Advertisement

Small Business Economics

, Volume 47, Issue 2, pp 313–330 | Cite as

Science parks and regional innovation performance in fiscal austerity era: Less is more?

  • Areti Gkypali
  • Vasileios Kokkinos
  • Christos Bouras
  • Kostas TsekourasEmail author
Article

Abstract

European financial crisis has raised questions about the sustainability and the contribution of innovation anchors especially in Southern European countries such as Greece. This paper utilizes the concept of regional innovation systems (RISs) and introduces a methodological approach that allows for evaluating an Science and Technology Park’s (STP) contribution into the corresponding RIS performance, taking into consideration (1) the RIS idiosyncrasies, (2) the dominant role of government expenditures on R&D and (3) the underlying complexity of knowledge production and management, under alternative sets of restrictions imposed by fiscal consolidation on the preferences of authorities which design and implement Science, Technology and Innovation (STI) policies. Our framework relies on the estimation of a multi-input–multi-output latent knowledge production function approach and the corresponding efficiency indices. Data requirements are sourced from the Regional Innovation Scoreboard, for the four Greek regions and from a small-scale case study, with respect to the examined regional STP covering the period from 2000 to 2012. The main empirical findings highlight that the contribution of the examined STP in the corresponding RIS performance diminishes alongside with the decrease in GERD investment levels, with respect to all the efficiency indices. These findings are attributed to the structural characteristics of both the RIS and the STP under investigation, and capture their dependence on managing public financial resources for STI activities.

Keywords

Science and Technology Parks Regional innovation system Efficiency Financial crisis Dominant policy input Structural equation modeling 

JEL Classifications

D24 L25 L32 O38 R11 R58 

Notes

Acknowledgments

The authors acknowledge that the starting point and the drive of this paper have been generated in the context of the INTERREG IVC project ‘InCompassRegional Policy Improvement for Financially Sustainable Creative Incubator Units’ (Contract Number 1127R4). In this framework, we would like to thank all the project partners and employees of several Technology Parks and Incubators around Europe for sharing of information and experience. We owe special thanks to Patras Science Park employees for their kindness to provide any data we required. This research has been partially cofinanced by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Programme ‘Education and Lifelong Learning’ of the National Strategic Reference Framework (NSRF)—Research Funding Programme: Thales, investing in knowledge society through the European Social Fund under Grant MIS 380232.

References

  1. Antonopoulos, C., Papadakis, V., Stylios, C., Efstatiou, M., & Groumpous, P. (2009). Mainstreaming Innovation Policy in less favoured regions: The case of Patras Science Park, Greece. Science and Public Policy, 36, 511–521.CrossRefGoogle Scholar
  2. Arvanitis, S., & Stucki, T. (2012). What determines the innovation capability of firm founders? Industrial and Corporate Change, 21, 1049–1084.CrossRefGoogle Scholar
  3. Audretsch, D. (2001). The Prospects for a Technology Park at Ames: A new economy model for industry–government partnership? In C. Wessner (Ed.), A review of the new initiatives at the NASA Ames Research Center. Washington, DC: National Research Council.Google Scholar
  4. Audretsch, D., & Link, A. (2012). Entrepreneurship and innovation: Public policy frameworks. The Journal of Technology Transfer, 37, 1–17.CrossRefGoogle Scholar
  5. Audretsch, D. B., & Vivarelli, M. (1995). New firm formation in Italy. Economics Letters, 48, 77–81.CrossRefGoogle Scholar
  6. Audretsch, D. B., & Vivarelli, M. (1996). Determinants of new-firm startups in Italy. Empirica, 23, 91–105.CrossRefGoogle Scholar
  7. Autio, E. (1998). Evaluation of RTD in regional systems of innovation. European Planning Studies, 6, 131–140.CrossRefGoogle Scholar
  8. Bakouros, Y. L., Mardas, D. C., & Varsakelis, N. C. (2002). Science park, a high-tech fantasy? An analysis of the science parks of Greece. Technovation, 22, 123–128.CrossRefGoogle Scholar
  9. Barbero, J. L., Casillas, J. C., Ramos, A., & Guitar, S. (2012). Revisiting incubation performance: How incubator typology affects results. Technological Forecasting and Social Change, 79, 888–902.CrossRefGoogle Scholar
  10. Baumol, W. J. (1990). Entrepreneurship: Productive, unproductive and destructive. Journal of Political Economy, 98, 893–921.CrossRefGoogle Scholar
  11. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.CrossRefGoogle Scholar
  12. Broekel, T. (2012). Collaboration intensity and regional innovation efficiency in Germany—A conditional efficiency approach. Industry and Innovation, 19(3), 155–179.CrossRefGoogle Scholar
  13. Caracostas, P. (2007). The policy-shaper’s anxiety at the innovation kick. In F. Malerba & S. Brusoni (Eds.), Perspectives on innovation. Cambridge: Cambridge University Press.Google Scholar
  14. Coelli, T. J., Prasada Rao, D. S., & Battese, G. (2006). An introduction to efficiency and productivity analysis. Norwell: Kluwer Academic Publishers.Google Scholar
  15. Colombo, M. G., & Grilli, L. (2005). Founders’ human capital and the growth of new technology-based firms: A competence-based view. Research Policy, 34, 795–816.CrossRefGoogle Scholar
  16. Colombo, M. G., & Grilli, L. (2010). On growth drivers of high-tech start-ups: Exploring the role of founders’ human capital and venture capital. Journal of Business Venturing, 25, 610–626.CrossRefGoogle Scholar
  17. Colombo, M. G., Grilli, L., & Giannangeli, S. (2013). Public subsidies and the employment growth of high-tech start-ups: Assessing the impact of selective and automatic support schemes. Industrial and Corporate Change, 22(5), 1273–1314.CrossRefGoogle Scholar
  18. Cooke, P. (2001). Regional innovation systems, clusters, and the knowledge economy. Industrial and Corporate Change, 10, 945–974.CrossRefGoogle Scholar
  19. Doloreux, D. (2004). Regional innovation systems in Canada: A comparative study. Regional Studies, 38(5), 481–494.CrossRefGoogle Scholar
  20. Doloreux, D., & Parto, S. (2005). Regional innovation systems: Current discourse and unresolved issues. Technology in Society Journal, 27, 133–153.CrossRefGoogle Scholar
  21. Dosi, G., Marsili, O., Orsenigo, L., & Salvatore, R. (1995). Learning, market selection and the evolution of industrial structures. Small Business Economics, 7, 411–436.CrossRefGoogle Scholar
  22. Edquist, C. (Ed.). (1997). Systems of innovation: Technologies, institutions and organizations. London: Pinter/Cassell.Google Scholar
  23. Esposito Vinzi, V., Chin, W. W., Henseler, J., & Wang, H. (Eds.). (2010). Handbook of partial least squares: Concepts, methods and applications (Springer Handbooks of Computational Statistics Series, Vol. II). Heidelberg: Springer.Google Scholar
  24. Etzkowitz, H., & Kloftsen, M. (2005). The innovating region: Towards a theory of Knowledge Based Regional Development. R&D Management, 35(3), 243–255.CrossRefGoogle Scholar
  25. Felsenstein, D. (1994). University-related science parks—‘Seedbeds’ or ‘enclaves’ of innovation? Technovation, 14, 93–110.CrossRefGoogle Scholar
  26. Ferguson, R., & Olofsson, C. (2004). Science parks and the development of NTBFs—Location, survival and growth. The Journal of Technology Transfer, 29, 5–17.CrossRefGoogle Scholar
  27. Flanagan, K., Uyarra, E., & Laranja, M. (2011). Reconceptualising the ‘policy mix’ for innovation. Research Policy, 40, 702–713.CrossRefGoogle Scholar
  28. Fritsch, M. (2002). Measuring the quality of regional innovation systems—A knowledge production function approach. International Regional Science Review, 25, 86–101.CrossRefGoogle Scholar
  29. Fritsch, M., & Graf, H. (2011). How subnational conditions affect regional innovation systems: The case of the two Germanys. Papers in Regional Science, 90(2), 331–353.CrossRefGoogle Scholar
  30. Fritsch, M., & Slavtchev, V. (2011). Determinants of the efficiency of regional innovation systems. Regional Studies, 45, 905–918.CrossRefGoogle Scholar
  31. Griliches, Z. (1979). Issues in assessing the contribution of research and development to productivity growth. The Bell Journal of Economics, 10, 92–116.CrossRefGoogle Scholar
  32. Hair, J., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–151.CrossRefGoogle Scholar
  33. Hansson, F., Husted, K., & Vestergaard, J. (2005). Second generation science parks: From structural holes jockeys to social capital catalysts of the knowledge societies. Technovation, 25, 1039–1049.CrossRefGoogle Scholar
  34. Heblich, S., & Slatchev, V. (2014). Parent Universities and the location of Academic Startups. Small Business Economics, 42(1), 1–15.CrossRefGoogle Scholar
  35. Hollanders, H., Tarantola, S., & Loschky, A. (2009). “Regional innovation scoreboard 2009” European Commission. https://ec.europa.eu/jrc/en/news/2009-regional-innovation-scoreboard-diversity-across-europe-7212.
  36. Hwang, H., Malhotra, N. K., Kim, Y., Tomiuk, M. A., & Hong, S. (2010). A comparative study of parameter recovery of three approaches to structural equation modeling. Journal of Marketing Research, 47, 699–712.CrossRefGoogle Scholar
  37. Jaffe, A. B. (1989). Real effects of academic research. American Economic Review, 79, 957–970.Google Scholar
  38. Kaihua, C., & Mingting, K. (2014). Staged efficiency and its determinants of regional innovation systems: A two-step analytical procedure. The Annals of Regional Science, 52(2), 627–657.CrossRefGoogle Scholar
  39. Laranja, M., Uyarra, E., & Flanagan, K. (2008). Policies for science, technology and innovation: Translating rationales into regional policies in a multi-level setting. Research Policy I, 37(5), 823–835.CrossRefGoogle Scholar
  40. Lindelof, P., & Lofsten, H. (2003). Science park location and new technology-based firms in Sweden: Implications for strategy and performance. Small Business Economics, 20, 245–258.CrossRefGoogle Scholar
  41. Link, Α. Ν., & Link, K. R. (2003). On the growth of U.S. science parks. Journal of Technology Transfer, 28, 81–85.CrossRefGoogle Scholar
  42. Massey, D. B., Quintas, P., & Wield, D. (1992). High-tech fantasies: Science parks in society, science and space. London: Routledge.Google Scholar
  43. Nauwelaers, C., & Reid, A. (1995). Methodologies for the evaluation of regional innovation potential. Scientometrics Journal, 34, 497–511.CrossRefGoogle Scholar
  44. OECD. (2012). Science, technology and industry outlook 2012. Retrieved from http://www.oecd.org/greece/sti-outlook-2012-greece.pdf.
  45. Phan, P. H., Siegel, D. S., & Wright, M. (2005). Science parks and incubators: Observations, synthesis and future research. Journal of Business Venturing, 20, 165–182.CrossRefGoogle Scholar
  46. Quatraro, F. (2009). The diffusion of regional innovation capabilities: Evidence from Italian patent data. Regional Studies, 43, 1333–1348.CrossRefGoogle Scholar
  47. Ringle, C. M., Sarstedt, M., & Schlittgen, R. (2014). Genetic algorithm segmentation in partial least squares structural equation modeling. OR Spectrum, 36, 251–276.CrossRefGoogle Scholar
  48. Rosenberg, N. (1982). Inside the black box: Technology and economics. Cambridge University Press.Google Scholar
  49. Runiewicz-Wardyn, M. (2013). The efficiency of regional innovation systems (RIS). The role of high-tech industry and knowledge-intensive services. Contributions to economics: Knowledge flows, technological change and regional growth in the European Union (pp. 81–102).Google Scholar
  50. Santarelli, E., Carree, M., & Verheul, I. (2009). Unemployment and firm entry and exit: An update on a controversial relationship. Regional Studies, 43, 1061–1073.CrossRefGoogle Scholar
  51. Soete, L., Verspagen, B., & ter Weel, B. (2009). Systems of innovation. Working Paper no 2009-062. Maastricht: UNU-MERIT.Google Scholar
  52. Sofoulli, E., & Vonortas, N. (2007). S&T parks and business incubator in middle-sized countries: The case of Greece. The Journal of Technology Transfer, 32, 525–544.CrossRefGoogle Scholar
  53. Squicciarini, M. (2008). Science Parks’ tenants versus out-of-Park firms: Who innovates more? A duration model. The Journal of Technology Transfer, 33, 45–71.CrossRefGoogle Scholar
  54. Taymaz, E., & Ucdogruk, Y. (2013). The demand for researchers: Does public R&D support make a difference? Eurasian Business Review, 3(1), 90–99.Google Scholar
  55. Tewdwr-Jones, M., & McNeill, D. (2000). The politics of city-region planning and governance—Reconciling the national, regional and urban in the competitive voices of restructuring. European Urban and Regional Studies, 7(2), 119–134.CrossRefGoogle Scholar
  56. Uyarra, E. (2008). The impact of universities on regional innovation: A critique and policy implications. Manchester Business School working paper No. 564, Retrieved from http://hdl.handle.net/10419/50728.
  57. Uzzi, B. (1996). The sources and consequences of embeddedness for the economic performance of organizations: The network effect. American Sociological Review, 61, 674–698.CrossRefGoogle Scholar
  58. Vivarelli, M. (2013). Is entrepreneurship necessarily good? Microeconomic evidence from developed and developing countries. Industrial and Corporate Change, 22(6), 1453–1495.CrossRefGoogle Scholar
  59. Wallsten, S. (2001). The role of government in regional technology development: The effects of public venture capital and science parks. SIEPR Discussion Paper 00-039. Retrieved from http://www.stanford.edu/group/siepr/cgi-bin/siepr/?q=system/files/shared/pubs/papers/pdf/00-39.pdf.
  60. Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus. London: Wiley Series in Probability and Statistics.CrossRefGoogle Scholar
  61. Westhead, P. (1997). R&D inputs and outputs of technology-based firms located on and off Science Parks. R&D Management, 27, 45–62.CrossRefGoogle Scholar
  62. Wong, K. K. (2013). Partial least squares structural equation modelling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24, 1–32.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Areti Gkypali
    • 1
  • Vasileios Kokkinos
    • 2
    • 3
  • Christos Bouras
    • 2
    • 3
  • Kostas Tsekouras
    • 1
    Email author
  1. 1.Department of EconomicsUniversity of PatrasPatrasGreece
  2. 2.Department of Computer Engineering and InformaticsUniversity of PatrasPatrasGreece
  3. 3.Computer Technology Institute and Press “Diophantus”PatrasGreece

Personalised recommendations