity (γ), increases as the training proceeds. The                benefit is counted according to the following formula:                                                                                                       (2)                        The net costs of apprenticeship training (NC) are the difference between the costs (C) and                the benefits (B):                                                                                                     (3)                         We  used  the  Slovak  Act  no.  61/2015  on  Vocational  Education  and  Training  (Dual                Education) to modify this general calculation procedure. We have applied the rules of this law                for  determining  apprentices'  remuneration,  the  tax  savings,  and  contribution  to  training                apprentices  from  the  state.  This  contribution  is  paid  once  in  Slovakia  on  30  June  for  each                apprentice to which company has provided practical training in a dual education system. For                                                               193","SMEs,  the  amount  of  the  grant  is  set  at  €  1000/apprentice.  This  Slovak  Act  introduces  the                elements of the dual system, not the dual system in the pure form, such as in Germany. This                country was chosen because of the similarity with the Czech Republic, i.e. a similar historical and                economic development, and similar problems in the labor market. For our calculation, we used                small or medium-sized enterprise because this category has the largest numerical share of all                companies in Pardubice region (99.14 %). The percentage of SMEs for the whole Czech Republic                is very similar (99.84). However, the vast majority of these companies are small companies. The                small size category means that these companies have between 0 and 49 employees, medium-                sized companies have 50 - 249 employees and large companies have more than 250 employees.                  3  Results and Discussion                       First, we find out whether there is a statistically significant influence of length of practice                on the above-mentioned benefits of the dual system from Table 1. We performed correlation and                regression analysis. The results of correlation analysis are shown in Table 2. The correlation                coefficients were determined for confidence intervals of 95 % and 99 %.                           Table 2: Impact of time spent in practical training in the company on selected variables                                                                             Time spent in practical                                                Indicator                                                                             training in the company                            Time spent in practical training in the company (in %)   1.000                            Relative youth unemployment rate (15-24 years) in %      -0.624**                            GDP per capita                                          0.211                            Completion rate of upper secondary education (in %)       0.908***                 Note: statistically significant values that are significant: *** at a confidence interval of 99 %; ** at a confidence interval of                95 %, * at a confidence interval of 90 %.                Source: Authors.                       From the correlation coefficients, the time spent in practical training in the company has a                strong negative impact on the relative youth unemployment rate (r = -0.624), and very strong                positive impact  on  the completion rate of upper secondary education  (r =  0.908). These  two                significant variables entering the regression model. The value of the determinant coefficients for                the following statistically significant indicators are as follows: 0.480253 for the relative youth                unemployment  rate,  and  0.609027  for  completion  rate  of  upper  secondary  education.  The                regression  analysis  results  show  that  indicators  explain  the  model  with  a  relatively  high                percentage. Relative youth unemployment is influenced by the time spent in practical training of                48 %, and in the case of completion rate of upper secondary education it is about 61 %.                      Table 3 represents the estimated costs, benefits and resulting net costs of the hypothetical                company in the Pardubice Region. This company trains six apprentices. This number is based on                the assumption that our hypothetical company uses 1 instructor for practical training and one                instructor  can  lead  at  the  same  time  a  maximum  of  6  apprentices  (according  to  Czech                legislation). Number of apprentices may be arbitrary for the calculation methodology, depending                on the company's personal and material capabilities. Years are defined as calendar years from                the perspective of the company but the 3-year length of the curriculum is considered (the first                year  begins  on  1  September  and  the  fourth  year  ends  on  30  June).  Considered  number  of                training hours of apprentices in the company is given in brackets for each year. Total number of                training hours for all four years is 1 400. This number of hours is the lowest possible for dual                education according to the Slovak Act mentioned above.                                                                       194","Table 3: Net training costs by year of hypothetical company                                                          (in CZK)                                                          1st year     2nd year     3rd year    4th year                                Period                                                        (186 hours)   (467 hours)   (467 hours)  (280 hours)                  Costs                  apprentices' remuneration               32 779        92 771      119 538      81 626                  Trainers’ wages                         35 293        88 611      88 611       53 129                  Material expenses                       12 013        32 009      36 732       23 780                  Total costs                             80 085        213 391    244 881      158 535                   Benefits                  Production generated by the apprentices   58 521      173 704     251 845     185 161                  Tax savings                               0           94 348      94 348       47 174                  Contribution to training apprentices from   0         155 178       0            0                  the state                  Total benefits                          58 521        423 230    346 193      232 335                   Net costs                               - 21 564     +209 839    +101 312     +73 800                 Note: tax savings = absolute tax savings after the application of a flat-rate tax of EUR 3 200 per pupil or EUR 1 600 per                pupil according to the number of hours of training provided per year.                Source: Authors.                      The  resulting  net  costs  over  the  reference  years  show  that  the  initial  investment  in                apprentices will return to the company for the second year. In the second year, however, the                excess of benefits over costs is mainly due to a contribution to training apprentices from the                state. From the second year, company can also use a tax deduction from its tax base. You can see                that the benefits from production generated by the apprentices are increasing with increasing                time and apprentice’s remuneration are rising, too. This growth is due to increasing productive                performance of  apprentices  (Figure  1).  From  the  calculation  follows  that the more  hours  the                company  provides  in  dual  education,  the  greater  the  net  benefits  it  achieves.  Because  of  the                increasing productivity of apprentices (increasing benefit), training company has an interest in a                sufficiently  long  training  duration  to  recoup  its  initial  training  investments  as  apprentices                become more productive later in the training period. Put differently, the amount of training that                company is willing to provide increases with increasing training duration [15].                      The  costs  and  benefits  of  apprenticeship  training  are  an  important  determinant  of  a                company’s decision to hire apprentices, which Mühlemann [12] for Germany and Switzerland                dealt with. He found that German company on average makes a net investment of EUR 5 400 per                year per apprentice, the average Swiss firm generates a net benefit of EUR 2 300 per year per                apprentice. Two factors explain this difference. First, the relative pay of apprentices is around                twice as high in Germany as in Switzerland. Second, there are marked differences in the tasks                allocated to apprentices when they work in production. German apprentices spend more time                doing practice exercises, Swiss ones doing productive work, and particularly doing skilled tasks.                It has to be noted that, in contrast to our research, this research was carried out on the already                existing dual education in companies. Mühlemann calculated the average costs and benefits of                3  032  companies  in  Germany  and  2  518  companies  in  Switzerland.  We  used  the  same                methodology with slight differences given by the Slovak Act.                      Wolter  and  Mühlmann  [19]  simulated  the  hypothetical  costs  and  benefits  of                apprenticeship training for the case that Spanish companies were to start dual apprenticeships                similar  to  Switzerland  or  Germany.  The  simulations  show  that  there  would  be  at  least  one                scenario for each of the analyzed occupations so that training companies could reach the break-                even  point  by  the  end  of  the  training  period  (i.e.  without  having  to  rely  on  post-training                benefits).  A  potentially  important  component  of  post-training  benefits  are  savings  on  future                                                                195","hiring  costs.  Retaining  apprentices  upon  completion  of  their  training  eliminate  the  costs  of                externally recruiting and familiarizing new skilled workers. Blatter, Mühlemann and Schenker                [2] show that average hiring costs range, depending on company size, from 10 to 17 weeks of                wage payments. Larger companies have higher rents, which authors explained by longer average                interview times.                      Small companies can expect smaller net training benefits or may have to bear net costs,                while  larger  companies  can  expect  net  benefits.  This  pattern  leads  to  a  situation  in  which                medium-sized  and  larger  companies  are  more  likely  to  offer  training  than  small  companies.                From  the  calculation  methodology  used  follows  that  the  more  number  of  apprentices  the                company  employs,  the  lower  the  net  costs  reaches.  Employing  more  apprentices  can  afford                larger  companies.  Large  companies  with  numerous  apprentices  have  the  possibility  of                economies of scale and training costs reduction. Because small companies are the backbone of                the economy in many countries (case of the Czech Republic), special incentives, such as access to                training funds and technical assistance with the training of tutors are important [19].                  4  Conclusion                       Our research has confirmed the importance of the length of practice in company within                the  vocational  training.  Correlation  and  regression  analysis  showed  that  the  time  spent  in                practical  training  in  the  company  has  statistically  significant  negative  impact  on  the  relative                youth  unemployment  rate  and  positive  impact  on  the  completion  rate  of  upper  secondary                education. However, the limit of this analysis is the need to consider the results with caution                because there might be some other different factors affect the youth unemployment rate or GDP.                Estimated costs and benefits of training hypothetical company in the Pardubice Region consists                of  two  main  components.  First,  the  costs  that  arise  during  the  training  period  (apprentice’s                wages,  trainers’  wages,  material  expenses);  second,  the  benefits  that  company  can  generate                during the training period by letting apprentices substitute unskilled and skilled workers (saved                wages of unskilled  and  skilled  workers -  production  generated  by  the  apprentices).  It  is  also                calculated  with  tax  savings  and  with  one-time  contribution  to  training  apprentices  from  the                state. Based on the resulting net costs of this hypothetical company, company's investment in                apprenticeships should start returning in the second year, and the benefits should outweigh the                costs in the third and fourth years, too. The net costs also depends on the size of the company -                the  larger  the  company,  the  lower  the  net  costs  and  the  higher  the  benefits.  The  share  of                medium-sized companies in the total number of companies in the Czech Republic is only 0.7 %.                Most companies are small companies. The dual system in its pure form, as it works in Germany,                is difficult to apply for this reason. A solution would be the cooperation of schools with several                companies. In small companies, there is a further risk that not all employers are able to train                apprentices all activities and skills required by the graduate's profile and some employers use                obsolete  production  facilities.  When  employing  small  companies  for  apprenticeship  training,                they need to be financially supported by the state. Also in our calculation, state funding in the                form of tax savings and contribution to training apprentices appears to be a key factor in the                excess of  benefits over costs.  From  this  point of view,  the  dual system  seems  very costly  for                public finance. However, it is necessary to consider the significant benefits that are difficult to                quantify.  For  example,  a  smoother  transition  of  graduates  to  the  labor  market,  ensuring  the                needs of the labor market, or limiting non-prospective fields. The limit of this analysis is the fact                that  the  estimated  costs  and  benefits  of  a  hypothetical  company,  not  a  real  company  are                calculated. At present, the introduction of the dual system as a solution to problems of vocational                education  is  discussed  topic  in  the  Czech  Republic.  Pilot  projects  are  currently  underway,                introducing  elements  of  the  dual  system.  Also,  some  companies  are  actively  seeking  to  work                more closely with apprentices because of a lack of labor force. Further research could analyze                the costs and benefits of the dual system of these involved companies and get more realistic                results.                                                                 196","References                 [1.]  ALMEIDA,  R.,  BEHRMAN,  J.,  ROBALINO,  D.  2012.  The  right  skills  for  the  job?  Rethinking  training                     policies for workers. The World Bank.                [2.]  BLATTER, M., MÜHLEMANN, S., SCHENKER, S. 2012. The costs of hiring skilled workers. European                     Economic Review; 56(1):20-35.                [3.]  CEDEFOP, 2011. [online] The benefits of vocational education and training. Luxembourg:                     Publications Office of the European Union. Available on                     http://www.cedefop.europa.eu/files/5510_en.pdf                [4.]  DEISSINGER, T., HELLWIG, S. 2005. Apprenticeships in Germany: modernising the dual system.                     Education+ Training; 47(4/5):312-324.                [5.]  EDUin, 2018. [online] Audit vzdělávacího systému v ČR: rizika a příležitosti (2017). Available on                     http://www.pedagogicke.info/2018/01/eduin-audit-vzdelavaciho-systemu-v-cr.html                [6.]  HAMILTON, S.F. 1999. The lmpact of Apprenticeship on Youth: A Prospective Analysis. Social                     Interactions in Adolescence and Promoting Positive Social Contributions of Youth; 6(4):427-455.                [7.]  HANUSHEK, E.A., MACHIN, S.J., WOESSMANN, L. 2016. Handbook of the Economics of Education.                     Elsevier.                [8.]  INFOABSOLVENT.CZ, 2018. [online] Nezaměstnanost absolventů z hlediska úrovně vzdělání a                     skupin oborů vzdělání. Available on http://www.infoabsolvent.cz/Temata/ClanekAbsolventi/5-1-                     05/Nezamestnanost-absolventu-skupiny-oboru-vzdelani                [9.]  KUBANOVÁ, J. 2008. Statistické metody pro ekonomickou a technickou praxi, Bratislava: Statis.                 [10.] LERMAN, R. 2014. [online] Do firms benefit from apprenticeship investments?. IZA World of Labor.                     Available on https://wol.iza.org/articles/do-firms-benefit-from-apprenticeship-investments/long                [11.] MALCOMSON, J.M., MAW, J.W., MCCORMICK, B. 2003. General training by firms, apprentice contracts,                     and public policy. European Economic Review; 47(2):197-227.                 [12.] MÜHLEMANN, S. 2016. The Cost and Benefits of Work-based Learning. OECD Education Working                     Papers, No. 143, OECD Publishing, Paris.                [13.] POSPOLU, 2013. [online] Spolupráce středních škol a firem - zaměstnavatelů při odborné výuce,                     odborném výcviku a odborné praxi žáků středních a vyšších odborných škol. Available on                     http://www.nuv.cz/uploads/POSPOLU/Zprava_dotaznikove_setreni_skoly_FIN.pdf                [14.] POTTER, M. 2013. Apprenticeships in Germany. Northern Ireland Assembly, Research and                     Information Service Briefing Paper 30.                [15.] QUINTINI, G., MARTIN, S. 2006. Starting well or losing their way?: The position of youth in the labor                     market in OECD countries (No. 39). OECD Publishing.                [16.] RAUNER, F. 2008. Kosten, Nutzen und Qualität der betrieblichen Ausbildung. Innovative                     Berufsbildung–Auf die Attraktivität für Jugendliche und Unternehmen kommt es an; 43-71.                [17.] SENKER, P. 1995. Training levies in four countries: implications for British industrial training policy.                     University of Sussex, Science Policy Research Unit.                [18.] STEEDMAN, H. 2007. Adapting to globalised product and labour markets, Institute for Futures                     Studies.                [19.] WOLTER, S.C., MÜHLEMANN, S. 2015. Apprenticeship training in Spain – a cost effective model for                     firms. Bertelsmann Stiftung, Guetersloh.                                                                             197","Talent Management in Public Healthcare                                                  ROBAKIEWICZ, Wioletta                            Warsaw University of Technology, College of Economics and Social Sciences (Plock), Poland                                                  wioletta.robakiewicz@gmail.com                 Abstract                 Talent  management  has  gained  more  and  more  attention  in  recent  years;  however,  current  research                focuses mainly on developing concepts, constructions and definitions. Despite numerous studies, talent                management  has  not  been  the  subject  of  extensive  research  in  reference  to  different  types  of                organizations.  In  healthcare  organizations,  the  demand  for  highly  qualified  employees,  who  can  be                considered as talents, is emphasized. Employees with exceptional abilities are a valuable, rare and sought                after resource. Until now, studies on talent management in healthcare organizations are rare, and the need                for  such  research  is  self-evident.  Difficult  economic  conditions  and  strong  employment  trends  are  a                serious  challenge  for  talent  management  in  healthcare  organizations.  Specialists  in  the  field  of  talent                management in healthcare have to constantly pursue three strategic goals: cost reduction, improvement of                patient satisfaction and improvement of patient safety. The purpose of this article is to assess the current                state of talent management in healthcare organizations and the steps that can be taken to move closer to                the high impact talent management function. The methodology was based on the analysis of the literature                on the subject concerning public healthcare organizations in the world and own research. Effective talent                management can help health care organizations save time, money and reduce inefficiencies.                Keywords: talent management; public healthcare; hospitals.                 JEL Classification: M12, M54, I15, O15, J24                    1  Introduction                       Recently scientific research has been paying special attention to talent management. This                is  very  interesting  because  of  its ability  to create  and  maintain  competitive  advantage of  the                entities [3, 14]. Talent management is one of the processes of human resources management,                which  has  lately  become  the  point  of  special  interest.  This  process  looks  a  bit  different                depending on the definition of talent and on what the organisation wants to achieve through this                management. There are two approaches: the first one focuses on the key, outstanding employees                called talents; the other one focuses on all employees, treating each of them as a potential talent.                Talent  management  is  described  as  a  complex  process,  which  includes  recruitment  of  right                candidates (that is war for acquiring talents), their retention at company and providing them                with chances for development and promotions. The process of talent management is supported                by  information  systems  and  applications  enabling  better  exploitation  of  potential  of                organizations. Basically, talent management is associated with creation of a bank of talents from                internal and external sources, appropriate usage of those resources in key positions and further                work  on  motivation,  organizational  engagement  and  other  behaviour  patterns,  which  are                important for the results of an organisation [13]. This perception of talent management focuses                on  replacing  the  concept  classical  approach  with  human  resources  management. This  means                that the entity that wants to actively engage talents in organisational life, has to find the ways of                utilising  their  own capabilities  and  preparing  a  strategy to  encourage  its  own  outstanding                employees to contribute to the organisational success.                      Despite a growing interest in the research in this area, there is not much knowledge about                the  ways  in  which  public  organisations,  especially  public  healthcare  entities  manage  their                talents. This article was created to fill up this gap and its objective was to analyze the literature                studies on talent management in public healthcare entities. This aim was accomplished in two                stages. Firstly, there was research on the latest literature on the subject of talent management                and  the  directions  in  which  the  scientific  debate  is  carried  on.  Secondly,  the  review  of  the                                                               198","empirical  research  was  conducted  in  selected  public  healthcare  entities  in  the  world,  own                research and theoretical as well as practical implications were formulated.                   2  Material and Methods                       Methodology  is  based  on  the  analysis  of  the  literature  about  public  health  care                organisations  around  the  world.  Having  in  mind  that  public  healthcare  organisations  are                absolutely  crucial  for  the  society,  the  results  of  the  research  done  on  the  management  of                extraordinary employees in the world health care organisations were presented in this article.                Effective  talent  management  may  help  public  health  care  organisations  to  reduce  the  lack  of                efficiency and save time and money. The literature related to talent management was identified                in a number of ways. A targeted review of the literature over the past ten years was undertaken                at the beginning of the research. This was supplemented throughout the duration of research by                continuous monitoring of other relevant internet based information sources.                      The review of the literature on talent management (books and press publications) was                commenced by the author in October 2018. The searches were done using also the following                databases:  EBSCO,  Scopus,  ProQuest  and  Web  of  Science.  The  first  search  strategy  used  the                following  search  terms:  \"talent  management\",  \"human  capital  management\",  \"human  capital                development\" and \"human resource planning\". However, this generated several thousand hits.                As a result, it was decided to use the singe term \"talent management\" and limit the search to the                previous 20 years of publications in order to identify the key documents on the subject.                      To  verify effectiveness of  talent management in  public  healthcare,  the  review  of  recent                research  done  by  the  entities  from  around  the  world  was  performed.  In  total,  I  collected  38                documents on the subject. The results of these analyses will be discussed in the next section.                      My own empirical research was based on three semi-structured interviews, conducted in                health  care  organizations  in  Poland  in  the  Mazowieckie  Voivodeship.  On  the  basis  of  the                literature  studies  I  prepared  the  research  questionnaire  regarding  talent  management  in                healthcare organizations. The data was collected by means of interviews on the basis of open-                ended question. In every organization the respondents were employees with deep knowledge                about organizational strategies, policies and practices. The study finished in December 2018.                   3  Results and Discussion                       There  are  a  few  interesting  scientific  paths  taken  by  scientists  in  the  area  of  talent                management. This article presents only a fragment of this diversity to emphasise its significant                impact  on  the  considerations.  This  allows  creation  of  theoretical  background  for  this  area  of                research.  It  is  crucial  to  define  the  concept  of  talent  and  character  and  essence  of  talent                management.                      The definition of talent is interpreted differently by particular authors. Talent is deemed to                denote a person who has appropriate predispositions and abilities [11]. From the psychological                point of view talent is an individual who is aware of his unique predispositions and interests                more than an average person. They are able to notice the relation between own features and                possibilities of education and career [1]. Such a person consciously takes care of their strengths                and  notices  their  impact  on  their  future  development  [32].  In  wider  approach,  a  talent  is  a                person, who exhibits creativity, extraordinary skills, professional commitment, satisfaction from                achievements  and  self-improvement  [4].  The  relation  between  talent  and  realisation  of                organisational  goals  is  often  emphasized  as  well.  Talent  is  a  person  who  has  potential,                motivation, skills and knowledge, thanks to which they have an impact on functioning of the                organisation by achieving extraordinary results. That individual achieves entrusted goals and                simultaneously  takes  care  of  their  own  development  [23].  The  definition  of  a  talent  can  be                viewed from different perspectives, treating it as: competences appreciated by the organisation                or group of people, predispositions crucial for success of that individual, taking actions that will                help to discover and develop outstanding features [7].                                                               199","Comparative analysis of definitions of talent leads to the following conclusions:                      ·  Skills  and  potential  are  the  main  characteristics  of  talent.  The  other  ones  are                         motivation, value system and practical skills.                      ·  The actions characteristic for a talent are: creation, composition, inspiration, innovative                         behaviour  and  positive  impact  on  other  people. In  terms  of  mental  processes:                         sensation, perception and understanding.                      ·  A talent has impact on: the organisation, afterwards on broadly defined effectiveness of                         the employee and later on development in conjunction with passion.                       Analysis  of  the  literature  shows  that univocal  definition  of  talent is  difficult.  Therefore,                there are many possibilities and each of them will be correct if it takes into account the needs of                an organisation [32].                      To investigate this definition in context of talent management it is crucial to remember to                interpret  talent  not  only  as  a  person  who  represents  extraordinary  abilities  but  also  an                employee who through their engagement and self-development contributes to the success of the                organisation.                                             Table 1: Definitions of talent management                 Author        Definition of talent management                 Wellins, Smith,  Recruitment, development, promotion and retention of talents, planned and pursued according to                 Mc Gee        present and future goals of the organisation.                 Clake, Vinkler   Action including identification, development, retention and utilisation of talents in context of the                               given organisation.                 Listwan       A set of actions regarding outstandingly talented people, taken with regard to their development                               and abilities and achievement of goals of the organisation.                 Amstrong      Process of identification, development, recruitment, retention and deployment of talented people.                 Lawler        Attraction of actual talents and helping them to understand the expectations about their work for                               the  organisation.  It  is  also  providing  them  with  development  experiences  that  contribute  to                               organisational strength and key competences, thanks to which it is possible to retain actual talents.                 Cappelli      Process in which employees anticipate and fulfil their needs related to growth of human capital.                 Davis         Talent management means recruitment and appropriate training and development of employees                               and also retention of the employees achieving excellent results. The strategy of talent management                               is a well-defined, structured approach of the organisation in terms of recruitment, retention of the                               employees and also training and development of skilled individuals in the organisation.                 Blass         Additional processes of management and possibilities available to people that are talents in the                               organisation.                 Silzer, Dowell   Integrated set of processes, programmes, cultural standards in the organisation that were created                               and implemented to attract, develop, build up talents with a view to achieving strategic goals and                               fulfil future business needs.                Source: Own study based on [2, 5, 7, 8, 12, 15, 27, 28, 34, 37].                       Diversity and a high number of possible interpretations of talent management makes it                very difficult to choose one definition as the most appropriate. It is more sensible to distinguish                a few main perspectives, from which we can investigate talent management [5]:                      ·  process  perspective  -  in  this  perspective  it  is  believed  that  future  success  of  the                         organisation depends on having the right talents;                      ·  cultural  perspective  -  this  perspective  perceives  talent  management  as  an  essential                         element to achieve success;                      ·  competitive perspective - from this perspective talent management is to identify talents                         and to offer them better conditions than competitors;                      ·  development  perspective  -  according  to  this  perspective  talent  management  is  a                         stepped-up career path for employees with high potential;                      ·  HR planning perspective - means putting right people in right positions in a specific                         time;                      ·  change  management  perspective  -  this  perspective  uses  talent  management  as  the                         element that stimulates changes.                                                                200","Despite  many  debates  on  this  topic,  there  has  not  been  much  attention  paid  to  talent                management in public sector so far [19, 26].                                      Table 2: Talent management in medical entities in the world                     Country                      Conclusions                 United States   American medical schools devote time and resources to development of leaders- doctors. Talent                               management programs are a chance for the future of medical entities.                 Great Britain   The research done in British hospitals shows that talent management is the key to improving the                               situation in health care.                 Poland        The  research  on  talent  management  in  health  care  organisations  are  rare  whereas  demand  for                               such research is enormous.                 China         In China talent management in the global chain of values is undergoing development. The country                               wants to decrease shortages in the number of health care employees.                 Pakistan      The research results suggest that medical entities have to devise appropriate practises in terms of                               management of talented workers. Such actions may help them achieve their desired objectives.                 Slovakia      The  key  positions  in  many  health  care  organisations  are  not  held  by  persons  with  proper                               competences. Despite the growing popularity of talent management it is not a commonly used tool                               in Slovakian organisations.                 Finland       The  problems  related  to  recruitment  and  retention  of  employees  encourage  medical  entities  to                               develop new recruitment and leadership as well as talent management practices.                Source: Own study based on [9, 18, 21, 24, 30, 31, 33].                       Public healthcare as a part of economic environment is characterized by growing demand                from customers and commonly understood and accepted mission. The result of activity of both                public  and  private  healthcare  organisations  is  operation  for  the  society  as  part  of  health                improvement  and  lifesaving.  In  order  to  function  healthcare  organisations  must  operate                according  to  the  law.  Realisation  of  the  primary  goal  -  to  help  people  in  need  -  and  its  own                business  needs  as  well  is  becoming  very  challenging  for  those  institutions.  Having  an                appropriate number of employees providing the highest quality care is a guarantee of success.                To  enable  every  member  of  staff  to  broaden  their  competences  in  terms  of  the  latest  trends                contributes to the growth of healthcare entities. It was estimated that total labour expenses in                this branch make up 60-70 % of the operational costs. It is and additional capital strain. The                above mentioned conditions justify the need of effectiveness and productivity improvement of                healthcare employees.                      The total expenses on public healthcare in the main regions of the world till 2020 will                stand  at  8.7  billion  USD,  growing  from  7  billion  USD  in  2015[16]  (figure  1).  The  expenses                presented  in  the first  graph  will  be accelerated by  development  of  the market, ageing  of  the                society, technological progress, clinical development and increasing labour costs.                                             Figure 1: Health care spending 2015-2020                                       Source: Own study based on: [38].                                                               201","Specialists  in  talent  management  in  public  healthcare  sector  believe  that  three  main                strategic  goals  should  be  pursued:  cost  reduction,  improvement  in  patient  satisfaction,                improvement in patient safety [17].                      Increased  workload  is  an  everyday  reality  for  all  employees  in  healthcare  institution.                Through the initiative of human resources related to the improvement in process efficiency and                retention  of  employees,  costs  are  reduced  by  these  organisations.  According  to  the  research                done by a leading supplier of software and advisory solutions in talent management in public                healthcare entities - 74% of respondents are going to improve the processes in human resources                management whereas 69% of respondents with a view to reducing costs are going to implement                the initiative to retain employees [20]. Leave of a qualified employee equals approximately twice                as much as the first-year salary of a newly employed one. A qualified employee provides the                institution with previously acquired skills [22].                      Respondents  of  the  survey  carried  out  in  2014  by  a  leading  provider  of  software  and                advisory solutions in talent management in health care entities - Healthcare Source, need to deal                with competitive initiatives (67%) and low budget initiative management (49%). Based on the                opinion  of  49%  of  respondents  of  that  survey  inappropriate  technology  is  a  very  important                problem as well. Specialists in human resources management in healthcare entities are aware of                huge  potential  of  the  technology.  The  respondents  have  identified  the  technologies  of                effectiveness  management  (30%)  and  e-learning  contents  (25%)  as  factors  improving  the                technology  contributing  to  strategic  achievements  as  far  as  talents  are  concerned.  ‘Human                Resources management and education can see each other through a glass wall, but their actions                are often not integrated’. The healthcare sector is constantly changing. The process results from                 the evolution of regulations, policy, care models and above all a growing demand for medical                services. Based on the recent surveys [17], we can say that talent management specialists in                healthcare  organisations  will  always  expect  more  for  less.  The  annual  analysis  of  the  results                Healthcare  Source  shows  the  main  goal-  providing  services  more  effectively  for  the  lowest                possible  costs.  A  consequence  of  this  is  a  growing  interest  in  automation  of  technological                processes and reduction of manual labour strain.                      With a view to recruiting talented employees to provide patient-oriented care healthcare                institutions in rely on skills and sacrifices of the recruiters. They try to create a team that always                attempts to provide the highest quality services. The key role belongs to doctors, nurses, medical                assistants  as  well  as  the  professional  staff:  receptionists,  administrators  and  internship                managers. Everyday work of staff varies from place to place, but the main task is invariable- to                provide efficient functioning of a healthcare institution (e.g. hospitals). The persons having to do                with administration may expect increase of employment by 23% until 2022 [6]. This result is                much higher than national average for majority of professions in the USA. This growth reflects                an increasing demand caused by ageing society and technological development, that contributes                to the prolonged life expectancy. Such a health care system requires new hospitals, clinics and                also a higher number of doctors and healthcare personnel as well as administrators. The USA                expect an increase in employment in healthcare sector until 2026. Approximately 4 million new                positions will be created, which stands for one third of overall employment increase [25].                      My own empirical research was based on three semi-structured interviews, conducted in                health care organizations in Poland in the Mazowieckie Voivodeship.                      Public hospital A - The hospital determined the key positions in the organisation, however,                the employees holding them can hardly ever be described as those attaining best results. The                decisions  regarding  particular  workers  in  the  examined  entity  were  largely  made  based  on                subjective opinions. Human resources management is affected by trade unions. The hospital is                preparing the talent management program. The organisation reveals a need to conduct talent                identification.  The  study  proves  that  trainings  should  be  classified  among  the  activities                undertaken for talent management.                      Public hospital B - The talent management program is in its early development. The reason                is  relatively  modest  policy  and  practices  in  terms  of  human  resources  management.  The                organisation runs crippled talent identification and promotes persons achieving good results.                The  management  believe  that  anyone  to  have  revealed  appropriate  competences  and                                                               202","achievements in the past may be given a chance to take up a major position in the organisation.                However,  the  key  positions  for  the  medical  entity  are  determined  for  medical  roles  with                administrative ones being overlooked. The results of the study show that talent management                oriented  activities  are  related  to  trainings,  employee  assessment  and  a  number  of  internal                recruitments.  The  talent  management  program  in  place  enables  improvement  of  employees’                knowledge and skills. The trainings focus on the needs of the organisation whereas individual                needs of particular workers are inferior to them.                      Public  hospital  C  -  The  hospital  attempts  to  improve  its  human  resources  and  talent                management is perceived as going beyond.                                     Table 3: Talent management in Polish public medical entities                         Organisation         Public hospital A     Public hospital B      Public hospital C                      Advancement in talent         Under                In force             Does not exist                     management program         preparations                         Key positions         Doctors, nurses   Doctors, nurses, diagnosticians   Doctors                    Talent management tools       Trainings    Trainings, system of employee   Do not exist                                                                   assessments, internal                                                                      recruitments                   Objectives of an organisation   Program      Improvement in the practices   Planning of a talent                  regarding talent management   implementation            run             management program                           program                Source: Author                       The  study  conducted  by  myself  reveals  that  inclusion  of  talent  management  in  Polish                public medical entities means that managements tend to perceive workers as similarly capable                of holding key positions as well as equal chances for all the staff employed by the organisation. It                is also worth noticing that trade unions in public medical entities are very effective in pushing                their opinions regarding the issue of human resources management within organisation-based                decisions.                   4  Conclusion                       To sum up, talent management in Polish public medical entities is at its early development                stage. In the future talent management development is bound to vary depending on the financial                capacity  of  such  entities.  In  public  organisations,  trade  unions  will  still  have  a  tremendous                impact  on  talent  management.  They  will  influence  the  ability  of  the  management  to  take                significant decisions in this respect. As far as the transfer of solutions between countries and                organisations  is  concerned  it  is  obvious  that  medical  entities  will  adjust,  the  practices  and                policies created in other organisations for their own needs. In the future Polish medical entities                should concentrate on identification of their own needs as employers. Healthcare sector units                should realise to what degree talent management has an impact on employees’ achievements                and their retention. The key to a success for a medical entity is to retain the identified talents                among their workers.                      Talent management is one of the key challenges for organisations worldwide in a dynamic                and volatile market environment requiring a response that is both quantitative (enough health                professionals) and qualitative (with the adequate level of skills) [29].                      Despite the many years of ongoing discussion, the issues of talent management in public                healthcare organisations are still important and valid. Success in recruitment and retention of                talented  employees  improves  the  position  of  a  healthcare  institution  and  contributes  to  the                quality  of  the  services  provided.  That  translates  to  a  high  level  of  patient  safety  and  their                satisfaction as well as improves the organisation. Unfortunately, the limited size of this article                does not enable presentation of equally interesting models of talent management.                                                                 203","One limitation of this article is the lack of intercultural research, which would relate to the                issues connected with safety and health in the world and analysis of the main factors affecting                qualified employees’ decisions to move from developing to highly developed countries. This kind                of research surely would strengthen the potential of the reflections that aim to boost the efforts                to retain talents. Such actions would increase the stability of the global chain of values in the                public  healthcare.  Nonetheless,  it  seems  that  this  analysis  may  be  a  valuable  voice  in  the                discussion about talent management in public healthcare institutions, and the presented issues                may be a starting point for both further research and implementation of practical solutions in                the organisations.                  References                 [1.]  ACHTER,  J.A.,  LUBINSKI  D.  2005.  Blending  Promise  with  Passion.  Best  Practices  for  Counseling                     Intellectually Talented Youth, (Eds.): BROWN, S.D. LENT, R.W. Career Development and Counseling.                     Putting Theory and Research to Work, Wiley, Hoboken NJ, 602.                [2.]  AMSTRONG, M. 2011. Zarządzanie zasobami ludzkimi, Wolters Kluwer, Warszawa, 503.                [3.]  ASHTON, C., MORTON, L. 2005. Managing talent for competitive advantage: Taking a systemic                     approach to talent management. 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The CEO’s Guide to Talent Management: Building a Global                     Leadership Pipeline, PA: Development Dimensions International, Pittsburgh, s. 2.                [38.] World Industry Outlook, 2017. Healthcare and Pharmaceuticals, The Economic Intelligence Unit,                     June.                                                                            205","Use of Cost Effectiveness Analysis in Health Care.                                     Towards Efficiency in Health care?                                                    ROZMARINOVÁ Jana                                  Faculty of Economics and Administration, Masaryk University, Czech Republic                                                 Jana.Rozmarinova@econ.muni.cz                 Abstract                 Cost-effectiveness (CEA) analysis is one of the measures how to inform decision-makers on the allocation                of public resources. Though it was used when considering allocating resources in the public programs, it                was  later  implemented  in  health  care  economics,  and  it  has  become  a  basic  economic  analysis  when                implementing economic analysis in the health care sector. The role and impact of CEA have its importance                and is dealt with in the context of Healthcare resources. Our study aims at an examination of using the                Cost-Effectiveness Analysis in health care. As a methodology, the literature review is used. The objective of                our  study  is  to  overview  the  knowledge  about  CEA  in  health  care,  its  suitability  for  the  health  care                intervention evaluation and to find arguments, which contribute to the debate on cost-effectiveness (CE)                thresholds. Our results show that the ICER should not be the single criterion for decision-making.                 Keywords: Cost-effectiveness analysis, economic evaluations                JEL Classification: O11, I15                    1  Introduction                       No matter on the system of the financing what we can observe over the last decades is the                rapidly  rising health care  costs.  The share of health care  expenditure  in  GDP  rises  rapidly  in                most countries in Europe. Technological Change on Health Care involving both diagnostics and                treatment has been the driving force behind the rapid growth of health care expenditures [22].                This trend resulted in searching a concept, which balance the cost of care, and the quality of care,                the aim of the concept is to compare alternative interventions and to assess the relative cost-                effectiveness. CEA is the leader of economic analysis, the cost-effectiveness analysis (CEA). In                this paper, we aim at the CEA, a concept that can help to make the public finance sustainable                when  concerning  health  care  cost  and  is  one  of  the  key  elements  of  Health  Technology                Assessment.                      To bring this issue into a wider context, we should first answer the question, why public                economists  deal  with  Health  care,  its  financing  and  further  with  improving  efficiency.  Malý                shows the main sources of the inefficiency in the health care sector, the consequences of market                failure,  (well-known  characteristics  of  healthcare  markets,  which  was  firstly  described  by                Arrow, especially the externalities in health care market and asymmetric information) [1, 11].                The market failure approach to understanding the role of the government is largely a normative                approach.  Further  Malý  states  the  second  source  of  inefficiency  -  state  interventions.  The                realised  amount  of  health  care  (services)  is  higher  at  a  higher  marginal  cost  than  it  would                correspond to the market optimum [11].                      The reviews of the literature are currently quite a standard tool of research, but not the                reviews of research on Cost-effectiveness analysis in Health care. A literature review for using                CEA in health care was performed quite a long time ago by Warner and Hutten in 1980 and by                Klarman (1982) [10, 20]. To fill that gap in the literature, in this study we analysed published                studies in the journal database, which address uses of the CEA. The purpose of our study is to                investigate prior research in a field of CEA analysis, this approach is important as this reveals the                current state of the knowledge and offers the guidance to researchers who are seeking this topic                to  explore  (Karatas,  2008).  More  specifically,  the  following  research  questions  (RQ)  are                addressed.                                                               206","RQ1: What are the discussed strengths and weaknesses of CEA in the studies published?                      RQ2: What type of thresholds is preferred and why?                      The aim of our study is to identify in the literature strengths and weaknesses of CEA.                  1.1 Background                      The CEA is one of the basic economic analyses which may be part of the evaluation of new                technology  by  pointing  out  the  consequences  of  allocating  resources  to  new  programs  (cure,                health care intervention, …). Even if the CEA was primarily used when considering allocating                resources  in  the  public  programs  later  it  was  implemented  in  health  care  economics.  The                beginnings  of  CEA  and  concept  of  \"threshold”  was  probably  initially  used  by  Weinstein  and                Zeckhauser in 1973 at first [21].                      In the case of CEA, the health benefit can be defined and measured in natural units (e.g.                years of life saved, deaths prevented, life-years gained and QALYs) and the costs are measured in                money.  It,  therefore, compares  therapies  with  qualitatively  similar outcomes in  a  therapeutic                area.  CEA  is  the  most  commonly  applied  form  of  economic  analysis  in  the  literature,  and                especially pharmacy. The disadvantage of the cost effectiveness analysis is it that it does not                allow  comparisons  between  two  different  areas  of  medicine  with  different  outcomes.  Cost-                effectiveness analysis (CEA).                      The „incremental cost-effectiveness ratio (ICER)“ is a statistic used in cost-effectiveness                analysis to summarize the cost-effectiveness of a health care intervention. It is defined by the                difference in cost between two possible interventions, divided by the difference in their effect. It                represents  the  average  incremental  cost  associated  with  1  additional  unit  of  the  measure  of                effect. The ICER can be estimated as:                         Where     and    are the cost and effect in the intervention group and where    and                are the cost and effect in the control care group. If we use a verbal formulation of the formula,                we state that ICER is given by the difference in costs between two health care programs divided                by the difference in outcomes between the programs                      The  aim  of  CEA´s is  to  improve  the  health  of  populations.  CEA  evaluates  the  costs  and                health  effects  of  interventions  and  summarizes  the  results  in  cost-effectiveness  ratios,  for                example, the cost per year of life gained. A general measure of health outcome, such as life-years                or  quality-adjusted  life-years  QALYs),  makes  it  possible  to  compare  very  different  health                interventions  [16,  19]. When  we  need  to  simplify  the  model  so  we  can  state  that  the  CEA  is                concerned  with  health  care  intervention  of  program  which  requires  a  comparison  of  one                intervention with an alternative method of dealing with the patients in a given health state. The                alternative method may be some other treatment and we usually call it the comparator (it can be                no treatment at all). It is very important to note that a cost-effectiveness analyse must state the                two interventions that are being compared. The main results of a CEA – are cost–effectiveness                ratios.                      The CEA is not the only possible economic analysis in Health care, but it is the leader of                them. Other analyses are Cost of Illness, Cost minimization, Cost Consequence and Cost-Utility                and Cost utility analyses. Tab. 1 shows on the frequency of the individual economic method in                academic  publications,  it  summarizes  the  results  of  our  investigation.  ‚When  searching  the                expression “Cost  of Illness”  (resp. “cost  minimization  analysis”,)  in column  “title”, “AND”  was                used in column “connector” a “health care” in column “topic”. The searching was not limited by                the year of publication output. The results show the CEA is by far the most numerously and it                appears with nearly 5 times higher frequencies than CUA or CBA.                                                                       207","Table 1: Web of science, frequency of results to individual methods                                           Analysis type            Result                                           Cost of Illness             30                                           Cost Minimization           62                                           Cost-Effectiveness        1,109                                           Cost Consequence            38                                           Cost-Utility               256                                           Cost Benefit               215                                           Budget Impact               58                Source: Authors.                       The number of CEAs in the literature continues to grow at an impressive rate e.g. [7, 21,                18]. But the question is, if these analyses are being performed properly with the aim to inform                decision makers and which limits it brings with it. In our paper, we want to fulfil this research                gap.                  2  Material and Methods.                       In  review  studies,  various  methods  are  used  by  researchers  to  select  manuscripts.                Examples  include  selecting  from  important  journals  within  the  field  or  selecting  all  articles                published within the leading journals of the field (Karatas, 2008).                      For this review, we selected scientific articles on the uses of CEA, published in journals                that are indexed in the SSCI database. We employed this method because it is easy to access the                field such as topic and research area (The Web of Science site WOS) was the point of access. In                WOS, we used the advanced search function, and input the search terms “Cost effectiveness “and                “health care “. We searched the expression “Cost effectiveness” in column “title”, “AND” was used                in column “connector” a “health care” in column “topic”. The searching was not limited by the                year  of  publication  output.  Moreover,  the  searching  for  scientific  articles  was  performed  in                Databases J – stor and Google Scholar were used to identify the articles, the duplicities were                excluded. Finally, we selected 11 articles for the purpose of our study.                      As mentioned above the core of our research is based on literature review of literature                sources. The methods of deduction and synthesis of acquired knowledge were used to identify                research  outcomes.  The  last  part  of  this  paper  has  normative  character  and  contains                recommendations for further research in this area.                  3  Results and Discussion                       O´Brien (1994) concentrated on the difference of two approaches to CEA, he reminds that                uncertainty of the CEA arises because the true cost and effectiveness of an intervention are not                known  but  estimated,  where  the  estimations  can  be  derived  from  direct  measurement  or                indirect measurement which includes expert´s opinion. O'Brien's study is concentrated on the                two approaches to CEA Analysis, in his study we do not find evidence on the debate on the CEA                threshold [12].                      According  to  Russell  et  all  (1996),  the  cost-effectiveness  analysis  could  be  used  in  the                development of medical and public health practice. The societal perspective is emphasised in the                study.  CEA  analysis  is  understood  as  an  aid  to  decision  making  which  provides  valuable.                Information  about  health  resources  allocation.  The  study  emphasises  which  health  outcomes                and  costs  are  relevant  and  how  they  should  be  valued.  Study  pint  out  the  principles  which                should  be  followed  to  a  good  solution  (using  Quality-adjusted  life  year  -  QALY  weights  from                surveys is recommended). A note to this study is the fact that the study was not fully available                and only abstract was assessed for our analysis [16].                                                                  208","Table 2: Authors and research founding                 Study                   Research result                 O'brien,             -   Two general approaches to CEA, the deter-ministic models and prospective                 (1994)                  stochastic analyses, no debate on decision making and CEA threshold                  Russell et all       -   CEA does not reflect every element of importance in health care decisions but the                 (1996)                  information  it  provides  is  critical  to  informing  decisions  about  the  allocation  of                                         health care resources                  Power, Eisenberg     -   Issue  of  “timing”  of  CEA  is  discussed  (results  for  early  stage  of  using  medical                 (1998)                  technology and routine used later can differ substantially)                  Eichler et all       -   CE thresholds are expected to emerge in many countries                 (2004)               -   soft thresholds with upper and lower boundaries are prefer to rigid implementation                                         of a single CE criterion                                      -   transparency should be ensured                  Donaldson            -   the economic evaluation may not give a clear-cut result                 (2002)               -   the analysts should highlight the potential opportunity costs involved                  Russell              -   the cooperation between the CEA analysts and decision maker is extremely needed                 (2016)                  to serve the needs of public health decision                  Bertram              -   fixed cost–effectiveness threshold should never be used as a stand-alone criterion                 (2016)                  for decision-making.                                      -   Cost-effectiveness ratios have useful informative value                                      -   a  broader  context  supported  by  legislation,  stakeholder  and  patient’s  groups  is                                         needed.                Source: Authors.                      Eisenberg and Power (2004) examine the issue of timing of CEA for new technologies and                the issue if the CEA should be performed at the beginning of an intervention life cycle or later.                The problem is that the results for the early stage of using medical technology would be much                different than when the CEA is performed in a later life cycle of it when the intervention is a                daily routine, daily used [7].                      Eichler  (2004)  aims  at  the  concept  of  a  threshold,  a  ration  between  monetary  costs                (national currencies) and a measure of health gain. The decision rule than use a critical reaction                as a constrained (ICER). By results, its study the thresholds should have a soft upper and lower                boundary against the rigid implementation of singe CE criterion [5].                      Donaldson´s (2002) study is one of those, which sounds more critic to CEA. The author                points out to studies where not all factors have been taken in mind in CEA. Authors of the study                examined articles in MEDLINE database and found that CEA is often misused especially in the                sense  of  the  calculating  incremental  cost-effectiveness  ration.  “We  contend  that,  beyond  the                classic approach, many studies labelled as cost-effectiveness analyses of health care are not that                at all. At best, this mislabelling is confusing: at worst, conclusions drawn by the studies' authors                could  be  harmful  to  patients'  health.  Thus,  there  are  contraindications  to  the  use  of  cost-                effectiveness analysis in health care, and an alternative economic approach is required.” Authors                recommend  that  the  economic  evaluations  should  pay  more  attention  to  implications  for                opportunity cost [4].                      Russell (2016) emphasises that the solution must be developed out of a consensus among                analysts  and  decision  makers.  The  benefits  and  costs  should  always  be  presented  in  a                disaggregated way so that decision-makers can clearly see the components [15].                      Bertram (2016) evaluates CEA as a useful instrument for decision in health sectors, but he                remains that more criteria than only CEA thresholds should be taken in mind, e.g. the health loss.                The  study  points  out  that  cost-effectiveness  ratios  should  be  informative  but  further,  the                                                                209","affordability  and  budget  impact  should  be  taken  in  mind  when  deciding  on  health  care                interventions which will be paid from public sources [3].                      If we concentrate on the literature, where economic analysis, in general, are performed,                and CEA is as part of it, we can furthermore identify the following issues, which we summarise in                table 3.                                              Table 3: Authors and research founding                 Study              Research result                 Baltussen      -   Problem obtaining the necessary data to carry out the economic evaluations is emphasized                 (2003)         -   The information which it provides are decisive in informing decisions about the allocation                                    of health care resources                  Ross           -   The affecting the decisions made within the healthcare sector, the link between economic                                    evaluation and health policymaking has been missing                 (1995)                 Johannson      -   From  public  choice  perspective,  the  costs  and  benefits  face  the  actual  decision  makers                                    differs from the cost and benefits usually included in economic evaluations                 (1991)                  Fiedberg       -   Risk of bias analysis.                 (1999)                Source: Authors.                  4  Conclusion                       The  CEA  analysis  the  most  popular  approach  and  answer  to  the  issue  that  medical                research  continues  to  produce  an  increasing  number  of  innovations;  however,  budgetary                constraint does not allow using all of them.                      We concentrated on the literature, which proposes recommendations for the use of CEA                and  tried  to  identify  strength  and  the  weakness  to  consider  more  attention  when  the  CEA                analysis  is  performed  or  interpreted.  From  the  practical  issues  we  can  highlight  that  more                attention should be paid when the cost was estimated, the relevant health outcomes and cost                should be considered and last but not least the problem obtaining the necessary data to carry                out appear.                      To the debate about the ICER, most of the authors agree, that ICER should not be the only                criterion for the decision (or not a rigid ICER should be used, soft thresholds with upper and                lower boundaries is preferred).                      Some author criticises the CEA concept with the examination of performed studies. They                show on the low quality of studies or biased CEA studies. As far as the critical remarks about the                cost-effectiveness analysis, we point to the work of Donaldson [4].                       Mentioned above show that undoubtedly the CEA should be an aid to decision making                (and not only a domain of researchers – analyst), but the challenge to more transparency and                consistency in the decision-making process arises. Moreover, some contradictory issues (should                the ICER to be a rigid or soft boundary?) show that some issues of cost-effectiveness assessment                remain the subject for debate and challenge for future research.                      The opinion of the author reflects the fact that many factors influence the results of cost–                effectiveness  analyses  (which  data  was  used;  which  comparator  was  chosen).  Then  the                variations  in  the  inputs  can  cause,  that  the  results  of  the  analysis  can  significantly  differ                according to the choice of inputs. The analyses may not reflect the problem accurately, sufficient                local capacity for the appraisal of economic models is needed and if the health system lacks it,                the overreliance on cost-effectiveness ratios and a fixed threshold for decision-making may not                be the right path and may result in the wrong decision being made.                                                                     210","Acknowledgements                       This   research   is   supported   by    the   Masaryk    Univesity   internal   grant                no. MUNI/A/1103/2018 “Hodnocení zdravotnických technologií”.                  References                 [1.]  ARROW, K J. 1963. Uncertainty and the welfare economics of medical care. The American economic                     review; 53 (5). 941-973.                [2.]  BALTUSSEN, R. M., TORRES, E., HUTUBESSY, R. C., ACHARYA. 2003. World Health Organization.                     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Journal of economic literature; 29(2): 523-552                                                                                                                                       212","Comparison of Inequalities in Incomes in the European Union                                                            a                                                                                  b                                        SOBOTKA Martin , SOBOTKOVÁ Lucie                                Faculty of Economics and Administration, University of Pardubice, Czech Republic                                           a                  b                                           martin.sobotka@upce.cz,  lucie.sobotkova@upce.cz                Abstract                 The  article  deals  with  the  analysis  of  income  inequalities  in  the  population  of  the  EU  Member  States.                However,  this  basic  view  is  related  to  the  methodological  aspect  for  assessing  the  level  of  income                inequality  in  these  countries.  The  most  general  approaches  and  indicators  are  used  for  analysis  (their                relevance for analysis is not called into question). However, the article rather focuses on their appropriate                grasp. For a more comprehensive analysis, the article used an analogy with a similar approach, which is                used  for  assessing  so-called  convergence  between  the  surveyed  countries.  The  original  concept  of                economic convergence is often  extended to other areas. Therefore, it has been proposed  to  extend the                standardization of the ranking of countries according to their inequality. The aim of this approach is to                make easier the search for examples the good practices that EU Member States have already applied over                the years to reduce the level of income inequality.                 Keywords: inequality; redistribution of income; evaluation methods; indicators of income inequality                JEL Classification: H11, H70                    1  Introduction                       The fundamental problem that economics solves is the issue of efficiency. To make this                concept  easier,  the  economists  have  developed  the  3E  concept  (economy,  effectiveness,                efficiency). However, there is a widespread concept that, besides three basic economic concepts,                still follows equity (see e.g. [3]). It is thanks to this element that we can leave a rating based on                net performance and add it to the social point of view. However, this does not mean that the                issue  of  equity  is  not  directly  related  to  the  basic  performance  model.  This  article  focuses                primarily  on  the  counterpart  –  i.e.  the  inequalities  that  will  be  related  to  the  income  of  the                population. Therefore, we will follow the basic redistribution problem, but it also has a strong                relation to the issue of efficiency. The fundamental question of trying to achieve greater equity in                the  distribution  of  incomes  in  society  can  be  linked  to  the  assessment  of  how  income                distribution evolves over time. Whether we can see differences in income distribution between                developed and less advanced economies where a higher inequality is generally expected (e.g.                [2]). It is also a question of the appropriate setting of the tax-spending system, especially when it                is  necessary  to  consolidate  public  budgets  (e.g.  [6]).  Dauderstädt  and Keltek  [9]  mention  the                significant  potential  impact  of  the  inequalities  created  on  the  European  Union  by  the  single                market. Income inequality affects the purchasing power of the population.                      The need to address inequalities is also underlined by the OECD institutions (see e.g. [15]),                which perceive inequalities as a negative element because the mentioned inequalities not only                reduce  social  confidence  of  institutions  but  also  act  as  incentives  for  political  and  social                instability. It can be the creating social barriers among groups or reducing social cohesion. It                may also be an increase in the perception of injustice that arises from the unfair advantage of                some individuals. Alternatively, the implications of a reduction in the willingness to share public                goods can be mentioned, resulting in an overall reduction in social cohesion in society.                      There  are  reasons  for  monitoring  income  inequality.  The  downstream  issues  are  the                question of measuring inequalities and finding ways to alleviate income inequality. The article                aims  to  assess  the  level  of  inequalities  across  EU  Member  States  and  on  the  basis  of  the                assessment of the results, to identify examples of good practice for tackling income inequalities.                                                                 213","Social  policy  issues  are  categorized  among  shared  policies  in  terms  of  the  division  of                competences  between  the  EU  and  the  Member  States.  Thus,  the  EU  is  in  the  Treaty  on  the                Functioning of the EU (see Head X) as an institution which supports and supplements the actions                of the Member States. On this basis, it seeks to promote the harmonization of social systems                while  respecting  their  diversity  at  Member  State  level.  In  the  historical  context,  the  wider                attention is paid to social issues in the 1957 EEC Treaty (see Article 117). And although the need                to address social issues arises, particularly in the context of the creation of a common market,                the Single European Act (1987) leaves the concept of social policy to member states and only                mentions the need to address social inequalities and take steps to improve the social situation in                the EU. From the current point of view, it is necessary to mention, in particular, the Europe 2020                strategy, in which the attention is paid to social issues within the framework of so-called smart,                sustainable and inclusive growth. At the same time, integration is understood as supporting the                economy with high employment while preserving economic, social and territorial cohesion. In                terms  of  social  policy,  efforts  are  made  to  reduce  poverty  and  to  increase  the  level  of  labor                integration.                  2  Material and Methods for Evaluation the Income Inequalities                       The article focuses on comparing income inequalities in the EU Member States. The data                for  this  comparison  results  from  the  Eurostat  database.  Specifically,  the  data  that  Eurostat                receives  through  standardized  EU-SILC  (European  Union  Statistics  on  Living  Conditions)                measurement.  This  survey  is  standardized  in  all  Member  States,  including  other  associated                countries. The unified methodology thus enables to compare the economic and social conditions                of  households  in  individual  countries  (for  more  detailed  see  [8]).  Conversely,  data  was  not                obtained from other databases because the other methodology used to collect it could distort the                analysis outputs. Dauderstädt a Keltek [9] state that Eurostat data is obtained as a population                weighted  by  national  averages  in  relation  to  this  database.  This  implicitly  assumes  that  the                poorest  household  group  is  essentially  the  sum  of  the  poor  in  the  respective  quantile  of  all                Member States while neglecting different levels of national income.                      Assessment options include a range of approaches ranging from simple to fairly complex                ones. Barr [4] states, for example, the goal is to create the indicator that evaluates the variance in                income in a given population through one variable. The ideal is to set a value between zero and                one, with zero being the most commonly reserved for the same income. Conversely, the result                one is then related to situations of absolute distribution (the individual earns the income of the                whole society). The evaluation itself is often based on two aspects:                      ·  establishing a unit of equality or inequality of an individual, family or household,                      ·  determining, which quantity the inequality will relate to (e.g. income, wealth, abilities,                         etc.).                       The choice of the variant varies with the purpose of the analysis. The simplest approaches                are  based  on  the  frequency  distribution,  which  is  determined  on  the  basis  of  the  amount  of                individual  earnings  within  each  level of  the  assessed  incomes.  From  a  mathematical  point  of                view, we get a continuous function or a histogram. The advantage of using a continuous function                is  its  simplicity  and  easy  interpretation.  Barr  [4]  draws  attention  to  the  fact  that  the  simple                interpretation applies especially to middle-income groups. On the contrary, the ability to report                falls in the case of both extreme groups (the poorest or the richest), where distortion may occur.                      The  graphical  apparatus  for  assessing  inequalities  is  the  Lorenz  curve,  which  was                explicitly  designed  to  illustrate  inequalities.  The  curve  consists  of  points  representing  the                cumulative share of income beneficiaries in the total number of beneficiaries and their share of                total income. Absolute equality in the breakdown of incomes is expressed in the Lorenz curve                with a curve with a 45 ° slope. The resulting income inequalities cause that the curve to moves                away from this diagonal. And the distance between the straight-line distribution of income and                the actual distribution represents the respective income inequality.                                                               214","Atkinson [2] reminds that Lorenz's curve can help to compare two situations, for example,                the distribution of incomes before and after taxation, when it can be concluded that the other of                the  curves  is  closer  to  the  diagonal.  Difficulties  in  comparison,  however,  occur  if  one  of  the                curves  compared  crosses  the  second  curve.  In  this  case,  it  cannot  be  clearly  stated  which                distribution of income is associated with a higher degree of inequalities. Thus, if a generalized                conclusion  cannot  be  drawn  on  the  distribution  of  incomes  among  the  population,  the                comparison of individual income groups is offered as a starting point (e.g. [4]).                      However, if we want to compare more curves, small differences may not be apparent (see                [13]). Therefore, for the comparison of individual curves, it is not possible to take advantage of                the  graphical  apparatus.  For  this  reason,  Schutz  [17]  points  out  that  the  analysis  should  not                focus on the curve, but rather it is the slope rating of the curve at each point. In this case, we can                compare the curve directions that are the tangents of the curve at the relevant points. This gives                us a more accurate picture of inequalities than can be deduced from the Lorenz curve itself. The                curve directive at a given point can be obtained by the first derivative of the respective function.                However, when using statistical data directly, it is more appropriate to use the form of:                                                                                    (1)                where: PDS – the percentage of incomes received by the S group,                       PPDS – the percentage of recipients (i. e. group S).                      When setting the appropriate values, the result can be interpreted in relation to the value                one, which represents the value of the line on the main diagonal. The more the value deviates                from  one,  the  greater  inequalities  at  that  point  we  can  reach.  Calculated  values  for  selected                function points can be represented by the histogram of slopes (see Figure 1). On the x axis the                percentage of recipients divided by individual decals is recorded. The y axis already shows the                appropriate value of the directive. In the histogram of Figure 1, it is also clear that the D10-D40                recipients represent the poorest sections of the population. For comparisons, the value of the                area  under  the curve  of the  even  distribution  of  income,  which  also corresponds  to  the  area                above this curve, can be used. The richest part of the population obtains the loss of the poorest                part of population. However, the number of population groups that can be classified as poor and                the number of the richest population may differ.                      Lapáček [13] reminds that the content of the histogram area can be calculated as:                                                                                     (2)                      where: m – the number of groups for which the tangent line of the Lorenz curve is less                than 1.                      By measuring the income inequalities, the histogram area may be below 1, or the sum of                the area contents above and below the x axis may be used (the same applies to the quality of the                two areas). For detailed evaluations, you can also evaluate the areas of individual columns in                each subgroup.                      As  another  indicator,  the  so-called  Income  Quintile  Share  Ratio  (S80S20)  (used  e.  g.  in                OECD analyzes (see e.g. [15], [16]) is used for this indicator, which basically indicates the ratio of                the  income  of  20%  of  people  with  the  highest  balanced  income  in  society  (we  measure  5th                quintile) to the volume of straight lines attributable to the 20% of the poorest households (i.e.                1st  quintile.  The  value  of  the  coefficient  is  in  the  range  of  values  from  one  to  infinitely.  The                increasing coefficient refers to income growth of the richest people, the more the value closes                one,  the  more  the  income  in  the  company  will  be  flattened,  the  value  1  then  refers  to  the                absolute equality in the distribution of income in society.                      The outputs of the calculated inequality coefficients (in particular, if output is one value                expressing the state of inequalities in a given economy, it can be represented in graphical form,                which  will  allow  us  to  compare  the  situation  in  individual  states  (see,  for  example,  frequent                                                               215","outputs published in OECD publications - [15], [16]). The advantage of this approach is then the                ease  clarity  or  the  possibility  of  creating  a  country's  \"ranking\"  according  to  the  value  of  the                indicator for the year under review. Year-on-year, a certain country's shift can be traced to this                ranking, with ordinary information added directly to the value of the indicator. This makes it                possible the individual countries to rank better.                      The following chapter will use the above procedures to analyze the situation within EU                Member States. The above outlined procedures will be used to analyze data from the Eurostat                database. In terms of time series, the data will be examined in the 2005 to 2017 series. The start                of  the  reference  period  can  be  combined  with  the  largest  EU  enlargement  so  far  (the  fifth                enlargement since the beginning of the Community). This way, the largest number of countries                can be tracked in a long-time series. The analysis will gradually expand (as has been the case for                further  enlargements  over  the  years)  about  Bulgaria,  Romania  and  Croatia.  The  analysis  will                therefore respect the later accession of those countries.                   3  Analysis of Inequalities within the EU Member States                       The  basis  for  assessing  inequalities  among  the  Member  States  is  the  graphical                representation of the Lorenz curve. The development was monitored on the time series of 2005                (i.e. after the enlargement to Central and Eastern Europe) to the present (i.e. 2017). The aim was                to capture the average change in income inequalities during the reference period. However, the                low rate of change in income inequalities has made the changes in graphic expression hardly                visible. For this reason, the histogram of slopes of tangents for Lorenz curves.                      Thus, the population was divided into individual income groups according to the deciles                (D1  to  D10).  The  time  span  of  2005  to  2017  was  also  maintained.  Only  in  view  of  the                development of the macroeconomic situation was the situation observed in 2009 (see the global                financial and economic crisis). This graph is shown in Figure 1                                     Figure 1: The histogram of slopes of tangents for Lorenz curves                                        Source: Own calculation according to Eurostat.                      We can see relatively small changes in Lorenz curves in Figure 1. These changes represent                changes in the average level of inequalities within the EU Member States, can already be seen.                Appropriate  changes  between  the  years  under  review  are  difficult  to  assess  due  to  the  low                increments/decreases  of  displayed  values.  According  to  the  basic  rule,  which  says  that  with                increasing deviation from one grows inequality at that point. And it is precisely this tendency                that has been realized on average in the EU. We can say that the crisis in 2009 did not have a                significant impact in terms of income inequality. If we calculate the area of the slopes now for                the specific EU countries, we will find more fundamental changes in the inequalities concerning                                                               216","only  a  limited  number  of  countries.  Alternatively,  in  ordinal  expression,  the  order  of  the                surveyed countries changes.                       Table 1: Evaluation of inequalities according to area size from the histogram – selected countries                                                 2005               2009               2017                              Country      Value    Order     Value     Order    Value     Order                          Sweden           0.162      1       0.18       6       0.193       9                          Denmark          0.163      2       0.178      5       0.188       6                          Slovenia         0.166      3       0.158      1       0.165       2                          Slovakia         0.18       4       0.173      3       0.157       1                          Finland          0.181      5       0.18       7       0.178       4                          Germany          0.181      6       0.202      12      0.203      14                          Czech Republic   0.182      7       0.174      4       0.172       3                          Austria          0.182      8       0.19       10      0.193       8                          Netherlands      0.184      9       0.187      9       0.188       7                          Luxembourg       0.186      10      0.203      13       0.22      19                          Hungary          0.19       11      0.172      2       0.196      10                          France           0.194      12      0.207      16      0.201      11                          Belgium          0.194      13      0.182      8       0.182      5                Source: Authors.                       An  overview  of  selected  countries  in  Table  1  outlines  the  basic  changes  in  income                inequalities in selected EU countries. Here, the countries are arranged according to the size of                the inequalities resulting from the size of the area that would be appropriate if the histogram                was designed for each country in the respective years. For easier assessment, the ranking of the                country in the relevant year is also given (the range includes all 28 EU Member States). The                development between 2005 and 2017 shows that the size of inequalities is not dependent on the                country’s  maturity.  In  many  economically  strong  countries,  inequalities  have  deepened  over                time (see, for example, the situation of Sweden, Luxembourg, Germany) or have decreased (see                Belgium). Thus, we cannot immediately link the issue of inequalities to economic performance.                      To complement the analysis of further evaluation through indicators, the benchmark is                based on the Income Quintile Share Ratio (S80S20).                      Figure 2: Increase and reduce inequalities between EU countries according to the S80S20 indicator                                        Source: Own calculation according to Eurostat.                                                                217","The above analysis has now been expanded by another indicator. Its advantage is the use                of one value to express the rate of inequality. However, Figure 2 shows an increase or decrease                in  the  inequality  gap  between  the  endpoints  of  the  period  under  review.  Similarly  to  the                existence of inequalities in the incomes of the population, dynamic changes can also be observed                in these inequalities. Thus expressed changes in inequalities can help to find, for example, good                practice in reducing inequalities. E. g. Poland and Romania experienced the largest decline in                income  inequalities.  However,  from  the  point  of  view  of  the  overall  view  of  the  level  of                inequalities in these countries, a simplified assessment cannot be made because both countries                showed  high  inequalities  between  population  groups  at  the  beginning  of  the  period  under                review                      In the introduction of the article, the link to public policies, in particular public finance,                was mentioned. Continuity could be reflected, for example, through the impact of taxation or                learning the amount of social security contributions on the one hand and the payment of social                support,  unemployment  benefits  and  other  social  policy  spending  activities.  First  of  all,  the                relationship  between  the  above  mentioned  public  finance  measures  and  the  development  of                income inequalities was examined. Thus, the Eurostat database included data for:                      ·  public expenditure on social protection, expressed as a percentage of GDP,                      ·  public expenditure on family and child benefits as a percentage of GDP;                      ·  public unemployment benefits expressed as a percentage of GDP;                      ·  taxes on individual or household income expressed in relation to GDP,                      ·  total receipts from taxes and social contributions expressed in relation to GDP.                      As a method of statistical analysis, a correlation was chosen which would demonstrate the                degree of tightness of the dependence between the growth of the relevant public expenditure                indicator  between  2006  and  2016  and  the  rate  of  growth  of  inequalities  in  selected  years.                However, the correlation analysis carried out did not prove the reluctance between the above                indicators and the increase or decrease in income inequality in society. This raises the question                of  whether  to  look  for  good  practice  examples  within  countries  and  their  public  policies.                However, the above data selections are examined from a single point of view. For this reason, the                following  chapter  outlines  a  possible  procedure  for  assessing  individual  countries  and  their                income inequalities.                  4  Enhancement of Income Inequality Analysis                       The  above-mentioned  assessment  of  inequality  developments  in  publications  is  often                based  on  country-to-country  comparisons  based  on  average  gains  or  disparities  in  income                inequalities among the population groups of the respective state. E.g. OECD analytical analyzes                use a graphical representation based on the organization of countries according to the level of                the relevant indicator, according to the amount of its change in a certain period. However, the                question remains whether the use of \"one dimension\" of income inequalities is sufficient for, the                evaluation of a successful one. E. g. the amount of decrease in the value of the relevant indicator                over a certain period of time depends on the initial level of this indicator. For this reason, other                options  were  sought  to  express  the  development  of  the  income  inequality  situation.  For  this                situation,  the  analogy  method  was  used,  where  a  similar  \"problem\"  solves  the  theory  of                convergence.  This  theory  deals  with  the  reduction  of  differences  between  two  or  more                quantities over time. Authors [14] draw attention to the original concept of convergence (1980s                and 1990s), which was derived only for the area of economic growth.                      However,  convergence  as  an  indicator  can  be  perceived  in  several  forms:  beta-                convergence or sigma-convergence (see e.g. [1], [5]) or delta-convergence (see e.g. [7]).                      In  our  case,  we  will  use  the  beta-convergence  approach,  which  evaluates  not  only  the                growth  process  in  the  relevant  indicator  but  also  refers  to  the  initial  value  of  the  relevant                indicator. Typically, it is recommended to perform the logarithm of the above values, thereby                eliminating  the  asymmetric  distribution  and,  as  a  rule,  by  approaching outlying  values.  From                these variables, the geometric mean is determined according to the formula:                                                               218","1                                        log k =  (log y - log y 0  )                                                     n                                              n                                  (3)                      where:   k   - the average growth factor of the variable per unit of the time period under                              review                             y – a variable,                             n – count of periods.                      Part of the analysis is the construction of a graph where the x axis includes the values of                 log y0 and the y axis corresponds to the values log   k  . This concept will also be used to measure                income inequalities. As a source of data, the above-mentioned indicator of income inequality has                already  served  as  a  source  of  data.  It  was  mainly  used  for  its  property  meeting  the  above-                mentioned requirement to express the inequality gap in the given territory through one value of                the  relevant  indicator.  For  these  countries  and  for  the  period  under  review,  the  necessary                magnitude was calculated - the average change over the reference period, which supplemented                the  information  on  the  initial  value  of  the  indicator.  For  Bulgaria,  Romania  and  Croatia,  the                indicator was designed for EU membership. The results can be graphically represented by the                graph in Figure 3.                                      Figure 3: Point graph for S80S20 for the period 2005 to 2017                                     Source: Authors.                       The  value  of  the  EU-average  indicator  helped  us  to  divide  the  scoreboard  into  four                quadrants.  It  can  be  said  that  the  ideal  values  for  the  inequality  area  would  be  in  the  third                quadrant. This means that the low level of initial inequalities is still accompanied by a gradual                reduction  of  these  inequalities  (see,  for  example,  Czech  Republic,  Slovakia,  Belgium,  and                Finland). It is precisely this segment that we could use for international analysis and the search                for  \"good  practice\"  in  finding  ways  to  eliminate  inequalities.  On  the  contrary,  the  \"most                problematic\" in this case is the first quadrant. The countries captured here not only reach high                rates of income inequality, but also over time these equalities are deepening (see the countries                of Bulgaria, Lithuania, Spain, Italy, and Greece).                      In spite of its clarity and a more detailed understanding of the problem of the expression                of  income  inequalities  and  their  dynamics  over  time,  this  procedure  also  suffers  from  some                distortions. The trend is expressed here by the initial and final state of the evaluated indicator. It                is based on the fact that the individual year-on-year increases (decreases) are eliminated during                the period under review and thus remain the main trend. It is precisely the potential fluctuations                within the indicator within a given period to be crucial for the interpretation of development                and appropriate measures to manage inequalities.                                                                   219","5  Conclusion                       The aim of the article was to demonstrate various methods for determining the level of                income inequalities on the example of EU Member States. The basic standard methods used for                detecting inequalities can provide us a basic overview of the state or development of inequalities                in  individual  countries.  Especially  the  histogram  of  Lorenz  curve  guidelines  and  the  income                inequality indicator. In addition to the standard assessment of the development of inequalities                across  EU  countries,  the  article  also  focused  on  the  relationship  among  the  development                inequalities  the  EU  Member  States  following  the  major  enlargement  to  Central  and  Eastern                Europe  and  indicators  that  reflect  the  trend  in  revenue  and  expenditure  policies  of  public                finances. However, carrying out a basic correlation analysis has not shown close dependence in                these areas.                      Another  direction  of  work  has  already  deviated  from  the  traditional  evaluation  of                inequalities.  In  particular,  the  beta-convergence  approach  was  used.  Compared  to  traditional                methods  for  assessing  income  inequalities,  we  have  thus  been  able  to  segment  individual                Member States in more detail. This more detailed classification could thus better serve to seek                good practice in the approaches used by the state within the framework of public finances.                  References                 [1.]  ARMSTRONG, H., TAYLOR, J. 2000. Regional economics and policy. Oxford: Blackwell.                [2.]  ATKINSON, A. B. 1970. On the Measurement of Inequality. Journal of Economic Theory; 2 (3): 244 –                     263.                [3.]  BAILEY, S. J. 2004. Strategic public finance. Basingstoke: Palgrave.                 [4.]  BARR, N. 2012. Economics of the welfare state. Oxford: Oxford University Press.                [5.]  BARRO, R. J., SALA-I-MARTIN, X. 1992. Convergence. The Journal of Political Economy, 100 (2): 223 –                     251.                [6.]  BASTAGLI, F., COADY, D., GUPTA, S. 2012. Income Inequality and Fiscal Policy. IMF. Staff Discussion                     Note No 2012 – 08.                [7.]  BLAŽEK, J., CSANK, P. 2007. Nová fáze regionálního rozvoje v ČR? Sociologický časopis, 43 (5): 945 –                     965.                [8.]  CZSO. 2018. [on-line] Životní podmínky (EU-SILC). Metodika. Available on:                     https://www.czso.cz/csu/czso/zivotni-podminky-eu-silc-metodika.                [9.]  DAUDERSTÄDT, M., KELTEK, C. 2011. Immeasurable Inequality in European Union. Intereconomics;                     46 (1): 44 – 51.                [10.] EC. 2009. [on-line] Consolidation Version of the Treaty on the Functioning of the European Union.                     EUR-Lex. Available on: https://eur-lex.europa.eu/legal-                     content/CS/TXT/?uri=celex%3A12012E%2FTXT.                [11.] EC. 2010. [on-line] Communication from the Commission: EUROPE 2020. A Strategy for Smart,                     Sustainable and Inclusive Growth. EUR-Lex. Available on: https://eur-lex.europa.eu/legal-                     content/EN/TXT/?uri=celex:52010DC2020.                [12.] KIREYEV, A., CHEN, J. Inclusive Growth Framework. IMF. Working Papers. 2017                 [13.] LAPÁČEK, M. Solidarita, ekvivalence a příjmová nerovnost v českém sociálním systému. Forum                     sociální politiky. 2 (1): 6 – 14.                [14.] MINAŘÍK, B., BORŮVKOVÁ, J., VYSTRČIL, M. Analýzy v regionálním rozvoji. Praha: Kamil Mařík –                     Professional Publishing, 2013.                 [15.] OECD. 2015. In It Together. Why Less Inequality Benefits All. Paris: OECD Publishing.                [16.] OECD. 2018. The Framework for Policy Action on Inclusive Growth. Paris: OECD Publishing.                [17.] SCHUTZ, R. R. On the Measurement of Income Inequality. The American Economic Review. 41 (1): 107                     – 122.                                                               220","Non-take-up Phenomenon in Conditions of the Czech Republic                                                             a                                                                                  b                                         ŠTARHOVÁ Iveta , GODAROVÁ Jana                                  Faculty of Economics and Administration, Masaryk university, Czech Republic                                         a                      b                                          Iveta.Starhova@econ.muni.cz,  Godarova@mail.muni.cz                Abstract                 The  concept  of  a  social  state  and  its  size  differs  from  country  to  country  and  is  influenced  by                characteristics such as its history, degree of solidarity and the mentality of its citizens which is manifested                in their desires, etc. The main question remains of how extensive the social security system of the Czech                Republic can afford to be under the condition that the state budget is balanced. In addition to the budget                constraints placed on the system, some states are also struggling with a non-take-up phenomenon in the                situation where an individual or household is entitled to assistance or social benefit under the legislation                in force. In the Czech Republic, insufficient attention is paid to this problem, in spite of the fact that a high                non-take-up rate can be a warning about problems in setting up or targeting the system. To identify the                gravity of the problem, the authors employ micro-simulation modeling using data from the Czech EU-SILC                survey from 2017. The paper is primarily focused on two specific types of benefits – the benefit package                for senior citizens and the benefit package aimed at families with children. A part of the final discussion of                the  results  will  encompass  methodological  and  data  constraints  and  the risk  groups  threatened  by  the                non-take-up phenomenon.                 Keywords: non-take up rate; Czech Republic, microsimulation modeling, failure of social policy, social benefits.                 JEL Classification: C63, H20, H53, I38                    1  Introduction                      Living standards and quality of life in modern society largely depend on the functioning of                three institutions: the market (the labour market in particular), the welfare state (social policy)                and the family [2]. The concept of a social state and its size differs from country to country and is                influenced  by  characteristics  such  as  its  history,  degree  of  solidarity  and  the  mentality  of  its                citizens which is manifested in their desires, etc. Social policy, as a part of public policy, is an                integral part of a functioning society. It contributes to the reproduction of a developed society,                mitigates poverty and unemployment, reduces marginalization of a larger part of the population,                and promotes social integration. According to many previous studies i.e. [9] the most threatened                risk groups of people are specifically senior citizens and families with children.                      Social policy uses a variety of tools to address inequalities, both in income and material                resources.  Efforts  to  reduce  disparities  are  linked  to  an  important  role  of  the  state  –                the redistributive  role. The  state  uses  taxes  and  benefits  to  redistribute wealth  towards  low-                income  population  groups  and  thus  addresses  the  living  conditions  of  individuals  and                households facing income and material difficulties. Social security benefits, as one of the most                important tools of social policy, play an irreplaceable role in reducing poverty. In addition to the                budget  constraints  placed  on  the  system,  some  states  are  also  struggling  with  a  non-take-up                phenomenon  in  the  situation  where  an  individual  or  a  household  is  entitled  to  assistance  or                social  benefit  under  the  legislation  in  force,  but  these  benefits  are  not  drawn  in  reality  for                various reasons.                      The problem of the non-take-up of welfare benefits has attracted relatively little attention                in both academic research and policy analysis even in the Czech Republic [4]. The paucity of                research on this issue stands in contrast with the evidence, reviewed in this paper, which shows                that a significant number of people who could successfully claim welfare benefits do not apply                for or receive them. Nevertheless a high non-take-up rate can be a warning about problems in                setting up or targeting the system.                                                                221","In the Czech Republic previous studies have varied greatly in quantifying the effect of this                phenomenon. They range between 30-90 %, depending on the benefits system or the risk group                definition [7]. In OECD countries the range is between 20-60 %. This wide range is caused by                a variety of approaches, methodological differences, model limitations and unavailable data for                individual countries. It is necessary to note that very few OECD countries were included in this                study due to there being no available data for many of them. [4]                      The aim of this paper is to identify the extent of the phenomenon of non-take-up of social                benefits in the Czech Republic and the factors influencing this. The paper primarily focuses on                two specific types of benefits – the benefit package for senior citizens and the benefit package                aimed at families with children - with respect to the risk groups of people mentioned above. The                first  part  of  the  article  is  purely  theoretical.  It  explains  the  importance  of  the  non-take-up                phenomenon and its impact on effectiveness; it outlines possible reasons for this lack of use and                explains  the involvement  and  importance  of  different  actors.  The  empirical  part  is  based  on                the discovered  level  of  non-take-up  for  the  Czech  Republic.  The  authors  employ  micro-                simulation modeling using data from the Czech EU-SILC survey from 2017. A part of the final                discussion  of  the  results  will  encompass  methodological  and  data  constraints  and  the  risk                groups threatened by the non-take-up phenomenon.                 1.1 Non-take-up as an effectiveness error                      Nowadays, despite the important role of social policy, targeting benefits is subject to error.                This failure has several reasons; nevertheless, the two main causes are errors occurring during                the actual  process  of  claiming  benefit.  Table  1  illustrates  the  consistency  of  policy  targeting,                entitlement and recipients of benefits. The first type of error is falsely claimed social security                benefits illustrated as B+D. It takes the form of ‘overpayment’ of benefits to individuals who are                not  eligible  for  them  and  would  have  been  identified  as  such  had  they  disclosed  all  relevant                information about their income and other details. On the other hand, social security benefits may                not fully reach those eligible for them. This is the case of non-take up (illustrated as E), defined                as the extent to which individuals fail to receive social security benefits for which are actually                eligible  [8].  Both  of  these  errors  limit  the  effectiveness  of  the social  policy.  Nevertheless,  the                fiscal effects of these errors are diametrically different: while ‘overpayment’ of benefit is costly                to government finances, on the other hand non-take up saves public money. This asymmetry                may partly explain why politicians place less emphasis on “non-take-up” than “overpayment”.                              Table 1: Consistency of policy targeting, entitlement and recipients of benefits                                                                    Target household                                                                Yes                No                                                                       Entitlement                                                            Yes       No        Yes       No                                Recipients of    Yes        A         B        C         D                                  benefits                                                 No         E         F        G         H                 Source: Authors based on [10].                       As Mares [7] also emphasizes, critics of the welfare state point to the problem of abuse of                the system  by  its  clients,  i.e.  the  drawing  of  social  security  benefits  by  persons  who  are  not                entitled to such. Social welfare advocates then focus on and point to the opposite problem –                the problem  of  non-use  of  social  security  benefits  by  entitled  persons.  The  description  of                possible combinations of policy targeting and its subsequent impact on households can be seen                in Table 1. The consistency of the support and the recipient of the benefits are shown as option                A. On the other hand, incorrect policy targeting is illustrated in situations E and F where F points                                                               222","out that the entire target population is not captured due to an inappropriate support system                setup, and E is a non-take-up situation.                      Low rates of take-up of welfare benefits are a cause of concern for at least three reasons                [4]. First, whatever the aim of a welfare program, the fact that it only reaches a fraction of those                that are supposed to benefit reduces the chances that it will achieve its goals. The second reason                for addressing the issue of low take-up of social benefits relates to equity. When the decision not                to  take  up  a  benefit  is  partly  involuntary  (i.e.  when  individuals  are simply  unaware  of  being                entitled,  or  feel  stigmatized  when  receiving  benefits),  this  generates  disparities  of  treatment                between individuals who should ex ante be treated equally by the welfare system. And finally,                better understanding the determinants of take-up decisions by individual agents will allow more                accurately anticipating the financial consequences of policy changes.                      Based on Hernanz et al. [4] it is possible to distinguish four groups of determinants which                set the extent of “non-take-up”. (1) the expected level and duration of entitlement to benefit, (2)                information costs, i.e. time and effort which is necessary for understanding the entitlement rules                of  social  security  benefits,  (3)  transaction  costs  associated  with  gathering  proof  of  eligibility,                administrative delays and error, and last, but not least (4) stigma as a psychological cost/barrier.                Moffitt (1983) emphasized stigma as the main cost of participation in a means-tested program.                Clearly, these factors interact with each other and at the same time the extent of “non-take-up” is                influenced by three levels of actors - legislative, administrative and client. All these actors set                social  space  in  which  a  potential  claimant  makes  a  decision  about  claiming/not  claiming                the benefit  [11].  Bruckmeier  and  Wiemers  [1]  examined,  on  the  basis  of  regression  analysis,                the importance  factors  influencing  the  level  of  take-up.  The  regression  results  on                the determinants  of  take-up  reveal  that  the  key-determinants  of  the  take-up  decision  are                the degree  of  need,  measured  as  the  benefit  level  households  are  entitled  to,  the  number  of                young children in the household as well as the expected duration of receiving benefit. On the                other hand they found that the stigma factor and information costs play a minor role in the take-                up  decision.  Of  course,  these  results  depend  on  the level  of  the  welfare  state,  social  security                system principles and culture disparities.                   2  Methodology, data sources and limitations                       To  identify  the  gravity  of  the  problem,  the  authors  employ  micro-simulation  modeling                using data from the Czech EU-SILC survey from 2017. Micro-simulation modelling is a tool for                simulating the effects of a policy on a sample of economic agents (individual, households, firms)                at an individual level. The usefulness of micro-simulation techniques in the analysis of public                policies has two aspects. The first is the possibility of fully taking into account the heterogeneity                of  economic  agents  observed  in  a  micro-dataset.  The  second  is  the  possibility  of  accurately                evaluating the aggregate financial cost/benefit of a reform.                      The level of non-take-up is measured by two different indicators [11]. Caseload-based rate                and expenditure-based rate. The first - the caseload-based rate is the most common indicator of                the non-take-up level. It is defined as the number of entitled non-recipients divided by the total                number of those eligible, whether receiving or not.                           The indicator provides a rather pessimistic view regarding the inefficiency of the social                security system. This is because it treats all claimants alike despite the fact that some of them                give  up  only  a  small  amount  of  benefits,  and  also  because  this  measure  does  not  take  into                account that non-recipients of benefits are on average entitled to a smaller amount of benefits                than  beneficiaries.  Therefore,  the  analysis  is  complemented  by  the  second  indicator  -  the                expenditure  based  rate  takes into an  account  the  size of unpaid  benefits. It  is  defined  as  the                amount of benefit not claimed by entitled non-recipients, divided by the total amount of benefit                                                               223","available to eligible recipients, whether actually receiving or not. This indicator is mostly lower                than the previous one because non-recipients can claim lower amounts of benefits on average                than recipients.                          The  paper  uses  data  from  the  sample  survey  EU-SILC  which  provides  representative                information on the income distribution of individual types of households, information on the                type, quality and financial demands of housing, long-term household items, as well as working,                material and health conditions of adults living in households. The Czech EU-SILC survey covers                approximately 8,000 households annually, which means approximately 18,000 individuals living                in the Czech Republic.                      The EU-SILC data are based on a sample. Therefore, it can be expected that such a survey                will not provide comprehensive information about all households in the Czech Republic (as is                the case  in  the  Population  and  Housing  Census  survey).  Levy  [6]  points  out  that  although                the household  survey  sample  may  be  representative  of  the  overall  population  it  is  not                necessarily  representative  of  population  sub-groups  such  as  recipients  of  particular  social                security benefits. The disparity was greatest in the case of female pensioners aged 80 or over.                      Because  the  survey  is  conducted  with  families  living  in  standard  forms  of  housing,                the information  on  families  living  in  lodging  houses,  homeless  persons,  persons  using  health                care facilities for a short or longer period of time and persons serving a jail sentence is missing.                Participation  in  the  survey  is  voluntary;  hence  the  results  of  the  survey  are  influenced  by                the possible  reluctance  of  a  household  to  participate  in  the  survey  (the  non-response                phenomenon). This fact applies, to a greater extent, to households at both ends of the income                spectrum.                      Accurate  computation  of  the  non-take-up  rate  requires  high-quality  information  on                household income. The vast majority of datasets used for the estimation of take-up rates are                based  on  self-reported  information. The  general  problems  related  to  the use  of  self-reported                information  are  particularly  relevant  in  studies  of  take-up  behaviour  [4].  It  is  known  that                respondents with lower income tend to overestimate their income and contrarily respondents                with higher income tend to underestimate it [3].                      There  could  also  be  a  disparity  between  the  date  of  the  interview  and  the  income                reference period. In the case of the EU-SILC survey - respondents are asked to report on incomes                earned  up  to  18 months  before  the  day  of  the  interview  [8].  Data  may  also  be  inconsistent                between status variables at the time of the survey and testing of these quantities in reality when                requesting benefits. An example of these status variables can be the number and age of children,                the type of housing, the number of people in the household, etc. The frequency of the survey                does not correspond to the decisive period for the benefits, which is in reality shorter. However,                for generalizing the entire population, we assume that the positive and negative deviations from                the model interfere with each other.                      However, despite the shortcomings and problems of the EU-SILC data, this data is the best                data available for scientific and research purposes in the Czech Republic (EU-SILC data are also                normally used for these types of analysis abroad).                   3  Results and Discussion                       The paper is primarily focused on two specific types of benefits – the benefit package for                senior citizens and the benefit package aimed at families with children - with respect to the risk                groups of people mentioned above. A major problem for these groups is housing costs. The state                assists households in covering this expenditure, with a state social security benefit - Housing                Allowance. This benefit is means-tested by assessing the income of all persons living together in                the household (Act No. 117/1995).                                                               224","The second selected benefit is Child Allowance which is only intended for families with                children.  In  the  Czech  Republic,  families  are  paid  up  to  2.4  times  the  subsistence  minimum                (the amount  determined  by  the  state  depending  on  the  number  of  persons  and  the  age  of                the children  in  the  family).  It  is  therefore  intended  for  low-income  families  with  children.                The amount of the benefit varies slightly according to the age of the child (CZK 500-700 per child                per  month,  for  comparison,  the  average  wage  was  approximately  CZK  30,000.00  and  the                minimum wage was CZK 11,000.00 in 2017).                                       Table 2: Recipients of Child Allowance and “non-take-up”                                                                   Entitlement                                                             Yes       No       Sum                                            Has      Yes    86 562   129 594   216 157                                        the household                                        in SILC2017   No   58 431   4 097 670   4 156 101                                       obtained Child                                         Allowance?   Sum   144 993   4 227 264   4 372 257                 Source: Authors based on Czech legislation and data from EU SILC 2017.                      Table 2 shows that the entitlement to Child Allowance is met by only 3.32% of the total                number of almost 4.3 million households in the Czech Republic. As was mentioned, this benefit is                targeted only at poor households located in lower decile groups. The number of households that                do not take up the benefit despite their entitlement is more than 58 thousand. The \"non-take-up\"                rate  based  on  the  caseload-based  indicator  is  40.30%  (the  expenditure-based  indicator  is                39.04%).                                      Table 3: Recipients of Housing Allowance and “non-take-up”                                                                     Entitlement                                                             Yes        No         Sum                                    Has the household   Yes   177 417    17 297    194 714                                      in SILC2017                                   obtained Housing   No   892 062    3 285 481   4 177 543                                      Allowance?                                                    Sum   1 069 479   3 302 779   4 372 257                Source: Authors based on Czech legislation and data from EU SILC 2017.                       Housing  Allowance  is  probably  the  most  complicated  benefit  of  the  entire  state  social                security  system.  The  complexity  of  the  benefit  is  evidenced  by  the  high  non-take-up  rate                associated  with  it  [5].  The  intricacy  of  Housing  Allowance  is  also  admitted  by  some  officials                responsible for the payment of the benefit.                      Housing Allowance has a much wider impact than Child Allowance, from the definition of                the target group, the entitlement to the benefit is 24.46 % (1 069 thousand) of the total number                of  households.  The  \"non-take-up\"  for  Housing  Allowance  according  to  the caseload-based                indicator is 83.41 % (the expenditure-based indicator is 65.06 %).                      In  the  Czech  Republic,  senior  citizens  represent  a  group  that  is  increasingly  becoming                entitled to the benefit. The claim rate is 37.33 % of senior citizen households according to the                SILC  2017  data.  The  non-take-up  rate  of  this  group  is  the  highest  of  the  monitored  types  of                household; it reaches up to 92.02 % of eligible senior citizen households (similar non-take-up                like  [5]).  A  role in  this may  be  played  by  low  literacy  levels,  which is  associated  with  senior                citizens  not  using  the Internet  and  other  information  means  where  they  could  find  more                information  about  the benefit.  Another  reason  may  be  ambiguity  and  non-comprehension                                                                 225","regarding the entire benefit system. Households sometimes struggle to understand the law itself                and often do not know how to find out if they are eligible to claim benefit.                      These  general  results  will  be  subjected  to  decompositions  in  follow  up  research.                Households  will  be  analyzed  according  to  important  factors  based  on  foreign  research                (according to the type and size of the family, number of children, place of residence and type of                housing, etc.). For the decision-making sphere, important information about changes in the non-                take-up rate over a longer period would also be important. However, preliminary analyzes do                not show a markedly downward trend.                  4  Conclusion                       The problem of the non-take-up of welfare benefits has attracted relatively little attention                in both academic research and policy analysis. Low rates of take-up of welfare benefits should be                a cause of concern for at least three reasons. First, whatever the aim of a welfare program, the                fact that it only reaches a fraction of those that are supposed to benefit reduces the chances that                it  will  achieve  its  goals.  The  second  reason  for  addressing  the  issue  of  low  take-up  of  social                benefits relates to equity. When the decision not to take up a benefit is partly involuntary this                will generate disparities of treatment between individuals who should ex ante be treated equally                by  the  welfare  system.  And  finally,  better  understanding  of  the  determinants  of  take-up                decisions  by  individual  agents  will  allow  more  accurately  anticipating  the  financial                consequences of policy changes.                      The  non-take-up  phenomenon  can  be  influenced  by  three  levels  of  actors  and  various                factors affect it. The nature of potential claimants/recipients, information barriers and an ability                to  process  information  affect  the  non-take-up  rate  at  client  level.  The  administration  of  the                whole social security system, setting conditions for eligibility and proper decisions of benefit                specialists/administrators all have a relevant impact on the non-take up level.                      Evidence about the level of non-take up of welfare benefits is very limited in most OECD                countries.  The  United  Kingdom  seems  to  be  the  only  country  that,  since  1997,  regularly                produced official estimates of take-up rates. Despite insufficient research in this field, previous                research  shows  that  the  non-take  up  levels  of  welfare  benefits  are  often  high  across  many                countries  and  programs.  This  is  particularly  the  case  for  (means-tested)  social  assistance                programs, where most estimates are in a range between 20% and 60% [4]. The results for the                Czech  Republic  confirm  the  general  trend  where  the  expenditure-based  indicator  is  lower.                However, these higher results of non-take-up indicators (Child Allowance non-take-up 39 % and                Housing  Allowance  65  %)  should  be  the  first  warning  signal  for  the decision  makers  to                undertake a deeper examination of setting benefits with regard to efficiency.                  References                 [1.]  BRUCKMEIER, K., WIEMERS, J. 2012. A new targeting: a new take-up?. Empirical Economics, 2012,                     43.2: 565-580.                [2.]  ESPING-ANDERSEN, G. 1999. Social foundations of postindustrial economies. OUP Oxford, 1999.                [3.]  HENNING,  L.  2011.  Comparability  of  EU-SILC  survey  and  register  data:  The  relationship  among                     employment, earnings and poverty.                [4.]  HERNANZ, V., MALHERBET, F., PELLIZZARI, M. 2004. Take-Up of welfare benefits in OECD countries.                 [5.]  JAHODA, R., GODAROVÁ, J. 2015. Housing for the Elderly - Are Older Adults a New Vulnerable Group?                     Proceedings of the 21st international Conference Current Trends in Public Sector Research. Brno:                     Masaryk University, 281-288.                [6.]  LEVY, H. 2009. Take up rates of means-tested benefits for the elderly in Spain. Institute of Social and                     Economic Research, University of Essex.                [7.]  MAREŠ, P. 2001 Problém nečerpání sociálních dávek. Brno: Výzkumný ústav práce a sociálních věcí.                                                                226","[8.]  MATSAGANIS,  M.,  LEVY,  H.,  FLEVOTOMOU,  M.  2010.  Non-take  up  of  social  benefits  in  Greece  and                     Spain. Social Policy \& Administration, 827-844.                [9.]  SIROVÁTKA T., KOFROŇ P., JAHODA R. 2011. Rizika příjmové chudoby a materiální deprivace v České                     republice. Brno: Výzkumný ústav práce a sociálních věcí, ISBN 978-80-7416-092-9.                [10.] VAN OORSCHOT, Wim J. 1995. Realizing rights: a multi-level approach to non-take-up of means-tested                     benefits. Aldershot, Hants, England: Avebury, xvi, 383 p. ISBN 1859720714.                [11.] VAN OORSCHOT, Wim J. 1994. Take it or leave it: a study of non-take-up of social security benefits.                     Tilburg: Tilburg University Press, 455 p. ISBN 9036195853.                                                                                                                                        227","Innovation Activities of Public Organizations                             in the Czech Republic between 2008 and 2014                                                       VOKOUN Marek                         Department of Economics, Institute of Technology and Business in Ceske Budejovice, Czech Republic                                                   marek.vokoun@mail.vstecb.cz                 Abstract                 The  paper  analyses  innovation  activities  of  public  sector  organizations  between  2008  and  2014.  This                paper estimates the innovation process using three steps. In the first step, the probability to innovate is                estimated. In the second step, the log of R\&D expenditures per one employee is estimated. In the third                step,  innovation  output  is  analyzed.  Results  suggest  that  size  depends  positively  on  the  decision  to                innovate like in the case of private companies. The further market orientation contributes to the higher                probability to innovate but not in the case of the public sector. Also, the probability to innovate in the                public sector does not depend on the technology level, but it does in case of the knowledge level of the                industry. The results, for the second step, suggest that the R\&D expenditures do not negatively depend on                the company size like in the case of private companies. The results, for the third step, suggest that the                sales from innovating goods and services do not depend on the company size and the input/output ration                is  not  statistically  significant.  The  innovation  behavior  of  enterprises  in  the  public  sector  differs                substantially.                 Keywords: research; development; public sector; differences; innovation process; efficiency                JEL Classification: O31, D23, L60, L80                    1  Introduction                       Innovation  activities  of  public  sector  organizations  (companies,  institutes,  and  other                organizations)  are  considered  important  for  sustainable  economic  development.  These                organizations are mostly known for cooperation and facilitator of knowledge transfer (research                institutions), but there are more types of public enterprises in the market. They are also “just”                adapting  to  technological  development  and  some  are  known  for  inefficient  research  and                development (R\&D) expenditures for large IS/ICT innovation projects. This paper analyses the                innovation  process  of  public  sector  organizations  in  the  Czech  economy  between  2008  and                2014.                       There  are  “hot  topics”  like  the  triple helix,  SMART  cities,  and  e-government  in  current                research.  All  public  sector  organizations  have  to  be  prepared  to  new  challenges  which  are                buzzing in the European Union. The fourth industrial revolution is changing economies around                the  globe  and  demands  qualified  personnel.  Public  offices  tend  to  have  issues  to  understand                what digital means and we speak only about the third industrial revolution here. For example,                the  only  complex  e-government  solution  was  introduced  by  the  government  of Estonia.  Even                though there are some issues with e-Estonia it is nothing in comparison to other countries which                are failing to introduce complex solutions and are still in the post-war age of “telephone and                paper”. The motivation of this paper is thus to discuss the similarities and differences between                private and public sector organizations.                      Because of SMART cities technologies, urban planning is a knowledge intensive activity of                big  cities’  officials  in  the  European  Union.  Public  and  private  sectors  together  shape  the                environment and wellbeing of citizens. Finding the right regulatory policy for fourth and lurking                fifth  industrial  revolution  is  a  challenge.  City  officials  are  not  ready  for  things  to  come.  For                example, in the case of shared mobility and driverless city technologies, city officials are solving                problems ex-post and lacking engagement [15]. It is the same story all over again like in the case                of  UBER  and  Airbnb  technologies  which  are  not  solved  everywhere  and  seems  irrelevant  in                                                               228","comparison. The solution is ready made and some cities are enhancing sustainability through                sharing without problems [9].                      Analysis  of  career  satisfaction  of  professionals  employed  in  various  Commonwealth  of                Australia  departments  revealed  that  without  a  leader  that  actively  shape  the  organizational                culture  no  innovation  will  occur.  The  emphasis  is  on  the  presence  of  performance-oriented                culture  because  that  is  the  only  way  to  support  talent  and  a  high  degree  of  creativity  [20].                Leadership  Behaviour  skills,  organizational  culture,  and  subsequent  barriers  are  disused  and                analyzed in the public sector literature the most [18].                      According  to  the  economic  theory  [19],  the  problem  is  the  natural  occurrence  of                bureaucracy and low-cost benefit efficiency that is everywhere where the public budget is. This                risk is also valid for public companies and R\&D organizations. The motivations of stakeholders                are  skewed.  The  only  motivation  is  power  and  budget  inside  the  organization,  not  profit                maximization  because  the  competition  is  not  present  or  able  to  wipe  out  inefficient  market                players [1].                      But there are not only cities. What is the role of public sector innovation labs? These sector                organizations also play a dominant role as a facilitator or carrier of technological growth. There                are  many  types  of  public  sector  innovation  labs  (islands  of  experimentation,  high-tech                incubators, digital labs, etc.) and their existence raised many questions [16]. It is because public                sector bureaucracies are resistant to change. The understanding of the matrix of stakeholders is                crucial for successful innovation implementation within public sector organizations [10].                      Should  we  compare  public  labs  and  private  labs?  According  to  economic  theory  public                sector labs are inefficient in delivering consumer innovations, but in case of generic or basic                research they role is important [6]. In the OECD countries, the share of public castor innovation                expenditures is decreasing; more public sources are allocated as grants and (direct or indirect)                subsidies to private companies. This trend can have adverse implications because of the positive                externality attenuation [4]. The benefits of the triple (or quadruple) helix-based system can be                endangered as well. Government organizations are able to nurture and centralize early stage                niche innovation networks [8].                      A systematic review of the literature on innovation in the public sector suggests the more                theoretical background to address the issue of innovation antecedents, importance and market                diffusion  [11].  A  good  practice  of  public  enterprises  is  to  adopt  market  technologies  and                implement new-to-the-firm open innovation since there are mostly no competitive pressures or                the  issue  is  social  driven  [17].  Public  enterprises  should  aim  at  innovations  which  deal  with                global issues like the reduction in greenhouse gas emissions [7]. In the case of hospitals, the                public  sector  can  even  perform  better  than  private  enterprises  like  in  Andalusia,  Spain  [13].                They can deal with agenda and innovation activities aimed at services that: “promote democratic                responsiveness, such as through active representation in public programs like small- and women-                owned business programs that are designed to promote racial and gender equity in the federal                procurement arena.“ [12, p. 187]                      What  makes  public  innovations  more  effective?  The  decentralization  makes  public                enterprise or organizations a more flexible control system. This can promote strategic renewal                and  more  ambitious  innovation  in  the  public  sector  [14].  An  enterprise-level  study  of  86                Ecuadorian  public  companies  found  a  positive  elasticity  (around  10  %)  between  R\&D                expenditures  and  sales  [2].  Another  Ecuadorian  research  found  internal  factors  like  workers                training, external acquisition of knowledge in a firm level analysis [5].                                                                             229","2  Research questions and hypotheses                      Current research aims at the role of the public sector and direct microeconomic studies                are  missing.  This  paper attempts  to  fill  this  gap by  analyzing  a  panel  of  data  which  includes                public  companies  and  other  organizations.  The  goal  is  to  analyze  the  innovation  process  of                public enterprises and other organization.                      The value added is provided in the basic research question which aims at the comparison                of  results  with  the  innovation  process  of  private  enterprises.  The  hypotheses  deal  with                differences and characteristics of enterprises using 3 innovation stages. H1: In the first stage, the                decision  to  introduce  new-to-the-market  innovation,  the  probability  to  innovate  is  lower  for                public  enterprises  in  comparison  to  public  enterprises.  H2:  In  the  first  stage,  the  decision  to                introduce  new-to-the-market  innovation,  the  characteristics  of  public  and  private  innovators                differs. H3: In the second stage, R\&D intensity, the intensity is lower for public enterprises in                comparison to public enterprises. H4: In the second stage, R\&D intensity, the characteristics of                public and private innovators differs. H5: In the third stage, innovation output, the intensity is                lower  for  public  enterprises  in  comparison  to  public  enterprises.  H6:  In  the  second  stage,                innovation output, the characteristics of public and private innovators differs.                  3  Material and Methods                       Four  Community  Innovation  Surveys  (CISs)  datasets  from  2008,  2010,  2012,  and  2014                were  coded into  variables  (Table  1). There are  22232  observations  about  firms in  the  Czech                industry  (NACE  3-digit  range  101-829)  and  791  public  companies.  Czech  Statistical  Office                collects data every two years and it is mandatory to report innovation activities that influenced                the  enterprise  in  the  last  three  years.  The  average  number  of  employees  is  193.37  but  the                variation is too high. The dataset includes only enterprises with 10 and more employees.                     Table 1: Summary statistics of Czech manufacturing (NACE 101-332) innovation sample in 2010-2014                            Variable                    Obs.   Mean      Std. Dev.   Min  Max                            Number of employees         22232  193.37    799.33   10   36332                            Sales of goods and services   22232  9.37E+05  6.60E+06  2   3.62E+08                            Total R\&D expenditures      9169   3.31E+04  2.80E+05  0   1.51E+07                            Foreign ownership           22232  31.23%    0.46     0    1                            Share of new-to-the-market sales  22232  3.95%   0.13   0   1                            New-to-the-market innovator   22232  18.61%   0.39    0    1                            Technological level (3 = highest)   22232  0.54   0.85   0   3                 Source: Authors.                       Estimation  method  [3]  uses  natural  logarithms  for  continuous  numerical  data.  The                procedure (Table 2) has three equations and comprises the term Xnitβn‘s (with n = 1, 2, and 3)                which  expresses  vectors  of  explanatory  variables  like  number  of  employees,  cooperation  on                innovation activities, etc.; the ε_itn‘s (with n = 1, 2, and 3) are random-error terms, the ρi denotes                fixed effects.                      The error terms are assumed to be independent of the exogenous variables. The bias from                omitted variables is high given the nature of estimated data (innovation activities) and there is                also slight endogeneity between financial variables. The first two error terms are estimated in                the Heckman procedure to control for selection bias. Mills ratio is estimated for each period to                account for selection bias. The vector of parameters to be estimated is denoted by βn (with n = 1,                2, and 3) and the single parameters to be estimated are α in the last equation (innovation input-                output elasticity).                                                               230","Table 2: Innovation process estimation procedure                        Innovation                        decision (  )                        and                        R\&D intensity (  )                         Appropriability (  )                 Source: Authors.                       The first innovation decision equation (rit ) accounts for selection into R\&D activities, and                                                             *                it deals with the probability of an enterprise i to engage in R\&D new-to-the-market activities in a                year t. This is specified as a panel Probit model, i.e. P(rit >0) = Ф(X1itβ1), where rit   equals  1 if                                                                                                *                                                                       *                enterprise i is a new-to-the-market innovator. The second linear equation (ki ) describes R\&D                                                                                           *                intensity (innovation input as the log of internal and external R\&D expenditures to the number                of employees in enterprise i). In all the equations, there is a number of potential determinants                (Xnitβn‘s) and some of them are used to identify each equation in a simultaneous estimation (i.e.                market  orientation,  etc.).  The  third  equation  (tit )  models  the  innovation  output  as  the  log  of                                                               *                sales  of  goods  and  services  from  the  new-to-the-market  innovated  goods  to  the  number  of                employees.                      The robustness check was possible by including Mill’s ratio (non-selection hazard) and to                estimate more differences of the public and private sector, the dataset was split into two and                results  are  available  for  all  companies,  public  sector,  and  the  private  sector.  This  conference                paper  has  limited  space  and  no  more  robustness  checks  were  implemented.  Random  effect                models are checked by Sargan-Hansen statistics and reported in result tables.                   4  Results and Discussion                       Private companies engage less in new-to-the-market innovation activities in comparison                to the default private sector company (not being part of a group, oriented at district markets,                low-tech, low-knowledge-intensive and operated in the year 2008). The decision to innovate is                in a positive relationship with the number of employees in all the sectors (Table 3).                      Both cuts (private and public sets of the full sample) are comparable only to some extent.                The  estimation  is  the  same  but  the  number  of  observation  is  lower  for  the  sample  of  public                companies. The average private company is not being part of a group, oriented at local (district)                markets,  low-tech,  and  operated  in  the  year  2008.  Average  public  company  with  the  same                characteristics  (not  being  part  of  a  group,  oriented  at  local  (district)  markets,  low-tech,  and                operated in the year 2008) is fundamentally different, but the comparison of both samples will                be done cautiously.                      Being  part  of  a  group  of  companies  is  beneficial  for  the  new-to-the-market  innovation                engagement in private but not in public sector. Further orientation is positive for both sectors                but  in  the case  of  the  public sector,  the  relationship  ends  at  the  national level.  There  are  no                differences between local, European and world market orientation in the private sector.                                                                             231","Table 3: Innovation process: Innovation decision – all companies, private and public sector                           New-to-the-market            (1)             (1a)            (1b)                           Equation                  Innovation      Innovation      Innovation                                                      decision        decision        decision                           Estimation method       Probit probability  Probit probability  Probit probability                                                   (Random effect)   (Random effect)   (Random effect)                           Sample                   All companies   Private sector   Public sector                           Log of number of employees   0.239***      0.230***        0.364***                                                       (0.02)          (0.02)          (0.09)                           Being part of a group      0.295***        0.313***         -0.095                                                       (0.04)          (0.04)          (0.25)                           Public ownership           -0.262**                                                       (0.12)                           Market orientation         0.679***        0.676***        0.547**                            National                   (0.05)          (0.05)          (0.26)                           Market orientation         0.583***        0.584***         0.000                            Europe                     (0.06)          (0.06)          (0.51)                           Market orientation         0.960***        0.970***         -6.719                            World                      (0.08)          (0.08)         (558.41)                           Technological level        0.159***        0.140**          0.847                            Low-Medium Tech            (0.06)          (0.06)          (0.53)                           Technological level        0.434***        0.418***         1.248                            Medium Tech                (0.06)          (0.06)          (0.87)                           Technological level        0.700***        0.677***         8.921                            High Tech                  (0.10)          (0.10)         (1159.25)                           Knowledge intensive         -0.017          -0.047         0.782***                            service                    (0.05)          (0.05)          (0.28)                           The year 2010               -0.016          -0.011          -0.292                                                       (0.04)          (0.04)          (0.23)                           The year 2012              -0.083**        -0.081**         -0.252                                                       (0.04)          (0.04)          (0.24)                           The year 2014               -0.066*         -0.058          -0.469*                                                       (0.04)          (0.04)          (0.26)                           Constant                   -3.132***       -3.087***       -4.019***                                                       (0.09)          (0.09)          (0.58)                           Panel variance             0.298***        0.300***         0.176                                                       (0.06)          (0.07)          (0.39)                           Observations                22184           21395            789                Source: Authors.                       Technological  level  plays  a  dominant  role  in  the  private  sector  and  there  is  a  strong                positive  relationship  that  grows  gradually.  In  the  public  sector,  we  observed  no  relationship                between  technological  levels  but  knowledge  intensity  is  an  important  factor  of  new-to-the-                market innovation-decision. Knowledge intensity in private sector is statistically not significant.                The survey year 2012 that cover the period 2010-2012 was clearly affected by economic crisis                and reported R\&D expenditures were lower in comparison to survey the year 2008 or 2010. The                private sector was affected in the period 2012-2014.                      The R\&D expenditures per employee are not dependent on public ownership (Table 4).                They are in a negative relationship with the number of employees in the private sector and on                average  in  all  sectors,  but  not  in  the  public  sector.  Being  part  of  a  group  of  companies  is                beneficial  to  R\&D  spending  in  the  group  of  new-to-the-market  innovators  from  the  private                sector but is not statistically significant for the sample of the public sector. There is a positive                annual  linear  trend  in  the  private  sector  and  no  trend  in  the  public  sector.  The  innovation                sample in the public sector is very small and the only significant result is a negative relationship                between high-tech level organizations and R\&D expenditures per employee. Higher intensity is                in lower-tech industries. The random effects allowed the assessment of public ownership but the                overall explained variability is low.                                                                  232","Table 4: R\&D expenditures per employee– all companies, private and public sector                 New-to-the-market         (2)              (2a)              (2b)              (2c)                 Equation            R\&D expenditures   R\&D expenditures   R\&D expenditures   R\&D expenditures                                     per employee (ln)   per employee (ln)   per employee (ln)   per employee (ln)                 Estimation method   Random effect (GLS)  Random effect (GLS)  Random effect (GLS)  Random effect (GLS)                 Sample               All companies     All companies     Private sector     Public sector                 Log of number of       -0.240***         -0.327***         -0.331***          -0.316                 employees               (0.03)            (0.04)            (0.04)            (0.30)                 Being part of a group   0.308***         0.209***          0.217***           -0.163                                         (0.07)            (0.08)            (0.08)            (0.56)                 Public ownership         0.156            0.204                                         (0.25)            (0.25)                 Technological level     -0.051            -0.125            -0.142            0.714                   Low-Medium Tech       (0.09)            (0.09)            (0.09)            (0.71)                 Technological level    0.330***           0.171*            0.157             0.984                   Medium Tech           (0.09)            (0.10)            (0.10)            (0.76)                 Technological level    0.490***           0.231             0.235            -2.538***                   High Tech             (0.17)            (0.19)            (0.19)            (0.81)                 Cross-sectional                          -0.655***         -0.682***          -0.534                   Mill’s ratio                            (0.20)            (0.21)            (1.33)                 Linear trend           0.042***          0.037***          0.039***           -0.051                                         (0.01)            (0.01)            (0.01)            (0.09)                 Constant               -80.697***        -68.706***        -72.854***        109.105                                         (25.05)           (25.36)           (25.64)          (185.17)                 Sargan-Hansen stat.      8.31             10.88             13.67              7.95                 Overall R                3.5 %            3.9 %             3.82 %            7.67 %                         2                 Observations             3880              3880              3793               87                Source: Authors.                       Sales of innovated goods and services per employee are estimated with fixed effects. The                public  ownership  variable  was  omitted  because  it  is  a  time-invariant  feature  (Table  5).  A                positive  relationship  is  with  cooperation  partners  in  the  public  sector.  Within  information                sources and university, cooperation was beneficial to innovation output. In the private sector, no                cooperation was beneficial to the sales of innovated goods and services.                      The  analysis  of  sales  of  innovated  goods  and  services  shows  a  lot  of  statistically                insignificant results. There are time-invariant characteristics of enterprises (fixed effects) that                determine the ability to capture profits from new-to-the-market innovation activities. There is a                positive relationship between the number of employees and innovation output in the private                sector. An increase of 10 % in employee count contributes on average to the 6.9 % growth in                sales of innovated goods and services. There is no such relationship in the public sector. The                ability  to  capture  profits  is  weaker  (about  25  %  lower  sales)  for  multinational  firms  in  the                private sector in comparison to local owned new-to-the-market enterprises.                      The  latent  R\&D  variable  shows  the  potential  innovation  input-output  ratio.  It  is                statistically not significant in all samples. R\&D expenditures (latent or real) are not multiplied                and translated into sales of innovated goods and services. There is also no annual linear trend                and no selection bias. The explained within variability is again low. Interestingly, there is no                relationship  between market  orientation  and  innovation  output  in  the  sample  of  new-to-the-                market innovators.                      Most  of  the  analyzed  companies  from  the  public  sector  come  from  industries  like                Production  and  distribution  of  heat  and  air  conditioning,  Water  supply,  Collection  of  waste,                Passenger transport. Then there are a lot of companies throughout the NACE spectrum. New-to-                the-market public sector innovators come from the industries: Collection of waste, Passenger                transport, Repair of fabricated metal products, machinery and equipment, Technical testing and                analysis,  Research  and  experimental  development,  Wired  telecommunications  activities,                Insurance, reinsurance, and pension funding, and Production, transmission and distribution of                electricity. There are also “new-to-the-firm” innovators (total 123 observations in the sample) in                the public sector but the majority is not innovators at all (668 observations).                                                                233","Table 5: Sales of innovated goods and services per employee – all companies, private and public sector                   New-to-the-market          (3)             (3a)             (3b)            (3c)                   Equation             Sales of innovated   Sales of innovated   Sales of innovated   Sales of innovated                                           goods and        goods and        goods and       goods and                                           services per    services per     services per    services per                                          employee (ln)    employee (ln)   employee (ln)    employee (ln)                   Estimation method       Fixed effects   Fixed effects    Fixed effects   Fixed effects                                             (OLS)            (OLS)           (OLS)            (OLS)                   Sample                 All companies    All companies   Private sector   Public sector                   Log of number of         0.644***         0.915*          0.692***          1.453                    employees                (0.14)           (0.47)          (0.13)           (2.10)                   Being part of a group     0.053           -0.124           0.056            -0.268                                             (0.15)           (0.32)          (0.15)           (1.08)                   Foreign ownership        -0.288**         -0.291**         -0.273*      No observations                                             (0.15)           (0.15)          (0.15)                   Latent R\&D variable       -0.034           0.793           -0.039           -0.042                                             (0.15)           (1.37)          (0.15)           (1.40)                   Market orientation        0.202            0.206           0.164            0.168                    National                 (0.14)           (0.14)          (0.14)           (0.57)                   Market orientation        0.234            0.235           0.200        No observations                    Europe                   (0.16)           (0.16)          (0.16)                   Market orientation        0.225            0.234           0.188        No observations                    World                    (0.20)           (0.20)          (0.19)                   Cooperation               0.108            0.106           0.073           3.900***                   - group                   (0.10)           (0.10)          (0.10)           (1.14)                   Cooperation               0.103            0.104           0.068            0.874                   - suppliers               (0.11)           (0.11)          (0.11)           (0.79)                   Cooperation               0.014            0.018           -0.020          1.422**                   - private sector clients   (0.10)          (0.10)          (0.11)           (0.71)                   Cooperation               0.088            0.095           -0.017           1.192                   - public sector clients   (0.21)           (0.21)          (0.21)           (1.40)                   Cooperation               0.177            0.186           0.170            0.470                   - competitors             (0.22)           (0.22)          (0.23)           (0.61)                   Cooperation               -0.143          -0.140           -0.176       No observations                   - labs                    (0.18)           (0.18)          (0.18)                   Cooperation               -0.100          -0.101           -0.151          2.201*                   - universities            (0.15)           (0.15)          (0.15)           (1.13)                   Cooperation               0.090            0.087           -0.104           4.798                   - private or public R\&D   (0.34)           (0.33)          (0.32)           (4.49)                   organization                   Linear trend              -0.010          -0.043           -0.009           0.059                                             (0.01)           (0.06)          (0.01)           (0.13)                   Cross-sectional        Not included        0.589         Not included    Not included                    Mill’s ratio                              (0.96)                   Constant                  26.685          87.747           24.514          -117.092                                            (27.28)          (105.11)         (27.01)         (251.01)                           2                   Adjusted R  within        2.9 %            2.9 %           3.2 %            9.3 %                   Observations              4127             4127            4034              93                Source: Authors.                  5  Discussion                       The  results  can  be  compared  only  to  a  few  papers  in  the  literature.  Clearly,  the  link                between R\&D expenditures and innovation sales is more complex and not positive. In an OLS                study with very limited control for selection bias or endogeneity, the positive link was found                between R\&D expenditures and sales [2]. Most of the companies (about 50 %) in the sample are                dealing with some sort of distribution networks (water, heat, waste) and they deal with public                goods and environmental issues. Their efficiency in comparison to private sector companies is                limited and we can see that the adoption of technologies via cooperation seems to be a positive                factor. This suggests a knowledge flows from the private sector to the public sector and certain                adaptation to new technologies rather than new-to-the-market innovation as suggested by [17].                                                              234","The main issue in the research design is a small sample size of public sector enterprises.                Problematic  is  also  the  ommssion  of  some  towns  as  major  players  in  innovation  activities                because there are no sales of goods and services. Also, the estimation of the last step could not                utilize random effect estimation procedure. Different techniques can be used which works with                product and process innovation (or other ex-post measurable innovation outputs). Current CIS                surveys are problematic and some variables cannot be provided or tested without indigeneity                issues  and  biases  (issues  in  hampering  factors  and  the  impossibility  to  estimate  sales  using                capital, investment or material variables).                  6  Conclusion                       There  are  substantial  differences  between  private  sector  and  public  sector  new-to-the-                market innovators. The probability to innovate is about 23 % lower in the public sector (H1 not                rejected).  Public  sector  enterprises  form  knowledge-intensive  industries  and  national  market                competitors  engage  the  most  into  new-to-the-market  innovations.  Private  sector  differs                extensively (H2 not rejected). It benefits from being part of a group of companies; there is also a                clear gradual positive relationship between further market orientation and technological level.                      In terms of R\&D expenditures, there are no statistically significant differences between                average  private  and  public  new-to-the-market  innovator  (H3  rejected).  High-tech  public                enterprises invest less in R\&D in comparison to lower-tech public enterprises. Private sector                again benefits from information sources and pressures of the group and there is a positive linear                trend that suggests annual 3.9 % growth of R\&D expenditures per employee in the private sector                (H4 not rejected).                      Innovation output is hard to measure. Sales of innovated goods and services per employee                could be estimated only by using fixed effects. Sargan-Hansen statistics rejects the use of random                effect  estimation  and  the  effect  of  public  ownership  in  the  whole  sample of  companies.  Both                groups were estimated independently. Innovation input-output elasticity (Latent R\&D variable)                was not significant for both groups (H5 rejected for fixed effects).                      Surprisingly, cooperation partners are significant in the public sector (H6 not rejected).                Within information sources and university, cooperation is beneficial to innovation output in the                public sector. In the private sector, no cooperation was beneficial to the sales of innovated goods                and services. There is no relationship between the number of employees and innovation output                in the public sector. On the other hand, an increase of 10 % in employee count contributes on                average to the 6.9 % growth in sales of innovated goods and services in the private sector.                  Acknowledgements                       This paper is an output of the scientific work of Internal Grant Agency at the Institute of                Technology and Business in České Budějovice, Czechia, grant name and number: Řízení inovací                v globálním kontextu [Managing innovation in a global context], IGS 16/2018.                   References                [1.]  ACEMOGLU, D. and ROBINSON, J. 2001. Inefficient redistribution. American Political Science Review,                     95(3): 649–661.                [2.]  ÁLVAREZ, N. G. and ARGOTHY, A. 2019. Research, development and growth in state-owned                     enterprises: empirical evidence from Ecuador. Industry and Innovation; 26(2): 158–175                [3.]  ANDERSSON, M. et al. 2012. 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International Journal of Organizational Analysis; 26(5): 890–914.                                                                                       236","Public Funding of Business R\&D Activities                            in the Czech Manufacturing Sector 2010 – 2014                                        VOKOUN Marek      1, a ; STELLNER František  2, b                         1                          Department of Economics, Institute of Technology and Business in Ceske Budejovice. Czech Republic                         2                         Department of Humanities, Institute of Technology and Business in Ceske Budejovice. Czech Republic                                         a                      b                                          marek.vokoun@mail.vstecb.cz;  stellner@mail.vstecb.cz                Abstract                The analysis aims at the Czech manufacturing sector and innovation activities between 2010 and 2014. A                panel of three Community Innovation Surveys is analyzed. This paper evaluates public funding of business                R\&D. The analyzed sample  consists of 9316 observations of which  4313 are about R\&D spenders, and                1942 are about new-to-the-market innovators. This paper estimates the model based on three stages of                the innovation business process. The probability to innovate (full sample), the R\&D expenditures per one                employee and sales from innovated goods and services per one employee (new-to-the-market innovation                sample)  are  analyzed.  Central  government  funding  and  EU  Programmes  funding  contributed  to  the                innovation intensity (R\&D expenditures). In the case of the innovation output, the additional contribution                of public support was measured. Local and central government programmes, EU programmes, and also                the variable describing support from the Framework/Horizon programmes were statistically insignificant.                Public  funding  led  to  some  extent  to  a  crowding-effect  of  private  sources  in  the  manufacturing  sector                among new-to-the-market innovators.                 Keywords: enterprises; innovation;public support; structural funds                 JEL Classification: O31, D23, L60, L80                   1  Introduction                       The public support of R\&D activities of enterprises is based on the Kenneth Arrow’s work                [4] about market failures. The outcomes of innovation projects of enterprises are divided into                private  and  public  returns.  The  issues  are  (a)  uncertainty  especially  in  industries  with  rapid                development and short-term profitability; (b) indivisibility or research and inappropriability of                the profit stream. In other words, the outputs of innovation projects have partially nature of                public goods. In theory, it is a good justification of public support. But there is no exact way to                ex-ante measure the “extra” public/societal component of innovation projects.                      There are many publicly funded support schemes for innovation at the firm level. Direct                support  is  usually  monetary  (financing  or  co-financing  for  projects  in  the  form  of  subsidies,                grants,  tax  breaks,  infrastructure  etc.)  or  non-monetary  (providing  data,  information,                knowledge,  requalification,  incubators  services,  facilitating  networking  and  coordinating                collaboration etc.). The debate about public support of R\&D is old and there is little consensus                about the effectiveness of monetary and non-monetary publicly funded support schemes and                about national innovation policies in general [2] [10].                      National  innovation  systems  include  also  directives  and  recommendation.  Intellectual                property rights (Patents, utility models, trademarks, copyrights, designs…) are rights given to                persons over the creation of their mind. Their protection by governments is one of the most                discussed issues in the field of law and economics [18] and the consensus is not being found [21]                [20].  The  green  technologies  (which  might  have  the  “extra”  public  component)  are  usually                “pushed”  and  “pulled”  by  government  regulation.  But  the  subsequent  public  support  of  eco-                innovation  activities  sometimes  ignores  the  linkages  between  financial  and  other  barriers                (personnel,  knowledge  etc.)  which  hamper  the  potential  of  societal-sustainable  R\&D  in                industries [19].                                                                 237","Recent studies suggest a positive impact and argue that public support matters. Projects                supported  by  the  EU  Framework  Programme  1998-2002  contributed  to  higher  labor                productivity [3]. There was a positive impact of public support for innovation at the market level                in Uruguayan firms [13]. Innovation vouchers that directly involve collaboration are beneficial                for increasing senior manager openness to external knowledge and risk tolerance in U.K. firms                [7].  The  degree  of  formal  protection  of  both  product  and  process  innovation  is  positively                influenced  by  public  support  in  the  Dutch  printing  industry  [17].  The  great  impact  of  public                funding was observed in the Spanish food and beverage industry. National funds contributed to                higher (54% more) R\&D expenditures in comparison to firms without this type of public support                [1].                      The  positive impact is  one  thing  but  it  is  expected  because enterprises  are  given more                money to R\&D activities. The question is how effective is the money spent. In the last stage of                innovation  process  [11]  (implementation  of  method/commercialization),  we  can  observe  the                ambiguity of the public support. There is negative additional contribution [8] [12], statistically                not significant contribution [15] [16] of public support to innovation output (higher sales from                innovated goods and services or probability of implanting product or process innovation).                      There is a body of evidence that the crowding-out effect of private R\&D is present and                supported  by  over-reporting  of  R\&D  tax  benefits  especially  in  large  enterprises  [14].  The                crowding-out  of  private  investment  is  present  in  the  sample  of  29  European  countries.  The                surveyed firms (70-200 respondents in each country) had at least 20 employees. The results                suggest that public support (direct and indirect) relate to higher levels of engagement in open                innovation but diminish in firms that are already innovative and support openness [6]. Public                support for innovation tends to target already successful companies which intensify crowding-                out  effects.  This  distortion  in  market  hinders  competition  and  crowds  out  private  funds  was                present in Russia in 2012 [22]. Similar results were found in Italy [5].                      The  goal  of  this  paper  is  to  analyze  crowding-out  effect  in  the  Czech  manufacturing                industry and to assess public support efficiency in R\&D intensity. This analysis is aimed at self-                reported new-to-the-market innovators and their sales of goods and services from new-to-the-                market innovated goods and services. The service sector was not analyzed because of estimation                issues and given the different nature of service sector innovation [9].                  2  Material and Methods                       Three Community Innovation Surveys (CISs) datasets from 2010, 2012, and 2014 were                coded into variables (Table 1). There are 9316 observations about firms in the manufacturing                industry (NACE 3-digit range 101-332). Czech Statistical Office collects data every two years and                it is mandatory. The average number of employees is 196.61 but the variation is too high. The                dataset  covers  only  enterprises  with  10  and  more  employees.  The  dynamic  component  of                microenterprises  is  missing.  Estimation  method  uses  natural  logarithms  for  continuous                numerical data like a number of employees or sales.                      The share of multinationals is quite high in the Czech economy. The sample has 31.85 %                foreign  owned  (50  %  and  higher  ownership)  enterprises.  The  average  technological  level  is                “Low-Medium Tech” enterprise, but again the variation coefficient is almost 100 %. There are                4313 innovators but only 2019 of them were new-to-the-market innovators, the rest “imitated”                the  competition  and  introduced  “innovation”  that  was  already in  the  market,  but  new  to  the                enterprise.  There  are  four  public  support  variables  divided  by  the  provider.  The  market                orientation variable ranges from a local market (small district) to world markets (the USA and                China). The interpretation of results is at 5 % alfa and the standard errors reported in brackets                below the regression coefficient are robust to heteroscedasticity.                                                                      238","Table 1: Summary statistics of Czech manufacturing (NACE 101-332) innovation sample in 2010-2014                            Variable                     Obs.   Mean     Std. Dev.   Min  Max                            Number of employees          9316     196.61   574.08   10    24509                            Sales of goods and services   9316   8.44E+05  5.96E+06   24  2.97E+08                            Total R\&D expenditures       4313   40820.66   372259    0   1.51e+07                            Foreign ownership            9316    31.85%      0.47    0        1                            Share of new-to-the-market sales   9316   4.19%   0.13   0        1                            Public support:                            Local government             9316     2.03%      0.14    0        1                            Public support:                            Central government           9316    12.15%      0.33    0        1                            Public support:                            EU funds                     9316    11.01%      0.31    0        1                            Public support:                            Horizon or Framework Programme  9316   7.12%     0.26    0        1                            New-to-the-market innovator   9316   21.68%      0.41    0        1                            New-to-the-firm innovator    9316    28.96%      0.45    0        1                            Technological level (3 = highest)   9316   0.96   0.94   0        3                              0: Low-tech                3,842   41.24 %                              1: Low-to-medium           2,525    27.1 %                              2: Medium                  2,436   26.15 %                              3: High-tech               513      5.51 %                 Source: Authors.                      The estimation procedure of the innovation process in manufacturing companies (Table 2)                comprise the term Xnitβn‘s (with n = 1, 2, and 3) which expresses vectors of explanatory variables                like  number  of  employees,  public  support  variables  etc.;  the  ε_itn‘s  (with  n  =  1,  2,  and  3)  are                random-error terms, the ρi denotes fixed effects.                      The error terms are assumed to be independent of the exogenous variables, but there is a                bias from omitted variables and also slight endogeneity between financial variables. The first                two error terms are estimated as a system (Heckman procedure), to control for selection bias.                Mills ratio is estimated for each period and was always significant which suggests selection bias.                The vector of parameters to be estimated is denoted by βn (with n = 1, 2, and 3) and the single                parameters to be estimated are α in the last equation (innovation input-output elasticity).                                          Table 2: Innovation process estimation procedure                        Innovation                        decision (  )                        and                        R\&D intensity (  )                          Appropriability (  )                Source: Authors.                       The first innovation decision equation (rit ) accounts for selection into R\&D activities, and                                                             *                it deals with the probability of an enterprise i to engage in R\&D new-to-the-market activities in a                year t. This is specified as a panel Probit model, i.e. P(rit >0) = Ф(X1itβ1), where rit   equals  1 if                                                                       *                                                                                                *                enterprise i is a new-to-the-market innovator.                                                             239","The second linear equation (ki ) describes R\&D intensity (innovation input as the log of                                                   *                internal and external R\&D expenditures to the number of employees in enterprise i). In all the                equations, there is a number of potential determinants (Xnitβn‘s) and some of them are used to                identify each equation in a simultaneous estimation (i.e. hampering factors, market orientation                etc.).                      The third equation (tit*) models the innovation output as the log of sales of goods and                services from the new-to-the-market innovated goods to the number of employees. The aim is to                estimate the input-output elasticity (α) and the additional effect of public support. The fourth                linear equation usually describes labor productivity, but due to the Czech Statistical Office data                restrictions, it is not employed.                  3  Results and Discussion                       Innovation  decision  (Table  3,  model  1)  regarding  new-to-the-market  innovation  is  in  a                positive relationship with enterprise size, being part of the group and in a negative relationship                with foreign-owned companies. There are control variables and their effect is described in Table                4.  This  first  step  selects  new-to-the-markets  innovators  in  the  innovation  process  that                successfully ended with new-to-the-market innovation.                           Table 3: Innovation process: Innovation decision and R\&D expenditures per employee                    New-to-the-market         (1)             (2a)              (2b)              (2c)                    innovation activities   Innovation    R\&D expenditures    R\&D expenditures    R\&D expenditures                                         decision       per employee (ln)   per employee (ln)   per employee (ln)                  Decision to innovate and    Probit    Random effect     Random effect    Random effect                      R\&D intensity      probability    (GLS)             (GLS)            (GLS)                Log of number of employees   0.388***   -0.243***         -0.487***        -0.513***                                         (0.03)         (0.04)            (0.07)           (0.07)                Being part of a group    0.320***       0.310***          0.071            -0.054                                         (0.08)         (0.12)            (0.13)           (0.13)                Foreign owned            -0.436***      0.428***          0.665***         0.598***                                         (0.08)         (0.11)            (0.13)           (0.13)                Funding – Local government              0.312*            0.309*           0.291*                                                        (0.16)            (0.16)           (0.16)                Funding – Central                       0.827***          0.803***         0.748***                government                                                        (0.09)            (0.09)           (0.10)                Funding – EU funds                      0.716***          0.693***         0.646***                                                        (0.14)            (0.14)           (0.14)                Funding – EU Framework                  0.049             0.055            0.038                Programme or Horizon                    (0.15)            (0.15)           (0.16)                Linear trend                            0.041*            0.042*           0.050**                                                        (0.02)            (0.02)           (0.02)                Coooperation partners    No             No                No               Yes                Market orientation       Yes            No                No               No                Technological level      Yes            No                No               No                Year dummy               Yes            No                No               No                Cross-sectional          Not applicable   No              -1.336***        -1.332***                  Mill’s ratio                                            (0.33)           (0.32)                Constant                 -3.677***      -79.532*          -78.261          -93.862*                                         (0.16)         (48.18)           (48.12)          (50.15)                Observations             9213           1942              1938             1938                Overall R                Not applicable   11.4 %          12.1 %           13.6 %                       2                Sargan-Hansen statistic   Not applicable   13.62          12.68            26.67                Source: Authors.                      The selection bias given by Mill’s ratio (see Heckman procedure) is evident in each period                and influenced the interpretation of the results of R\&D intensity. The intensity measured by the                logarithm of R\&D expenditures per one employee is in a negative relationship with enterprise                size in all the models (Table 3, model 2a, model 2b, and model 2c) and in a positive relationship                                                               240","with  the  foreign  ownership  of  the  enterprise.  Being  part  of  the  group  is  not  statistically                significant in all cases and did not survive the robustness check procedure.                      At 5 % level alfa, two funding variables (local government, Framework Programmes, and                Horizon  funds)  are  not  significant.  But  results  suggest  that  there  is  a  positive  relationship                between  R\&D  expenditures  per  one  employee  and  funding  by  local  government  (10  %  level                alfa), central government, and European Union funds. These results survived a robustness check                procedure.                                   Table 4: Innovation process: Innovation decision – control variables                                                                         (1)                                              New-to-the-market    Innovation                                              innovation activities   decision                                                                   Probit probability                                          Market orientation       0.716***                                            National               (0.08)                                          Market orientation       0.592***                                            Europe                 (0.09)                                          Market orientation       0.921***                                            World                  (0.12)                                          Technological level      0.072                                            Low-Medium Tech        (0.07)                                          Technological level      0.307***                                            Medium Tech            (0.08)                                          Technological level      0.664***                                            High Tech              (0.13)                                          The year 2012            -0.104**                                                                   (0.05)                                          The year 2014            -0.048                                                                   (0.05)                                          Panel-level variance constant  0.524***                                                                   (0.10)                Source: Authors.                     Table 5: Innovation process: R\&D expenditures and sales of innovated goods and services per employee -                                                      control variables                                                               (2c)                (3b)                                  New-to-the-market      R\&D expenditures   Sales of innovated goods and                                  innovation activities   per employee (ln)   services per employee (ln)                                                         Random effect    Fixed effects (OLS)                           Cooperation                   0.748***         0.126                           - group                       (0.14)           (0.15)                           Cooperation                   0.526***         0.073                           - suppliers                   (0.13)           (0.17)                           Cooperation                   0.494***         0.011                           - private sector clients      (0.12)           (0.15)                           Cooperation                   0.295            -0.028                           - public sector clients       (0.35)           (0.40)                           Cooperation                   0.333            0.495                           - competitors                 (0.26)           (0.38)                           Cooperation                   0.457**          -0.411                           - labs                        (0.22)           (0.29)                           Cooperation                   0.268            -0.214                           - universities                (0.18)           (0.18)                           Cooperation                   0.136            -0.107                           - private or public R\&D organization  (0.27)   (0.34)                Source: Authors.                                                                   241","Innovation decision that ends with a new-to-the-market innovation depends on market                orientation (Table 4). The relationship is positive for all the markets. Interestingly, European                markets  orientation  contributes  less  to  R\&D  intensity  than  national  market  orientation.                Medium-tech  and  high-tech  industries  spend  more  on  R\&D  than  low  and  low-medium-tech                industries.  Also,  the  probability  to  introduce  new-to-the-market  innovation  was  about  10  %                lower in the period 2009-2012.                      Cooperation brought positive effects to R\&D expenditures per employee (Table 5). The                best  contributors  were  the  companies  inside  the  group,  suppliers,  labs,  and  clients  from  the                private sector. There is no contribution to R\&D intensity of universities or public sector clients.                In the case of innovation output, there is no additional effect of all cooperation partners.                     Table 6: Innovation process: sales of innovated goods and services per employee - control variables                                                             (3a)                    (3b)                              New-to-the-market    Sales of innovated goods and   Sales of innovated goods and                             innovation activities   Services per employee (ln)   Services per employee (ln)                                                   Fixed effects (OLS)     Fixed effects (OLS)                         Log of number of employees   0.556*               0.576*                                                   (0.33)                  (0.33)                         Being part of a group     0.174                   0.207                                                   (0.32)                  (0.32)                         Foreign owned             -0.050                  -0.011                                                   (0.36)                  (0.36)                         Funding – Local government   0.350                0.389                                                   (0.28)                  (0.29)                         Funding – Central government  0.062               0.102                                                   (0.57)                  (0.58)                         Funding – EU funds        0.339                   0.339                                                   (0.51)                  (0.52)                         Funding – EU Framework    -0.056                  -0.032                         Programme or Horizon      (0.16)                  (0.16)                         Linear trend              0.061*                  0.064*                                                   (0.04)                  (0.04)                         Market orientation        0.209                   0.202                           National                (0.48)                  (0.49)                         Market orientation        0.045                   0.032                           Europe                  (0.45)                  (0.46)                         Market orientation        0.044                   0.043                           World                   (0.63)                  (0.64)                         Latent R\&D intensity      -0.031                  -0.020                                                   (0.03)                  (0.03)                         Cooperation partners      No                      Yes                         Constant                  -114.226*               -119.085*                                                   (69.17)                 (71.38)                         Observations              1937                    1937                         Adjusted R2               5.1 %                   6.7 %                Source: Authors.                       Sales of innovated goods and services per employee (Table 6) are not in any relationship                with all the variables at 5 % level alfa. We observe positive trend and relationship between size                and Sales of innovated goods and services per employee. The results are expected because there                is a high degree of heterogeneity of firms and the estimation only allows for within variation. We                were  unable  to  estimate  the  random  effect  model  more  variables  are  needed  or  different                estimation approach.                      Results  suggest  there  is  no  additional  effect  of  public  support  on  innovation  output                measured by sales of innovated goods and services per employee. The sample consists of new-                to-the-market  innovators  and  their  time-invariant  characteristics  (fixed  effects)  define  their                innovation output and the ability to capture profits.                                                                   242","4  Conclusion                       Czech  manufacturing  sector  R\&D  activities  of  new-to-the-market  innovators  were                influenced by public sources. This support did not contribute to higher R\&D expenditures in all                types of support and there was no additional effect of all the sources on sales of innovated goods                and services. Public funding led to some extent to a crowding-effect of private sources.                      The  sample  of  9316  observations  about  enterprises  received  support  from  local                government,  central  government,  EU  funds,  and  Framework  Programme/Horizon2020  funds.                Three-stage model of the innovation process was used and three dependent variables analyzed:                The probability to innovate, the R\&D expenditures per one employee and sales from innovated                goods and services per one employee.                      Result  suggests  that  national  and  EU  funds  contribute  to  higher  R\&D  expenditures  in                comparison  to  unsupported  firms.  But  the  effect  ends  there.  There  is  no  additional  effect  on                innovation  output.  There  are  two  possible  channels  and  both  are  not  statistically  significant.                First, the input/output innovation elasticity ratio (more R\&D produce more sales of innovated                goods and services) is not statistically significant for new-to-the-market innovators. Secondly,                public support sources have no additional effect on sales of innovated goods and services.                      The  ability  to  capture  profits  from  innovated  goods  and  services  depends  on  time-                invariant  characteristics  of  firms.  The  last  stage  that  describes  commercialization  is  the  very                problematic  and  random  effect  is  usually  hard  to  estimate.  Future  research  can  incorporate                easier  method  like  bivariate  Probit  for  the  product  (goods  and  services)  and  process  (new                methods) innovations.                  Acknowledgements                       This paper is an output of the scientific work of Internal Grant Agency at the Institute of                Technology and Business in České Budějovice, Czechia, grant name and number: Řízení inovací v                globálním kontextu [Managing innovation in a global context], IGS 16/2018.                  References                 [1.]  ACOSTA, M., CORONADO, D. and ROMERO, C. 2015. 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International Advances in Economic                     Research; 21(1):13–31.                                                                                            244","Paradigm Reform for the Czech Family Benefits and Credits                                                    VOSTATEK Jaroslav                                    Research Institute for Labour and Social Affairs, Prague, Czech Republic                                                       jvostatek@volny.cz                 Abstract                 While  many  authors  focus  on  the  submission  of  partial  improvements  of  the  Czech  family  policy,                insufficient attention has been devoted to the family policy system as a whole. In the Czech political scene,                there is an increasing tendency towards simple political marketing. However, social policy theory should                focus on analysing family policy, particularly via the application of (liberal, Christian-democratic, social-                democratic and neoliberal) welfare regimes. The optimal approach for individual countries is to focus on                one of these models, thus allowing for the reaping of the various synergy benefits of the application of one                coherent model. From this point of view, the Czech socio-economic system is based on somewhat unstable                foundations, in comparison e.g. to Germany or Sweden. The paper focuses on Czech family benefits and                credits and on their restructuring via the application of OECD and EU recommendations.                Keywords: child benefit ; child tax credit; parental benefit ; welfare regime ; full-day preschool                 JEL Classification: H24; H53; J13                    1  Introduction                       The OECD  has  repeatedly  recommended  that  the  duration  of  the  parental  allowance in                Czechia be shortened, and funds saved be transferred to the provision of childcare services for                families  with  small  children.  The  approach  of  the  EU  is  similar  in  this  respect:  „The  labour                market  participation  of  women  with  young  children  is  hampered  by  a  persistent  lack  of                affordable and quality childcare services, in particular for children up to 3 years old, by long                parental leave entitlements.” [2]. The OECD miscalculates the Czech full-rate equivalent of the                parental benefits in Czechia and we revise these data in this paper.                                       Figure 1: Typology of basic social models of family policy                                                        Lower generosity                                   Neoliberal model                         Liberal model                              Christian-democratic model                Social-democratic model            Universality                     Selectivity/testing                                                     Higher generosity                 Source: Author.                      It is possible to trace several typical, basic social models or welfare regimes as defined by                Esping-Andersen  [3].  We  distinguish  the  liberal,  Christian-democratic  and  social-democratic                social  models  as  well  as  the  neoliberal  model  that  has  developed  since  the  1990s.  The  main                differences  between  these  four  basic  social  models  of  family  policy  can  be  schematically                depicted via differences in, on the one hand, an emphasis on universality or the selectivity and,                on the other, the lower and higher generosity of the family policy – see Figure 1. The aim of this                                                                245","paper  is  to  compare  the  four  basic  models  and,  on  this  basis,  to  analyse  the  most  efficient                prospective reforms of the Czech family benefits and credits.                   2  Material and Methods                       The modern liberal social model entails the relatively low universal family benefits, as                e.g.  designed  by  the  UK  Beveridge  Commission  in  1942  and  introduced  by  the  Labour                government after the Second World War. The child benefit was intended to cover the child’s                subsistence minimum. The UK government introduced the Family Allowance, commencing with                the second child in the family. In 1977, this allowance was replaced by the Child Benefit paid for                the first child at the level of 5% of average net earnings. Since 2013, the child benefit has not                constituted  a  (fully)  universal  allowance  due  to  the  introduction  of  the  High  Income  Child                Benefit Charge, which affects around 1% of children. In the last few years, child benefits have                been provided in the amount of £20.30 per week for the oldest child and £13.40 per week for the                other children.                      In the beginning of the 2000s, some neoliberal concepts were realized in the UK aimed at                working families with children. In 2003 the Child Tax Credit (CTC) was introduced, significantly                affecting the overall state support system for families with children; in 2005 the CTC for a family                with  two  children  aged  2  and  7  and  one  breadwinner  with  national  average  earnings  (NAE)                amounted  to  roughly  the  same  as  the  universal  child  benefit;  moreover,  it  was  significantly                higher  than  in  the  majority  of  other  comparable  countries  [4].  Since  2016,  the  CTC  was                incorporated as a “child element” into the new Universal Credit (UC), a social assistance benefit                for those of active age towards which the UK is gradually moving – by region – up to the deadline                of 2022. The reform is linked to an extensive restriction in paid benefits.                      The Beveridge liberal maternity benefits model was based on the ruling male breadwinner                model at that time. The National Insurance Act of 1946 introduced (also) a universal Maternity                Grant  of  £4, intended  to subsidise maternity  costs;  the rest  of  the costs  were  expected  to  be                borne by the breadwinner. The universal Maternity Allowance (MA) of 36 shillings weekly was                designed  to  supplement  the  Maternity  Grant  for  married  working  women  for  a  period  of  13                weeks, provided they gave up working. MA was intended to make it easier and more attractive                for women to leave their job.                      Today, the Sure Start Maternity Grant in England of £500 is provided only for the first                child  and  for  recipients  of  means-tested  benefits  only.  The  Scottish  Pregnancy  and  Baby                Payment is more generous: £600 is paid for the first child and £300 for further children. The                means-testing of birth grants is typical for the neoliberal social model.                      The current maternity benefit was introduced by the Labour government in 2003; it is                paid for up to 39 weeks. The Statutory Maternity Pay (SMP) for working women who fulfil the                more demanding conditions is paid by the employer at a rate of 90% of earnings (without an                upper  limit)  for  the  first  6  weeks  and with  the  limit  of  £145,18  per  week  for  the  rest of  the                period. The Maternity Allowance (MA) reserved for other groups of working women including                self-employed is paid by the Jobcentre Plus at a rate of 90% of previous earnings, but not more                than £145.18 per week, with a lower limit of £27 per week. Certain working women (e.g. those                who work in a company owned by the husband or partner) are entitled to the MA over a shorter                period  of  14  weeks.  In  general,  British  maternity  allowances  are  secondary  benefits,  which                broadly corresponds to the liberal and neoliberal social models. The full-rate equivalent (FRE) of                maternity benefits is 12 weeks only.                      The  level  of  public  preschool  childcare  was  minimal  until  the  1990s.  „Playgroups                organized  by  parents  (mothers)  that  required  a  great  deal  of  parental  involvement  were  the                predominant form of care for preschool-aged children until the 1990s, but the short hours and                the  focus  on  three-  and  four-year-old  children  meant  that  these  playgroups  could  not  serve                children of full-time working parents. Parents in need of full-day child care tended to rely on …                relatives and the private market of childminders. Concerns about a shrinking labour force and                labour shortages, the major economic and social inequalities that were emerging as a result of                                                               246","earnings inequalities, and increases in child poverty led the Conservative government to turn its                attention to child care and early childhood education“ [8]. At the end of the 1990s however, both                Conservative and Labour governments initiated the introduction of limited state-financed pre-                school education which resulted in a contribution to the cost of day care for children aged 3 and                4 for a very limited period. (Compulsory school attendance in Britain commences at the age of 5                and in Northern Ireland at the age of 4; in England, almost 60% of children aged 4 years attend                preparatory classes at primary school.) The duration of funded childcare was originally set at                12.5 hours per week for 38 weeks per year and was later extended to 15 hours per week and                expanded to include two-year-old children from low-income families. A further shift occurred in                September 2018: for all children a further 15 hours per week was added subject to both parents                working (if possible) for at least 16 hours per week for a salary in the amount of at least the                applicable minimum wage (£125.28 per week) and a total annual family income of a maximum                of £100,000. The weekly hourly allocation can be used up flexibly even for a period of less than                38 weeks per year. In principle, this constitutes a (“universal”) allowance of up to £5,000 a year                for  the  care  of  children  aged  3  and  4  years.  The  concept  of  this  allowance  (“30  hours  free                childcare”) lies on the border of the liberal and neoliberal social models.                      In  general,  the  modern  liberal  model  of  family  benefits  exhibits  a  coherent  logic  that                corresponds to a system of low universal benefits. This model is “prone to” a greater or lesser                transformation to the neoliberal model.                      The Christian-democratic social model emphasises the crucial role of marriage and the                family. The original version of this model was based on the traditional division of labour in the                family. The modern version model emphasises the freedom of choice: parents should be free to                decide whether to spend more time on work or on childcare.                      The Christian-democratic model is dominated by personal income tax with the option of                the  joint  taxation  of  spouses  and  built  consistently  on  the  ability-to-pay  principle,  with  a                pronounced  progressivity  and  the  non-taxation  of  the  subsistence minimum  of  the  family.  In                Germany, this model takes the form of tax deductions. In 2019, the subsistence minimum for                each  child  is  €7,620;  the  amount  of  the  tax  saving  increases  with  rising  earnings.  The  child                allowances  are  considered  as  a  major  social  element;  the  current  allowances  for  1   and  2 nd                                                                                                  st                children amount to €204 and for each further child €235 per month. Since 1996, an “optional                system” allows taxpayers to choose between the child allowance or the child tax deduction. Child                allowances  are  higher  than  the  tax  savings  for  lower-  and  middle-income  families.  The  legal                interpretation of the Constitutional Court assumed that the child’s subsistence minimum cannot                be taxed and that the tax exemption of this minimum may also be realised in the form of child                allowances. Child allowances cover some one-third of the actual average cost of raising children.                      For  families  with  low  incomes,  a  means-tested  supplement  to  the  child  allowance  is                available in Germany for each child of up to €170 a month. The birth grant was abolished in                2004. The maternity allowance is a health insurance benefit; non-insured women are entitled to                a reduced maternity allowance of up to a maximum of €210 (sometimes referred to as a birth                grant  in  international  surveys).  The  basic  variant  of  the  maternity  allowance  is  of  14  weeks                duration and is paid out at 100% of net earnings. The health insurance fund contributes €13 per                calendar day to the maternity allowance, while the “rest”, up to 100% of net earnings, is paid by                the employer.                      The German parental benefit is a state earnings-related benefit: the rate is 65% of the net                income. The minimum amount of the parental benefit is €300 and the maximum €1,000 per                month. The benefit is intended to compensate for the earnings of the parent; it allows the parent                to work for up to 30 hours per week. The basic variant of the parental benefit is set at 14 months                from the birth, from which the duration of maternity allowance is deducted. The total maternity                and parental full-rate equivalent equals 42.6 weeks.                      In July 2015, the parental benefit was supplemented by the so-called Plus option which                allows for the doubling of the duration of the parental benefit at half the amount of the benefit.                According to German sources, this development contributed significantly to the afore-mentioned                freedom of choice between gainful employment and personal care for a child.                                                                247","The provision and financing of childcare is diversified in Germany. Nurseries and crèches                of various kinds are entitled to receive contributions from the federal and state governments                and  municipalities,  thus  resulting  in  the  significant  diversification  of  parental  fees.  Non-                contributory  care  for  preschool  children  is  gradually  being  introduced  to  varying  extents  in                individual municipalities and states in Germany. Since 2013, children from one year of age have                enjoyed the legal right to a place in day crèches or nurseries etc., provided by the municipality.                      Overall,  the  German  family  policy  system  is  based  to  a  considerable  extent  on  the                Christian-democratic  social  model,  particularly  with  respect  to  the  income  tax  and  parental                benefits concepts which are earnings-related to a high degree. According to the OECD, the option                of the joint spousal income taxation presents a barrier to the greater involvement of mothers                and women in general in the labour market. Developments in the field of childcare for preschool                and school-age children suggest a movement towards the social-democratic model.                      The  social-democratic  social  model  is  based  on  the  principle  of  social  rights  for                everyone  regardless  of  the  family  and  the  market;  everyone  (especially  children)  should  be                given  “an  equal  chance”  regardless  of  previous  income  or  performance.  In  principle,  both                parents work (dual earner model). Each parent pays income tax separately; the joint spousal                taxation and tax credits or deductions are simply not allowed. The model prefers public services                to cash benefits.                      Since March 2018, the universal child allowance in Sweden was at SEK 1,250 (€122) per                month per child. Extra payments are available for second and further children in the household.                      There is no birth grant in Sweden. Sweden has no separate maternity benefit: the parental                benefit commences 60 days prior to the expected date of birth and is paid for up to 390 days to                sickness insurance scheme participants in the amount of 80% of the gross wage with a minimum                of  SEK  250  and  maximum  of  967  per  day.  Social  security  benefits  in  Sweden  are  subject  to                personal income tax. The parental benefit for persons with no or low incomes is paid at a rate of                SEK 250 per day. Following the 390 days, there are further 45 days of parental benefit at a flat                rate of SEK 180 per day. The full-rate equivalent of the parental benefit available to mothers was                at 34.7 weeks in 2016.                      Preschool in Sweden is mandatory from age 3 to 6. Municipalities must offer preschool for                children  from  the  age  of  1.  Children  whose  parents  are  on  parental  leave  must  be  offered  a                preschool place for at least 3 hours a day, or 15 hours a week. Some municipalities offer more.                There  are  both  municipal  and  independent  preschools.  3  hours  a  day  of  public  preschool                attendance is free of charge. For further attendance, the municipality or the education provider                determines  the  fees.  Sweden’s  maximum-fee  policy  makes  childcare  affordable  for  everyone.                Low-income families pay nothing while the costs for more affluent parents are capped at SEK                1,382 per month. Parents should spend 1 to 3 per cent of the family’s income on childcare [7].                      The  Swedish  system  of  family  benefits  and  services  is  a  typical  example  of  the  social-                democratic social model. One of the results of this model is a low child poverty level.                      The neoliberal social model considers children to be a private issue or an investment.                Neoliberals  adapt  the  personal  income  taxation  by  numerous  and  extensive  deductions  and                credits. Due to them the US has the second highest level of rectified social spending in the world                (behind France) and … a very high child poverty rate.                      While child benefits do not exist in the US, two “child” credits can be claimed from federal                income  tax:  the  Earned  Income  Tax  Credit  (EITC)  provides  substantial  support  to  low-  and                moderate-income working parents and the newer Child Tax Credit (CTC) provides taxpayers up                to $2,000 (up to $1,400 of which families can receive as a refundable credit for each dependent                child under age 17). The CTC extends to middle-income and most upper-middle-income families                as well. The EITC and CTC are best seen not as taxes but as tested transfer programs that happen                to be administered through the tax code. Differing schedules by family type are a long-standing                feature of the US tax system. The Tax Policy Center estimates that 91 percent of families with                children will receive an average CTC of $2,420 in 2018. There are high error rates for the EITC.                Studies  by  Treasury  analysts  indicate  that  only  a  minority  of  improper  payments  stem  from                fraudulent actions.                                                                248","No  birth  grant  exists  in  the  USA.  Several  US  states  provide  for  paid  leave  with  partial                earnings compensation for several weeks such as California and New Jersey - 6 weeks at wage                rates  of  55%  and  67%  respectively.  The  full-rate  equivalent  of  US  maternity  and  parental                benefits is zero weeks.                      The pre-school age child care market is very fragmented in the US with varying levels of                service  quality  across  the  various  states.  The  federal  and  state  governments  provide  grants                aimed at easing the lack of availability of this type of care for low-income groups of workers.                Child Care and Development Block Grant (CCDBG), a $5 billion federal block grant program, is                the primary source of public funding for child care. Through CCDBG, the federal government                provides  grants  to  states  to  provide  monthly  subsidies  or  vouchers  to  low-income  families.                Parents pay a fee that is typically 10 percent of the cost of child care. About 2.6 million children                receive federal subsidies through one of several funding sources, including CCDBG. Head Start                and Early Head Start programs support the childcare needs of children living below the poverty                level or those with disabilities. Head Start programs currently serve approximately 42 percent of                income-eligible children, and Early Head Start programs serve less than 4 percent of income-                eligible children. One federal tax credit available to businesses is the Employer Provided Child                Care  Credit,  a  credit  for  businesses  who  cover  the  costs  of  child  care  expenses  for  their                employees. The credit is for 25 percent of expenses up to $150,000 per year. California State                Preschool Program offers full and part-day pre-Kindergarten for 3- and 4-year olds with family                incomes at or below 70 percent of the state median income and serves about 135,000 children                across the state. US child care financing system is a confused collection of funding streams with                no uniform goals, standards, or administrative structure [1].                      Our comparative analysis of the main benefits of the four basic family policy models and of                their interaction confirmed the characteristics shown in Figure 1. From the point of view of the                median voter, the social-democratic model is the most sophisticated one in general terms. In                practice, not only the parameters of the relevant systems but also the governance of the system                constitutes important factors.                  3  Results and Discussion                       The  current  Czech  system  of  family  benefits  and  tax  credits  has  been  influenced                significantly by the reforms over the past two decades. Up to 1995, universal child allowance                paid  out  under  the  health  insurance  system  had,  for  several  decades,  constituted  the  most                significant  benefit  in  this  area.  From 1996, child allowance  was  regulated  by  the  State Social                Support  Act  and  was  means-tested.  The  allowance  had  three  levels:  basic,  upper  and  lower                according to the income means-test result, with the criterion being a multiple of the subsistence                minimum  of  the  family.  In  2008,  the  uniform  level  of  allowance  was  introduced.  The  child                allowance  (CA)  is  differentiated  according  to  the  age  of  the  dependent  child.  The  last  mini                reform, introduced in 2018, was influenced by the neo-liberal policy of the KDU-ČSL political                party: the amount of the allowance (CZK 500/610/700, according to age) was increased by CZK                300  per month  but  only for  the children  of  working  parents  or  the  beneficiaries of a  benefit                based on employment and the replacement of income.                      Tax reforms from 1993 introduced deductions from the income tax base for children. In                2005, this system was replaced by the refundable child tax credit (CTC) claimable by one of the                parents. The amount of any negative income tax due to CTC is referred to as the “tax bonus”, the                amount of which is limited to CZK 60,300 per year and which is now “sufficient” for 3 children                (originally 4.5 children). Income tax payers with an income of at least six times the minimum                wage at the beginning of the tax year are entitled to claim the tax bonus. The amount of the CTC                is currently CZK 15,204 per year for the 1  child, 9,404 for the 2  child and 24,204 for the 3                                                                                                          rd                                                         st                                                                              nd                and further children. The parameters of both the CTC and CA change frequently according to the                current political needs rather than being based on a clear concept (as is the case in Germany).                Moreover, fraud concerning the tax bonus is on the increase. The Czech CTC + CA for one child                roughly correspond to German child allowances in relation to average earnings, which serves to                                                               249","illustrate  the  relatively  low  level  of  the  CTC  +  CB  in  Czechia.  However,  with  respect  to  two                children, various international comparisons have suggested that the level of Czech benefits and                credits is above the EU average in relation to earnings.                      The  birth  grant  was  originally  a  universal  health  insurance  benefit  before  it  was  re-                classified as a universal state social support benefit. It became a means-tested benefit from 2011                initially only for the 1  child (CZK 13,000) and from 2015 also for the 2  child (CZK 10,000).                                                                                      nd                                     st                Currently, in order to qualify for the birth grant, the income of the parents must not exceed 2.7                times the family subsistence minimum.                      Since 1987, the period of the receipt of the maternity benefit (MB) has been 28 weeks. It is                a health insurance benefit, the calculation of which copies that of the sick benefit but at a higher                rate.  Reduced  rates  apply  to  those  on  above-average  earnings.  Women  with  above-average                earnings are thus discriminated against compared to the usual construction of the calculation of                health insurance benefits; for example, in Germany no reductions apply, rather an earnings limit                is in place for the calculation of the benefit which is set at around 200% of NAE. The replacement                rate of the MB, calculated on the assumption that the insured earns the average national wage, is                90.2% of the net wage. The OECD [6] mistakenly states a low replacement ratio of 62.6%, mainly                due to not because the MB is not taxed. Consequently, the OECD has calculated the FRE at 17.5                weeks,  whereas  the  correct  figure  is  25.3  weeks.  Our  recommendation  for  rationalising  the                system is simple: the MB should be paid in the amount of 100% of the gross wage (with a 200%                earnings limit) for 25.3 weeks and the benefit should be taxed.                      The parental allowance (PA) has long been regarded as the most “distinctive” Czech family                benefit. The first variant of the benefit consisted of the “maternity allowance” (MA) which was                introduced in 1970 “in order to encourage population development; it is provided to working                women provided they care for their children and do not earn income from work during this                time.” The eligibility conditions of MA were analogous to those of maternity benefit; it was a                health  insurance  benefit  provided  for  children  under  the  age  of  one  year  and  subject  to  the                suspension  of  work.  The  amount  of  the  MA  was  universal.  The  parental  allowance  was                introduced in 1990 and applied to children up to 4 years of age subject to the parental full-time                childcare. Working was allowed for a maximum of 2 hours per day subject to a very low-income                limit; subsequently this restriction was lifted. In 1996 the PA was incorporated into the State                Social  Support  Act  and  the  (monthly)  amount  of  the  benefit  was  limited  to  1.1  times  the                subsistence  minimum  for  the  child’s  personal  needs.  The  PA  was  thus  transformed  into  a                universal  benefit  provided  without  regard  to  previous  employment.  If  the  mother  was  not                entitled to the MB, she was entitled to the PA instead of the MB (this applies up to now). Since                2004, no limit has been set on the income of the parents.                      While the original MA/PA can be characterised as a modern liberal benefit, since 2008 the                Christian-democratic  model  has  predominated:  the  PA  was  transformed  into  a  “three-speed”                universal  benefit  involving  the  choice  between  the  claiming  of  the  benefit  up  to  the  child                reaching 2, 3 or 4 years of age, with each “speed” associated with a different benefit amount                (CZK 11,400, CZK 7,600, CZK 3,800 / up to the 21  month CZK 7,600). The development of the                                                                st                benefit continued with the unification of the total maximum amount of the PA at CZK 220,000                with a maximum monthly amount of CZK 11,500 from 2012. The benefit also applies to parents                whose children attend childcare facilities. From 2 years of age, children can attend such facilities                on an unlimited basis. This construction had a significant effect on the behaviour of mothers: the                majority opted to remain at home until the child reached 3 years of age. The PA thus became a                significant barrier to women returning to work, most of whom preferred to care for the child at                home  with  an  PA  of  CZK  7,600  than  to  return  to  the  labour  market.  In  addition,  working                husbands are unable to claim the spousal tax credit of CZK 2,070 monthly.                      From  2018  the  monthly  limit  of  PA  of  CZK  11,400  was  abolished,  and  the  benefit  was                effectively transformed into a “baby bonus” of CZK 220,000, which can theoretically be used up                in 6 months, but in practice 6.74 months. If the PA were calculated from the NAE (in fact, the                wages of young women are significantly lower), the baby bonus could have been used up in 10.5                months. The dominant parameters in today’s PA consist of the baby bonus of CZK 220,000 and a                                                                250","monthly  limit  given  by  the  amount  of  the  MB.  The  Ministry  of  Labour  and  Social  Affairs  has                recently proposed that the baby bonus be valorised to CZK 300,000.                      The full-rate equivalent of the Czech PA according to OECD [6] was 35.6 weeks in 2016.                Dividing the baby bonus of CZK 220,000 by the weekly net NAE of CZK 4,862 reveals an FRE of                45.2 weeks. The total Czech FRE for maternity + paternal benefits for 2016 is 25.3 + 45.2 = 70.5                weeks, thus resulting in a shift from 5  place in the OECD ranking to 3  place behind Estonia (85                                                   th                                                                                  rd                weeks) and Hungary (71.8 weeks).                      „Parental allowances and other benefits available to families with young children reflect                the Czech authorities´ preference for family-based childcare and are therefore tilted towards de-                activating parents for relatively long periods“ [5]. Czechia thus continues to apply the classical                Christian-democratic model of the financing of all-day childcare in the family for 2-3 years. In                2014, the OECD recommended us to shorten the duration of MB and PA to just one year.                      The simplest partial reform of Czech family benefit system would be to change the rate of                the MB to 100% of the net wage accompanied by the abolition of reduction limits, which could                be accomplished by moving the MB to 100% of the gross wage accompanied by the taxation of                the MB. This reform should also include an earnings limit of 200% of NAE. Moreover, if we also                add a minimum MB of 50% of NAE, it is possible to abolish the non-systemic “replacement” of                the provision of the PA to uninsured women from the birth of the child.                      Similarly, the PA could be reformed at least by increasing its maximum rate to 100% of the                net wage. The maximal alternative consists of integrating the PA into the MB, which would also                mean integration into the health insurance system. The proposed increase of the baby bonus to                CZK 300,000 is in contradiction with the modernisation of the PA according to the Swedish and                German patterns and OECD and EU recommendations. Moreover, the existing baby bonus of CZK                220,000 should be abolished in one or two steps. It is also necessary to abolish the spousal tax                credit – if we want to apply the social-democratic social model and remove this barrier to the                return or entry of mothers to the labour market.                      A  very  low  number  of  children  under  three  years  attend  crèches  and  similar  facilities,                which almost do not exist in Czechia. The EU’s target is the involvement of one-third of such                children in such types of childcare and educational facilities. If modern countries like Germany                and Sweden guarantee the right to a place in pre-school facilities from the child reaching one                year of age, we should be able to support the same arrangement in Czechia. Our main problem in                this  respect  is  that  the  present  Czech  minority  government  prefers  short-run  marketing                measures such as a big increase of parental allowance.                   4  Conclusion                       Czech  family  benefits  and  tax  credits  require  paradigm  reform,  which  would  serve  to                anchor  them  in  an  effective  social  model.  The  OECD  and  EU  lambast  the  Czech  parental                allowance  due  to  its  length  of  provision.  The  aggregate  full-rate  equivalent  of  the  maternity                benefit and parental allowance is 70.5 weeks!                      Partial  efforts  allowing  the  claiming  of  the  current  baby  bonus  of  CZK  220,000  over                shorter periods have not yet led to a change in the behaviour of mothers who continue to show a                preference for claiming the paid leave up to the child reaching 3 years of age. Overcoming this                approach requires paradigm reforms that will lead at least to the payment of both benefits (or                even better an integrated benefit) in the amount of the full net wage, preferably in the form of                full gross wage compensation accompanied by the taxation of the benefits, with a limit of 200%                of  NAE  and  a  minimum  (even  for  uninsured  mothers/parents)  of  50%  of  NAE.  In  order  to                achieve the desired macroeconomic effect, it is necessary to introduce the right to a place for all                children from one year of age in full-day preschool facilities at an affordable price or even free of                charge.  In  this  way  it  would  be  possible  to  “catch  up”  with  e.g.  Germany  or  Sweden.  The                proposed  increase  in  the  baby  bonus  to  CZK  300,000  is  in  contradiction  with  the  necessary                paradigm reforms aimed at the application of the simple and effective social-democratic social                model.                                                               251","Child  benefits  and  tax  credits  require  paradigm  reform,  too.  Neoliberal  efforts  at  the                international and domestic levels to apply tax credits to working low-income parents are not                effective enough and lead to constant attempts at the greater or lesser modification of child tax                credits and to the introduction of ever more complicated structures such as Universal Credit in                the UK. It is an unreasonable assumption that the reintroduction of universal child benefits as                the only form of such support for families with children in Czechia would reduce the interest of                parents in working; the opponents should consider that child benefits are fully deducted when                calculating  the  final  social  assistance  benefit.  The  social-democratic  social  model  is  highly                effective in this respect as well. However, we respect the potential public choice of the German                optional system of child benefits and tax deductions and the joint spousal taxation that fits well                into the Christian-democratic welfare regime.                  Acknowledgement                       This paper was elaborated as part of the RILSA Typology of Social Benefits and Events in                the Insurance and Non-insurance Social Security System in terms of Suitability and Effectiveness                project.                  References                 [1.]  CCAoA,  2018.  [online]  The  US  and  the  High  Cost  of  Child  Care.  A  Review  of  Prices  and  Proposed                     Solutions for a Broken System. 2018 Report, Arlington: Child Care Aware® of America. Available at                     https://cdn2.hubspot.net/hubfs/3957809/COCreport2018_1.pdf?__hssc=122076244.2.1548087797                     429\&__hstc=122076244.9571bc10aa585717dce110a9b86a8b47.1548087797429.1548087797429.                     1548087797429.1\&__hsfp=2573031793\&hsCtaTracking=b4367fa6-f3b9-4e6c-acf4-                     b5d01d0dc570%7C94d3f065-e4fc-4250-a163-bafc3defaf20                [2.]  EC, 2017. [online] Council recommendation on the 2017 National Reform Programme of the Czech                     Republic and delivering a Council opinion on the 2017 Convergence Programme of the Czech                     Republic. Available at https://ec.europa.eu/info/sites/info/files/2017-european-semester-country-                     specific-recommendations-commission-recommendations_-_czech_republic-cs.pdf                [3.]  ESPING-ANDERSEN, G. 1990. The Three Worlds of Welfare Capitalism. Cambridge: Polity Press \&                     Princeton: Princeton University Press.                [4.]  FERRARINI, T., NELSON, K., HÖÖG, H. 2012. [online] The Fiscalization of Child Benefits in OECD                     Countries. GINI Discussion Paper 49. Amsterdam Institute for Advanced Labour Studies (AIAS).                     Amsterdam: University of Amsterdam. Available at http://www.gini-                     research.org/system/uploads/381/original/DP_49_-Ferrarini_Nelson_H_g.pdf?1345650142                 [5.]  OECD, 2010. [online] OECD Economic Surveys: Czech Republic 2010. OECD Publishing, Paris. Available                     at https://read.oecd-ilibrary.org/economics/oecd-economic-surveys-czech-republic-                     2010_eco_surveys-cze-2010-en#page2                [6.]  OECD, 2017. [online] Parental Leave Systems. OECD Family database. Paris: OECD - Social Policy                     Division: Directorate of Employment, Labour and Social Affairs. Available at                     http://www.oecd.org/els/soc/PF2_1_Parental_leave_systems.pdf                 [7.]  Skolverket, 2018. [online] Preschool and preschool class. For your child aged 1-6. Available at                     http://www.omsvenskaskolan.se/engelska/foerskolan-och-foerskoleklass/                [8.]  WHITE, L. A. 2009. [online] The United States in Comparative Perspective: Maternity and Parental                     Leave and Child Care Benefits Trends in Liberal Welfare States. Yale Journal of Law \& Feminism;                     21(1): Available at                     https://digitalcommons.law.yale.edu/cgi/viewcontent.cgi?referer=\&httpsredir=1\&article=1298\&co                     ntext=yjlf                                                                     252","Splitting of Environmental Taxes Revenues in the EU                                                                a                                                                                         b                                 ZIMMERMANNOVÁ Jarmila , SKALIČKOVÁ Jolana                                 Moravian Business College Olomouc, Department of Economics, Czech Republic                                      a                         b                                       jarmila.zimmermannova@mvso.cz,  jolana.skalickova@mvso.cz                Abstract                 Currently, EU member states use different kinds of economic instruments of environmental protection.                Besides their environmental impact, the main reason for economic instruments implementation is their                fiscal impact, precisely revenues of public budgets. The main goal of this paper is to find similarities in EU-                28, to find the groups of countries with the same fiscal impact of economic instruments on public budget                revenues.  The  method  of  cluster  analysis  is  used,  based  on  EUROSTAT  and  EEX  data  sets  for  the  year                2016. Three categories of economic instruments’ revenues (per capita) are selected as a base for cluster                analysis, with available data for all EU-28 countries – energy taxes without EU ETS, EU ETS and transport                taxes. We can distinguish six clusters in total, precisely group A characteristic by low tax revenues and low                EU  ETS  revenues,  group  B  with  high  tax  revenues  and  low  EU  ETS  revenues,  group  C  with  low  tax                revenues and high EU ETS  revenues, group D represented  by middle tax revenues and middle EU ETS                revenues,  group  E  and  group  F,  both  represented  by  one  country  with  extremely  high  tax  revenues.                Generally, countries of Central and Eastern Europe are not grouped only in one group, they have all low                tax revenues, but there are differences in EU ETS revenues. Focusing on northern countries of EU, they are                characteristic by rather higher or high tax revenues, but they are also split into different clusters.                 Keywords: tax revenues; cluster analysis; energy taxation; transport taxation; EU ETS                JEL Classification: H23                    1  Introduction                       Currently,  EU  member  states  use  different  kinds  of  economic  instruments  of                environmental protection. Besides their environmental impact, the main reason for economic                instruments implementation is their fiscal impact, precisely revenues of public budgets. It is the                case of environmental taxes in the energy and transport sector, tradable emission allowances,                resource taxes/fees and pollution taxes/fees.                      Regarding  economic  instruments  use,  there  are  differences  between  particular  EU                member  states  –  different  taxes  are  imposed  in  old  EU  countries,  different  in  new  member                states,  northern  and  southern  countries.  Some  countries  also  use  regional  economic                instruments. Both the total number and the main focus of particular instruments depend on EU                legislation (mainly in the energy sector) and national legislation (mainly in the transport sector).                      The main goal of this paper is to find similarities in EU-28, to find the groups of countries                with  the  same  fiscal  impact  of  the  economic  instruments  of  environmental  policy  on  public                budget revenues.                      For this purpose, two research questions are proposed:                      1) Are there similar characteristics between the countries of Central and Eastern Europe?                      2) Are there similar characteristics between northern countries of the EU?                  2  Literature overview                       Environmental  policy  employs  a  range  of  instruments  for  environmental  protection.                Together with other devices, economic tools constitute a mix whose individual components are                chosen by the countries according to their environmental policy priorities.                      One of the fundamental instruments of the mix is a so-called environmental tax [24]. The                general concept of taxation for discharged pollution dwells on the idea that if the ecological and                                                               253","social costs are not included in activities generating them, the government may set their value by                applying appropriate taxes [16].                      Mentioned in connection with the problem of global climate change is carbon tax as one of                the environmental taxes usually imposed on the production, distribution or use of fossil fuels                [22].                      Focusing  on  emission  allowances  trading,  the  European  Union  established  the  EU                Emissions Trading System (EU ETS), dealing with greenhouse gas emissions. Within the EU ETS,                there  are  European  Emissions  Allowances  –  EUAs  (since  2005)  and  European  Aviation                Allowances  –  EUAAs  (since  2012).  The  regulatory  framework  of  the  EU  ETS  was  mostly                unchanged  for  the  first  two  trading  periods  of  its  operation  (2005  –  2012);  however,  the                beginning of the third trading period in 2013 brings changes in common rules which should                strengthen the system. Since the EU emission allowances were previously grandfathered [32]                from  the  year  2013  the  most  important  yield  of  the  emission  allowances  is  auctioned.                Grandfathering was widely criticised, mostly because it introduced significant distortions to the                EU ETS [11]. Auctioning is the most transparent method of allocating allowances and puts into                practice the polluter pays principle [9]. We can say that policymakers give firms an incentive to                move towards production that is less fossil-fuel intensive [1]. The market price of the allowances                is determined by supply and demand. In the third trading period, there has only been one big                exchange which can be used for emission rights trading – European Energy Exchange (EEX).                      Regarding the analyses and modelling of both environmental taxes and tradable emission                allowances  systems,  there  are  many  studies.  Focusing  on  environmental  taxes,  various                investigations are simulating general environmental taxation impacts [2], distributional impacts                [33] and competitiveness impacts [8]. Regarding the EU ETS, scientists have focused mostly on                modelling and forecasting the prices of CO2 emission allowances [3]; [20]; [5]; [13]; [19].                      If we focus on recent scientific studies dealing with the carbon tax, we find out that those                are namely case studies for specific countries analysing the impact of carbon tax introduction in                those countries  – for example in Spain  where  the  authors  focused  on  the direct  and indirect                effects of environmental tax on Spanish products, based on the CO2 emission intensities. For this                purpose, they applied environmental input-output (EIO) and price models; more details in for                example Gemechu et al. [14].                       Another scientific paper studies CO2 taxation in its dual role as a climate and a fiscal policy                instrument  in  Portugal  (more  details  in  Pereira  and  Pereira  [25]).  It  develops  marginal                abatement cost curves for CO2 emissions associated with CO2 taxation using a dynamic general                equilibrium model of the Portuguese economy. Another scientific study deals with carbon and                energy  taxation  in  Malaysia  (more  details  in  Solaymani  [29]),  which  is  one  of  the  top  CO2-                emitting  countries  in  the  ASEAN  region.  Other  examples  focused  on  the  economic  and                environmental effects of the carbon tax in South Africa use the dynamic CGE modelling approach                [30].                      Scientific studies investigating the third EU ETS trading period are focused mainly on the                analysis of the influence of the intervention of the regulator on the functioning of the EU ETS                system and its parameters, especially on the development of the EUA price. Cretí and Joëts [6]                deal with price bubbles, speculation and the development of the EUA price on the stock market.                The  authors  conclude  that  the  most  significant  fluctuations  in  prices  are  the  result  of  the                announcement of changes in climate protection or energy policies. A related theme is observed                by Fan et al. [12] as well; the study presents a detailed overview of political measures taken by                the regulator within the framework of the EU ETS system regarding the price of EUA permits                during  the  period  including  all  three  trading  phases  (2005–2015).  The  authors  focus  on  the                agreement between the expected outcome, based on theoretical hypotheses, with the real result                of the political measures taken and arrive at the conclusion that not all political activity leads in                the desired direction.                      Nevertheless,  those  events  which  did  have  a  crucial  influence  on  the  EU  ETS  system                demonstrate the theoretically awaited results, whether positive or negative. A study [28] focuses                on  the  analysis  of  decision-making  by  individual  ministries  of  finance  in  the  Netherlands,                Denmark  and  Germany  in  connection  with  intervention  in  and  the  regulation  of  the  EU  ETS                                                               254","system.  This  analysis  shows  that  these  ministries  were  integral  parts  of  the  decision-making                process. They supported intervention within the EU ETS framework, but, at the same time, also                had, in their countries, varying goals, both fiscal and macroeconomic. Furthermore, their final                decisions were determined by the political orientation of the given country (especially in the                cases of Germany and the Netherlands). The price of tradable emissions allowances in the EU-                ETS system is discussed by Brink et al. [4].                      They particularly pointed to the current price of emission allowance on the market with                emission allowances.                      Finally, some authors consider environmental taxes and emission allowances similar to                each other, namely in respect of their impact. For research into the interactions of the system of                taxation  with  the  environment-protection  policies,  Goulder  [15]  for  example,  includes  the                carbon tax, as well as the system of trading emission allowances into one group, called a “green                tax”. In his opinion, the two economic tools feature similar characteristics especially concerning                the use of their returns if the tradable emission allowances are sold in auctions.                  3  Material and Methods                       The method of cluster analysis is used, based on EUROSTAT [10] and EEX [7] data sets for                the  year  2016.  Environmental  taxes  revenues  are  published  by  EUROSTAT  in  categories  of                energy  taxes,  transport  taxes,  resource  taxes  and  pollution  taxes.  Unfortunately,  data  for                categories resource taxes and pollution taxes are not available for a significant part of countries.                On  the  other  hand,  EU  ETS  auctions  revenues  data  are  available  on  EEX.  Therefore,  three                categories of economic instruments’ revenues are selected as a base for cluster analysis, with                available data for all EU-28 countries.                      Cluster  analysis  methods  are  used  to  differentiate  objects  into  a  system  of  categories,                which on the one hand document the similarities of objects within a single category and on the                other  hand  underline  the  differences  of  objects  falling  into  different  categories  [18]  or  [23].                These methods are based on the usage of the rate of conformity (or rather non-conformity) of                objects and clusters. This rate of non-conformity is expressed as the Euclidian distance between                the two vectors Y and Z in Formula 1:                                                          .                                                             (1)                        The paper uses hierarchical procedures, i.e. gradual clustering including the combinations                of objects into clusters. The result is the construction of a hierarchy, or dendrogram (tree-like                structure), depicting the formation of the cluster [17].                      Ward’s linkage method was applied in this paper. Ward’s linkage method minimizes the                sum  of  squares  of  any  two  theoretical  clusters,  which  can  be  generated  at  every  step  of                clustering [31]. Ward’s method is treated as rather efficient, and it considers the size of the data                sample, we are entitled to utilize it. It will get the optimal number of clusters, which will be                further presented.                      The  cluster  analysis  is  often  applied  to  analyse  of  territorial  units,  e.g.  in  the  regional                analysis of the localization of large enterprises [27] or in research focused on the development                of heterogeneity of EU countries [26].                   4  Results and Discussion                       Table  1  contains  the  basic  descriptive  characteristics  of  the  selected  variables.  The                outcomes show minimum, maximum, mean, standard deviation and variance.                      We can see that revenues from the energy taxes, EU ETS and transport taxes have a high                value of the variance. It is caused by different systems of environmental protection. There are                                                                 255","large disparities between the minimum and maximum values in all types of revenues within the                EU countries.                                           Table 1: Descriptive Characteristics of Variables                              Revenues              N   Minimum  Maximum    Mean   Std. Deviation   Variance                 Energy taxes without EU ETS, per capita  28   148.12   1461.66   521.09   296.78   88083.09                          EU ETS, per capita      28    0.32      18.06    8.48      3.71       13.83                      Transport taxes, per capita   28   9.52    766.59   164.38    171.44     29394.58                 Source: own processing, based on EUROSTAT [10] and EEX [7].                       For  our  research,  the  correlation  analysis  was  used  at  first.  The  variables  that  have  a                correlation coefficient higher than 0.9 could distort the results of further investigation. There are                no  significant  relationships  between  analyzed  indicators.  The  data  was  standardized  by  the                standard deviation for cluster analysis purposes. The number of observations was 28 for each                indicator and state.                                                 Table 2: Agglomeration schedule                                 Cluster Combined                 Stage Cluster First Appears                       Stage                        Coefficients                           Next Stage                               Cluster 1   Cluster 2               Cluster 1   Cluster 2                         1        15        21         0.015          0            0           12                         2        2         25         0.051          0            0           9                         3        3         14         0.112          0            0           13                         4        5         24         0.203          0            0           18                         5        9         22         0.297          0            0           17                         6        7         19         0.401          0            0           11                         7        12        28         0.515          0            0           14                         8        11        17         0.681          0            0           12                         9        2         23         0.907          2            0           13                        10        1         18         1.159          0            0           18                        11        7         20         1.474          6            0           19                        12        11        15         1.818          8            1           17                        13        2          3         2.225          9            3           21                        14        12        27         2.668          7            0           20                        15        10        13         3.194          0            0           20                        16        6          8         4.105          0            0           21                        17        9         11         5.155          5           12           23                        18        1          5         6.294         10            4           22                        19        7         26         7.885         11            0           22                        20        10        12         9.955         15           14           23                        21        2          6         12.992        13           16           26                        22        1          7         16.950        18           19           25                        23        9         10         23.089        17           20           26                        24        4         16         31.157         0            0           25                        25        1          4         40.301        22           24           27                        26        2          9         59.518        21           23           27                        27        1          2         81.000        25           26           0                Source: own processing, based on EUROSTAT [10] and EEX [7].                      Table 2 shows how the states are joined at each stage of the cluster analysis. This process                of connection progresses until the moment in time when all the EU states are joined in one large                cluster, which is represented by line 27. The coefficients represent the distances between two                states or two already created clusters, joined on the next level. The next part of the table shows                the phase when each cluster emerged. The last column shows the phase when the newly created                cluster combined with another, already existing cluster.                      Figure 1 presents the results of cluster analysis, the dendrogram using Ward linkage. It                shows detected similarities between regions.                                                               256","Figure 1: Results of cluster analysis for EU countries                                                                          Source: own processing, based on EUROSTAT [10] and EEX [7].                      Based on the dendrogram, we can distinguish six clusters in total, precisely:                      ·  group  A,  characteristic  by  low  tax  revenues  and  low  EU  ETS  revenues  (Lithuania,                         Poland, Croatia, Hungary, Spain, Portugal),                      ·  group B, with high tax revenues and low EU ETS revenues (Italy, UK, Sweden, France,                         Cyprus),                      ·  group C, with low tax revenues and high EU ETS revenues (Czechia, Latvia, Bulgaria,                         Slovakia, Romania, Estonia, Greece),                      ·  group D, represented by middle tax revenues and middle EU ETS revenues (Germany,                         Slovenia, Belgium, Malta, Ireland, Netherlands, Austria, Finland),                      ·  group E, represented by one country with extremely high tax revenues (Denmark),                      ·  group F, represented by one country with extremely high tax revenues (Luxembourg).                       In  the  beginning,  two  research  questions  were  set.  Regarding  evaluation  of  the  first                research  question  (“Are  there  similar  characteristics  between  the  countries  of  Central  and                                                               257","Eastern Europe?”), it is obvious, that countries of Central and Eastern Europe are not grouped                only in one group, they have all low tax revenues, but there are differences in EU ETS revenues.                Based on the results, we can see countries of Central and Eastern Europe in group A – Lithuania,                Poland, Hungary; group C – Czechia, Latvia, Bulgaria, Slovakia, Romania, Estonia; and group D -                Slovenia. The group, which is the most typical for countries of Central and Eastern Europe is                group C, with low tax revenues and high EU ETS revenues. There is only one additional state,                Greece.                      Concerning  the  second  research  question  (“Are  there  similar  characteristics  between                northern  countries  of  EU?”),  we  can  say  that  northern  countries  of  EU  are  characteristic  by                rather higher or high tax revenues, but they are split to different clusters. We can see northern                countries of EU in group B – Sweden, group D – Belgium, Netherlands, Finland) and group E –                Denmark.  The  group,  which  is  the  most  typical  for  northern  countries  of  EU  is  group  D,                represented by middle tax revenues and middle EU ETS revenues.                      Since the analysis is based only on revenues data from the year 2016 and other economic                data were not involved, we can only estimate that the groups of countries are also influenced by                similar  economic  development.  It  will  be  worth  in  future  research  to  add  more  economic                variables to the cluster analysis or to compare clusters in different years.                      Regarding the results, the general recommendation for policymakers can be to focus on                why there are in some countries lower tax revenues than in the rest of them. Dealing with EU                ETS revenues, some countries are probably better traders and can earn more money from the                auctions since the auction prices depend on current demand on the exchange [35].                      Comparing the results with other scientific studies, Liapis et al. [21] focused on clusters of                economic similarities between EU countries, calculating with different categories of economic                indicators,  including  tax  revenues.  Based  on  the  study,  within  the  area  of  tax  revenues,  the                notable groups of countries are Belgium and Italy, Greece and Portugal, Germany and Austria,                Finland and Sweden. The other countries are left alone. However, this analysis [21] does not                include all EU countries and the environmental tax revenues are not included in the category                “tax revenues”.                      Another study by Zaharia et al. [34] focuses on environmental taxation in EU countries,                but EU ETS is a part of category energy taxes. Based on the study, clusters in the year 2012 were                represented  as  follows:  cluster  1  comprises  Bulgaria,  the  Czech  Republic,  Germany,  Estonia,                Latvia,  Luxembourg,  Hungary,  Poland,  Portugal,  Sweden,  United  Kingdom;  cluster  2  includes                Greece,  Italy,  Cyprus,  Malta,  Austria,  Finland;  cluster  3  consists  of  Spain,  France,  Lithuania,                Romania,  Slovakia;  cluster  4  composes  of  Belgium,  Ireland,  Iceland  and  Norway;  cluster  5                includes Denmark, Croatia and Netherlands and cluster 6 consists of only one country: Slovenia.                  5  Conclusion                       The  main  goal  of  this  paper  was  to  find  similarities  in  EU-28,  to  find  the  groups  of                countries with the same fiscal impact of the economic instruments of environmental policy on                public budget revenues. The method of cluster analysis was used, based on EUROSTAT and EEX                data sets for the year 2016. Three categories of economic instruments’ revenues (per capita)                were selected as a base for cluster analysis, with available data for all EU-28 countries – energy                taxes without EU ETS, EU ETS and transport taxes.                      Based on the results, we can distinguish six clusters in total, precisely group A (Lithuania,                Poland, Croatia, Hungary, Spain, Portugal) characteristic by low tax revenues and low EU ETS                revenues, group B (Italy, UK, Sweden, France, Cyprus) with high tax revenues and low EU ETS                revenues, group C (Czechia, Latvia, Bulgaria, Slovakia, Romania, Estonia, Greece), with low tax                revenues  and  high  EU  ETS  revenues,  group  D  (Germany,  Slovenia,  Belgium,  Malta,  Ireland,                Netherlands, Austria, Finland) represented by middle tax revenues and middle EU ETS revenues,                group E (Denmark) and group F (Luxembourg), both represented by one country with extremely                high tax revenues. Generally, countries of Central and Eastern Europe are not grouped only in                one  group,  they  have  all  low  tax  revenues,  but  there  are  differences  in  EU  ETS  revenues.                                                               258","Focusing  on  northern  countries  of  EU,  they  are  characteristic  by  rather  higher  or  high  tax                revenues, but they are also split into different clusters.                      Regarding  our  future  research,  it  will  be  worth  to  add  more  economic  variables  to  the                cluster analysis, to focus on spatial aspects of particular economic instruments of environmental                policy or to compare clusters in different years. It can help to improve the efficiency of both the                tools and the policy as a whole.                  References                 [1.]  AATOLA, P., OLLIKAINEN, M., TOPPINEN, A. 2013. 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Procedia Economics and Finance, 12, 788-796.                                                                                          260","obalka a vstupy Current trends_23_Sestava 1  18.06.2019  9:56  Stránka 6                         Partners of the Faculty of Economics and Administration, Masaryk University                    Important / Main partners:                             Partners:                                               CURRENT TRENDS IN PUBLIC SECTOR RESEARCH                                               rd                  Proceedings of the 23 International Conference                  organised by the Department of Public Economics,                   Faculty of Economics and Administration, Masaryk University                    Editor: Petra Dvořáková                  Technical editor: Petra Dvořáková                  Editorial Board: P. Pirožek, P. Suchánek, M. Viturka, V. Hyánek, E. Hýblová,                  D. Němec, M. Matulová                  Published by Masaryk University, 2019                     st                  1 edition, 2019                     ISSN 2336-1239                  ISBN 978-80-210-9256-3                  ISBN 978-80-210-9257-0 (online : pdf)                  https://doi.org/10.5817/CZ.MUNI.P210-9257-2019",""];