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The Efficiency and Productivity Evaluation of National Innovation Systems in Europe

Abstract

Purpose: An efficient innovation system currently plays a crucial role in creating competitive prevalence, contributing to the economic growth of individual states. The innovation system is influenced by many socioeconomic factors, including in international rankings of innovativeness of economies. These classifications have some limitations. Primarily, they do not examine the efficiency, which means they do not analyze the relationship between the involved inputs and the relevant outputs generated in the innovation system. The study aims to measure the efficiency and productivity of the European state's innovation system based on the data from the international ranking of economies' innovation. Design/Methodology/Approach: In this study, the changes in the efficiency and productivity of the innovation system coming from European states were measured using the DEA and Malmquist index methods, based on data from the European Innovation Scoreboard international ranking innovation in economies. The maximizing of economic benefits was assumed in its impact on employment and sales in a given state. The non-radial SBM model, Super SBM, and Malmquist index based on SBM were used for the research. 27 European states were subjected to the analysis in the period from 2012 to 2019. Findings: The research results indicate that the average level of efficiency in the surveyed period fluctuated around 70%. Higher results of efficiency were achieved more frequently by states that joined the EU after 2004. The increase in the productivity of individual states was caused most frequently by an increase in their efficiency (catch-up effect) and less frequently by shifting the efficiency frontier (frontier effect). Practical Implications: The following research hypothesis was decided to be laid down: developing states and those newly admitted to the European Union after 2004 have been gaining relatively more economic benefits from smaller national innovation systems (NIS) resources than developed states and the so-called states of the "old Union." Originality/Value: The added value of the article is, first of all, a comprehensive measurement of the efficiency and productivity of European states NIS in three aspects - efficiency status, efficiency ranking, and productivity changes assessment.

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Category:
Magazine publication
Type:
Magazine publication
Published in:
European Research Studies Journal no. 24, edition 3, pages 471 - 496,
ISSN: 1108-2976
Publication year:
2021
DOI:
Digital Object Identifier (open in new tab) http://dx.doi.org/10.35808/ersj/2440
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  1. Abodunrin, O., Oloye, G., Adesola, B. 2020. Coronavirus pandemic and its implication on global economy. International Journal of Arts, Languages and Business Studies, 4, 3-23.
  2. Afzal, M.N.I. 2014. An empirical investigation of the National Innovation System (NIS) using Data Envelopment Analysis (DEA) and the TOBIT model. International Review of Applied Economics, 28(4), 507-523. DOI: 10.1080/02692171.2014.896880. open in new tab
  3. Bak, I., Cheba, K., Lacka, I. 2020. Sustainable Development and Innovations. How They Work Together? European Research Studies Journal, 23(3), 93-113. DOI: 10.35808/ersj/1627. open in new tab
  4. Banker, R.D., Charnes, A., Cooper, W.W. 1984. Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30, 1078- 1092. DOI: 10.1287/mnsc.30.9.1078. open in new tab
  5. Barbero, J., Zabala-Iturriagagoitia, J.M., Zofio, J.L. 2021. Is more always better? On the relevance of decreasing returns to scale on innovation. Technovation, 107, 102314. DOI: 10.1016/j.technovation.2021.102314. open in new tab
  6. Carayannis, E.G., Barth, T.D., Campbell, D.F. 2012. The Quintuple Helix innovation model: global warming as a challenge and driver for innovation. Journal of Innovation and Entrepreneurship, 1(2), 1-12. DOI: 10.1186/2192-5372-1-2. open in new tab
  7. Carayannis, E.G., Campbell, D.F.J. 2009. 'Mode 3' and 'Quadruple Helix': Toward a 21 st century fractal innovation ecosystem. International Journal of Technology Management, 46(3/4), 201-234. DOI: 10.1504/IJTM.2009.023374. open in new tab
  8. Carayannis, E.G., Campbell, D.F.J. 2010. Triple Helix, Quadruple Helix and Quintuple Helix and how do knowledge, innovation and the environment relate to each other? A proposed framework for a trans-disciplinary analysis of sustainable development and social ecology. International Journal of Social Ecology and Sustainability Development, 1(1), 41-69. DOI: 10.4018/jsesd.2010010105. open in new tab
  9. Carayannis, E.G., Campbell, D.F.J. 2014. Developed democracies versus emerging autocracies: arts, democracy, and innovation in Quadruple Helix innovation system. Journal of Innovation Entrepreneurship, 3(1), 12. DOI: 10.1186/s13731-014-0012-2. open in new tab
  10. Carayannis, E.G., Grigoroudis, E., Goletsis, Y. 2016. A multilevel and multistage efficiency evaluation of innovation systems: A multiobjective DEA approach. Expert Systems with Applications, 62, 63-80. DOI: 10.1016/j.eswa.2016.06.017. open in new tab
  11. Carvalho, N., Carvalho, L., Nunes, S. 2015. A methodology to measure innovation in European Union through the national innovation system. International Journal of Innovation and Regional Development, 6(2), 159-180. DOI: 10.1504/IJIRD.2015.069703. open in new tab
  12. Castellacci, F., Nater, J.M. 2013. The dynamics of national innovation systems: A panel cointegration analysis of the coevolution between innovative capability and absorptive capacity. Research Policy, 42(3), 579-594. DOI: 10.1016/j.respol.2012.10.006. open in new tab
  13. Caves, D.W., Christensen, L.R., Diewert, W.E. 1982. The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50, 1393-1414. DOI: 10.2307/1913388. open in new tab
  14. Charnes, A., Cooper, W.W., Rhodes, E. 1978. Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444. DOI: 10.1016/0377- 2217(78)90138-8. open in new tab
  15. Cooper, W.W., Seiford, L.M., Tone, K. 2007. Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software. 2 nd ed. New York, Springer. open in new tab
  16. Cornell University, INSEAD, WIPO. 2020. The Global Innovation Index 2020: Who Will Finance Innovation? Ithaca, Fontainebleau, Geneva.
  17. Edquist, C., Zabala-Iturriagagoitia, J.M., Barbero, J., Zofio, J.L., 2018. On the meaning of innovation performance: is the synthetic indicator of the Innovation Union Scoreboard flawed? Research Evaluation, 27(3), 196-211. DOI: 10.1093/reseval/rvy011. European Commission. 2019. The European Green Deal. Retrieved from: https://eur- lex.europa.eu/legal-content/ open in new tab
  18. EN/TXT/?qid=1588580774040&uri=CELEX:52019DC0640/.
  19. European Commission. 2010. Europe 2020. A strategy for smart, sustainable and inclusive growth. Retrieved from: https://eur-lex.europa.eu/legal- content/EN/TXT/PDF/?uri=CELEX:52010DC2020&from =EN/.
  20. European Union. 2020. European Innovation Scoreboard 2020. Luxembourg. open in new tab
  21. Färe, R., Grosskopf, S., Lindgren, B., Roos, P. 1992. Productivity change in Swedish pharmacies 1980-1989: A nonparametric Malmquist approach. Journal of Productivity Analysis, 3, 85-102. DOI: 10.1007/BF00158770. open in new tab
  22. Färe, R., Grosskopf, S., Lindgren, B., Roos, P. 1994. Productivity Developments in Swedish Hospitals: A Malmquist Output Index Approach. In: Charnes, A., Cooper, W.W., Lewin, A.Y., Seiford, L.M. (Eds). Data Envelopment Analysis: Theory, Methodology and Applications, Dordrecht, Springer, 253-272. open in new tab
  23. Freeman, C. 1987. Technology and economic performance: Lesson from Japan. London: Pinter Publisher. open in new tab
  24. George, G., Lakhami, K.R., Puranam, Ph. 2020. What has changed? The Impact of Covid Pandemic on the Technologic and Innovation Management Research Agenda. Journal of Management Studies, 57(8), 1754-1758. DOI: 10.1111/joms.12634. open in new tab
  25. Gern, K.J., Hauber, P. 2020. Business cycle highlight: Coronavirus keeps the global economy in suspense. Wirtschaftsdienst, 100(3), 223-224. DOI: 10.1007/s10273-020-2607-5. open in new tab
  26. Griffith, R., Redding, S., Van Reenen, J. 2004. Mapping the Two Faces of R&D: Productivity Growth in a Panel of OECD Industries. The Review of Economics and Statistics, 86(4), 883-895. DOI: 10.1162/0034653043125194. open in new tab
  27. Guan, J., Chen, K. 2012. Modeling the relative efficiency of national innovation systems. Research Policy, 41(1), 102-115. DOI: 10.1016/j.respol.2011.07.001. open in new tab
  28. Jurickova, E., Pilik, M., Kwarteng, M.A. 2019. Efficiency measurement of National Innovation Systems of the European Union countries: DEA Model Application. Journal of International Studies, 12(4), 286-299. DOI: 10.14254/2071-8330.2019/12-4/19. open in new tab
  29. Karadayi, M.A., Ekinci, Y. 2019. Evaluating R&D performance of EU countries using categorical DEA. Technology Analysis & Strategic Management, 31(2), 227-238. DOI: 10.1080/09537325.2018.1493191. open in new tab
  30. Karahan, O. 2017. The Relationship between national innovative capability and performance in Europe. Journal of Business, Economics and Finance, 6(1), 53-30. DOI: 10.17261/Pressacademia.2017.385. open in new tab
  31. Kim, E.S., Bae, K.J., Byun, J. 2020. The History and Evolution: A Big Data Analysis of the National Innovation Systems in South Korea. Sustainability, 12(3), 1266. DOI: 10.3390/su12031266. open in new tab
  32. Kim, Y., Park, S., Kwon, K.-S. 2020. Forecasting the Environmental Change of Technological Innovation System in South Korea in the COVID-19 Era. Asian Journal of Innovation and Policy, 9(2), 133-144. DOI: 10.7545/ajip.2020.9.2.133. open in new tab
  33. Kontolaimou, A., Giotopoulos, I., Tsakanikas, A. 2016. A typology of European countries based on innovation efficiency and technology gaps: The role of early-stage entrepreneurship. Economic Modelling, 52, 477-484. DOI: 10.1016/j.econmod.2015.09.028. open in new tab
  34. Leydesdorff, L. 2012. The Triple Helix, Quadruple Helix …, and an N-tuple of Helices: Explanatory Models for Analyzing the Knowledge-based Economy? Journal of Knowledge Economy, 3(1), 25-35. DOI: 10.1007/s13132-011-0049-4. open in new tab
  35. Lu, W.-M., Kweh, Q.L., Huang, C.-L. 2014. Intellectual capital and national innovation systems performance. Knowledge-Based Systems, 71, 201-210. DOI: 10.1016/j.knosys.2014.08.001. open in new tab
  36. Lundvall, B.-Å. (Ed.). 1992. National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning. London: Pinter Publishers.
  37. Lundvall, B.-Å. 1985. Product Innovation and User-Producer Interaction. Industrial Development Research Series No. 31. Aalborg: Aalborg University Press. open in new tab
  38. Lundvall, B.-Å. 1988. Innovation as an Interactive Process: From User Producer Interaction to National systems of Innovation. In: Dosi, G., Freeman, C., Nelson, R., Silverberg, G., Soete, L. (Eds.). Technical Change and Economic theory, London-New York: Pinter Publishers, 349-370.
  39. Lundvall, B.-Å. 2007. National Innovation Systems -Analytical Concept and Development Tool. Industry and Innovation, 14(1), 95-119. DOI: 10.1080/13662710601130863. open in new tab
  40. Lundvall, B.-Å., Vang, J., Joseph, K.J., Chaminade, C. 2009. Innovation system research and developing countries. In: Lundvall B.-Å., Joseph K.J., Chaminade C., Vang J. (Eds). Handbook of innovation systems and developing countries: Building domestic capabilities in a global setting, Northampton, MA, Edward Elgar, 1-32. open in new tab
  41. Mastromarco, C., Simar, L. 2021. Latent heterogeneity to evaluate the effect of human capital on world technology frontier. Journal of Productivity Analysis, 55, 71-89. DOI: 10.1007/s11123-021-00597-x. open in new tab
  42. Nelson, R.R., Rosenberg, N. 1993. Technical Innovation and National Systems. In: Nelson, R.R., editors. National Innovation Systems: A Comparative Analysis, Oxford: Oxford University Press, p. 3-21.
  43. Pakulska, J. 2021. The Eco-Innovation versus Economic Development on the EU Example. European Research Studies Journal, 24(1), 999-1008. DOI: 10.35808/ersj/2007. open in new tab
  44. Pan, T.-W., Hung, S.-W., Lu, W.-M. 2010. DEA performance measurement of the national innovation system in Asia and Europe. Asia-Pacific Journal of Operational Research, 27(3), 369-392. DOI: 10.1142/S0217595910002752. open in new tab
  45. Patel, P., Pavitt, K. 1994. The nature and economic importance of national innovations systems. STI Review, 14, 9-32. open in new tab
  46. Reinhart, C., Reinhart, V. 2020. The Pandemic Depression. The Global Economy Will Never Be the Same. Foreign Affairs, 99(5). September/October. open in new tab
  47. Simar, L., Wilson, P.W. 2007. Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136(1), 31-64. DOI: 10.1016/j.jeconom.2005.07.009. open in new tab
  48. Tone, K. 2001. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130, 498-509. DOI: 10.1016/S0377-2217(99)00407- open in new tab
  49. Tone, K. 2002. A slacks-based measure of super-efficiency in data envelopment analysis. European Journal of Operational Research, 143, 32-41. DOI: 10.1016/S0377- 2217(01)00324-1. open in new tab
  50. Tone, K. 2004. Malmquist productivity index: efficiency change over time. In: Cooper, W.W., Seiford, L.M., Zhu, J. (Eds). Handbook on data envelopment analysis. Boston, Kluwer Academic Publishers, 203-227. open in new tab
  51. Tone, K. 2017a. Non-radial DEA models. In: Tone, K. (Ed). Advances in DEA theory and applications: with extensions to forecasting models. Hoboken, John Wiley & Sons, 11-19. DOI: 10.1002/9781118946688.ch2. open in new tab
  52. Tone, K. 2017b. Super-Efficiency DEA Models. In: Tone., K. (Eds). Advances in DEA theory and applications: with extensions to forecasting models. Hoboken, John Wiley & Sons, 28-32. DOI: 10.1002/9781118946688.ch4. open in new tab
  53. UNDP. 2017. Spark, Scale, Sustainable Innovation for the Sustainable Goals. Retrieved from: https://www.undp.org/content/undp/en/home/librarypage/development-impact/spark- _-scale-_-sustain---2016-year-in-review.html. open in new tab
  54. United Nations. 2015. Transforming our World: the Agenda 2030 for Sustainable Development. Retrieved from: https://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E/. open in new tab
  55. Watkins, A., Papaioannou, T., Mugwagwa, J., Kale, D. 2015. National innovation systems and the intermediary role of industry associations in building institutional capacities for innovation in developing countries: A critical review of the literature. Research Policy, 44(8), 1407-1418. DOI: 10.1016/j.respol.2015.05.004. open in new tab
  56. Zabala-Iturriagagoitia, J.M., Aparicio, J., Ortiz, L., Carayannis, E.G., Grigoroudis, E. 2020. The productivity of national innovation systems in Europe: Catching up or falling behind? Technovation, 102215. DOI: 10.1016/j.technovation.2020.102215. Country 2012- 2013 2013- 2014 2014- 2015 2015- 2016 2016- 2017 2017- 2018 2018- 2019 open in new tab
  57. Table A7. Frontier effect Country 2012- 2013 2013- 2014 2014- 2015 2015- 2016 2016- 2017 2017- 2018 2018- 2019 open in new tab
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