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Rozdiely v efektívnosti inovačných systémov Slovenska a vybraných krajín Európskej únie
[Differences in Efficiency of National Innovation Systems of Slovakia and Selected EU Countries]

Author

Listed:
  • Peter Adamovský
  • Vladimír Gonda

Abstract

The aim of the paper is to identify differences in innovation efficiency of national innovation systems of Slovakia and selected countries of the European Union (Austria, Belgium, Bulgaria, the Czech Republic, Estonia, Germany, Romania and Sweden) in the period 2006-2015. The relative efficiency model applied uses a non-parametric method known as data envelopment analysis (DEA) in a super-efficiency version with a constant-returns-to-scale technology and input orientation. The data selection is based on innovation indicators and methodological aspects of the model. The authors discovered that Austria and Germany achieved an efficient score for technological efficiency, Belgium, Estonia, Romania and Slovakia for economic efficiency, and only Austria for overall efficiency. The research identifies peers for Slovakia among all the EU countries at all levels of efficiency, provides several recommendations for improvement and also confirms the existence of small countries' resulting bias.

Suggested Citation

  • Peter Adamovský & Vladimír Gonda, 2019. "Rozdiely v efektívnosti inovačných systémov Slovenska a vybraných krajín Európskej únie [Differences in Efficiency of National Innovation Systems of Slovakia and Selected EU Countries]," Politická ekonomie, Prague University of Economics and Business, vol. 2019(2), pages 181-197.
    • Handle: RePEc:prg:jnlpol:v:2019:y:2019:i:2:id:1234:p:181-197
    DOI: 10.18267/j.polek.1234
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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Cooke, Philip & Gomez Uranga, Mikel & Etxebarria, Goio, 1997. "Regional innovation systems: Institutional and organisational dimensions," Research Policy, Elsevier, vol. 26(4-5), pages 475-491, December.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Elias G. Carayannis & Urmas Varblane & Tõnu Roolaht (ed.), 2012. "Innovation Systems in Small Catching-Up Economies," Innovation, Technology, and Knowledge Management, Springer, number 978-1-4614-1548-0, December.
    6. Tõnu Roolaht, 2012. "The Characteristics of Small Country National Innovation Systems," Innovation, Technology, and Knowledge Management, in: Elias G. Carayannis & Urmas Varblane & Tõnu Roolaht (ed.), Innovation Systems in Small Catching-Up Economies, chapter 0, pages 21-37, Springer.
    7. Joe Sarkis, 2007. "Preparing Your Data for DEA," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 305-320, Springer.
    8. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    9. Barro, Robert J, 1990. "Government Spending in a Simple Model of Endogenous Growth," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 103-126, October.
    10. Malerba, Franco, 2002. "Sectoral systems of innovation and production," Research Policy, Elsevier, vol. 31(2), pages 247-264, February.
    11. Carlsson, B & Stankiewicz, R, 1991. "On the Nature, Function and Composition of Technological Systems," Journal of Evolutionary Economics, Springer, vol. 1(2), pages 93-118, April.
    12. Wade D. Cook & Joe Zhu, 2007. "Data Irregularities And Structural Complexities In Dea," Springer Books, in: Joe Zhu & Wade D. Cook (ed.), Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, chapter 0, pages 1-11, Springer.
    13. Maxim Kotsemir, 2013. "Measuring National Innovation Systems Efficiency - A Review of DEA Approach," Post-Print hal-00865875, HAL.
    14. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    15. McDermott, Gerald A & Mejstrik, Michal, 1992. "The Role of Small Firms in the Industrial Development and Transformation of Czechoslovakia," Small Business Economics, Springer, vol. 4(3), pages 179-200, September.
    16. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
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    More about this item

    Keywords

    data envelopment analysis (DEA); super-efficiency; national innovation system; Slovak Republic; European Union;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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