Supporting Knowledge and Policy-Based Stakeholders in Delivering Regional Impact: A Tool to Select Regional Scoreboard Indicators
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Purpose: The aim of the research is to explore how regional stakeholders can improve local and regional innovation policies and the transfer of best practices by devising a technique that ranks the EU Innovation Scoreboard indicators and instructs which indicator, if improved, could have the greatest impact for the region. In the current research the themes selected are Technology Licensing (TL), Spin-Off Creation and Entrepreneurship (SCE) and University-Industry Relations (UIR).
Design/Methodology: The study adopts an empirical methodology, applying statistic and econometric techniques. Each of the five regions in the study had to define their current status (Scenario 0) and the desired improvement they would like to achieve (Future Scenario). The Scenario 0 was based on the level and growth rate of a set of innovation indicators from the EU Innovation Scoreboard that are likely to be influenced by TL, SCE and UIR. The future scenario was defined by considering the effect of the innovation indicators on the Total Factor Productivity (TFP).
Findings: The results from the TFP indicate, for each of the five regions in the study, which EU Innovation indicators should be focused on. For example, in the Southern and Easter region of Ireland the top-ranked indicators are (1) Non-R&D innovation expenditures as % of turnover (U-I Relations Indicator), (2) small- and medium-sized enterprises (SMEs) introducing marketing or organisational innovations as % of SMEs (U-I Relations Indicator), (3) SMEs innovating in-house as % of SMEs (U-I Relations Indicator). Furthermore, the Southern and Eastern regions of Ireland should then concentrate their efforts on the development of practices and policies that could influence this indicator.
Practical Implications: This study provides guidance and instruction for regions and regional stakeholders on what innovation indicators they should focus on for the development of policies and knowledge transfer practices that can impact performance levels of the EU Innovation Scoreboard Indicators identified as potentially having the greatest impact.
Policy Implications: Regional stakeholders can utilise the approach adopted in this study to understand what innovation indicators from the Innovation Scoreboard they should select in order to deliver the greatest impact for the efforts (within a given theme). This tool can be supportive in the development of regional-based smart specialisations and regional development policy.
Originality/Value: Developing a technique that channels and instructs regional stakeholders where their innovation focus should be in terms of implementing practices and policies that drive innovation and competitive performance.
KeywordsRegional development Knowledge transfer Innovation scoreboard Knowledge economy Total factor productivity Practices and policies Technology licensing Spin-off creation and entrepreneurship University–industry relations
- Arancegui M., Querejeta M., Montero, E. (2011). Smart specialisation strategies: The case of the Basque Country, Orkestra working paper series in territorial competitiveness, 2011-R07.Google Scholar
- Arnkil, R., Järvensivu, A., Koski, P., & Piirainen, T. (2010). Exploring quadruple helix. Outlining user-oriented innovation models. Working Paper 85/2010, University of Tampere, Institute for Social Research.Google Scholar
- Asheim, B. E., & Gertler, M. (2005). The geography of innovation: Regional innovation systems. In J. Fagerberg, D. Mowery, & R. R. Nelson (Eds.), The Oxford Handbook of Innovation. London: Oxford University Press.Google Scholar
- Barca, F. (2009). An agenda for the reformed cohesion policy. Brussels: Report to the Commissioner for Regional Policy.Google Scholar
- Becattini, G. (1989). Sectors and/or districts: Some remarks on the conceptual foundations of industrial economics. In E. Goodman, J. Bamford & P. Saynor. Small firms and industrial districts in Italy (pp. 123–135)London, Routledge.Google Scholar
- Camagni R., & Capello R. (2012). “Regional innovation patterns and the EU regional policy reform: Towards smart innovation policies”, proceeds of the 52nd ERSA Conference in Bratislava.Google Scholar
- Carayannis, E.G., & Campbell, D.F.J. (2012). Mode 3 knowledge production in quadruple helix innovation systems. 21st-century democracy, innovation, and entrepreneurship for development. Springer Briefs in business, vol. 7. Springer: New York.Google Scholar
- CEC – Commission of the European Communities. (2010). Europe 2020. A strategy for smart, suitable and inclusive growth. Communication from the Commission, COM (2010) 2020.Google Scholar
- Cooke, P. (2002). Knowledge Economies: Clusters, learning & Co-operative advantage Studies. In International Business & the World Economy. London, Routledge.Google Scholar
- David P., Foray D., & Hall B. 2012. Measuring smart specialization. The concept and the need for indicators, in http://cemi.epfl.ch/files/content/sites/cemi/files/users/178044/public/ Measuring%20smart%20specialisation.doc.
- European Commission. (2010). Europe 2020: A strategy for smart, suitable and inclusive growth. COM (2010) 2020 final.Google Scholar
- Foray D., David P.A., Hall, B. (2009). Smart specialisation. The Concept, Knowledge Economists Policy Brief No.9. [online] Available from http://ec.europa.eu/invest-in-research/pdf/download_en/selected_papers_en.pdf. Accessed Dec 2011.
- Foray D., Van Ark, B. (2007). “Smart specialisation in a truly integrated research area is the key to attracting more R&D to Europe”, European Commission Expert Group “Knowledge for Growth”, Policy Brief No 1, http://ec.europa.eu/invest-inresearch/pdf/download_en/policy_brief1.pdf
- Freeman, C. (1987). Technology and economic performance: Lessons from Japan. London: Pinter.Google Scholar
- Freeman, C. (1995). The National ‘National System of Innovation’ in historical perspective. Cambridge Journal of Economics, 5–24.Google Scholar
- Giannitsis, T. (2009). Technology and specialization: Strategies, options, risks. Knowledge Economists Policy Brief, n. 8.Google Scholar
- Krugman, P. (1995). Development Geography and Economic Theory. US: MIT Press.Google Scholar
- Kyriakou, D. (2009). Introduction. In D. Pontikakis, D. Kyriakou, & R. van Bavel (Eds.), The Question of R&D specialisation. Perspectives and policy implications (pp. 11–17). Luxembourg: Office for Official Publications of the European Communities.Google Scholar
- Lagendijk, A. (2011). Regional innovation theory between theory and practice. In B. Asheim, r. Boschmar, & P. Cooke (Eds.), Handbook of regional innovation and growth (pp. 597–608). Cheltenham: Edward Elgar.Google Scholar
- Lundvall, B. A. (1992). National innovation systems: towards a theory of innovation and interactive learning. London: Pinter.Google Scholar
- Lundvall B-Å. (2004). Why the new economy is a learning economy. DRUID Working Paper No. 02–01.Google Scholar
- Marshall, S. (1890). Principles of economics (8th ed.). London: MacMillan.Google Scholar
- McCann P., & Ortega-Argilés R. (2011). Smart specialisation, regional growth and applications to EU cohesion policy, Economic Geography Working Paper 2011: Faculty of Spatial Sciences. University of Groningen.Google Scholar
- McCann, P., & Ortega-Argilés, R. (2013). Modern innovation policy. Cambridge Journal of Regions, Economy & Society, 6(1), 1–30.Google Scholar
- Nelson R., & Rosenberg N. (1993). National innovation systems (Ch. 1 – Technical innovation and national systems). Oxford: Oxford University Press.Google Scholar
- O’Gorman B., & Donnelly W. (2016). Ecosystems of open innovation: Their applicability to the growth and development of economies within small countries and regions. In U. Hilpert (Ed), Handbook on Politics and Technology. routledge, UK.Google Scholar
- Pontikakis, D., Chorafakis, G., & Kyriakou, D. (2009). R&D specialization in Europe: from stylized observations to evidence-based policy. In D. Pontikakis, D. Kyriakou, & R. van Bavel (Eds.), The question of R&D specialisation, JRC, European Commission (pp. 71–84). Brussels: Directoral General for Research.Google Scholar
- Porter, M. (1998). Clusters and the new economics of competition (pp. 77–90). Boston: Harvard Business Review.Google Scholar
- Sandu S. (2012). Smart specialization concept and the status of its implementation in Romania. Procedia Economics and Finance, 3, 236–242.Google Scholar
- Saviotti, P. P. (1997). Innovation systems and evolutionary theories. In C. Edquist (Ed.), Systems of innovation – technologies. Institutions and Organizations, London: Pinter.Google Scholar