The interesting relationship between entrepreneurial activity and regional competitiveness has been a major focus of academics, university managers, and policy makers during the past decades—in particular the role of institutions in the establishment of political, social, and economic rules-. For example, since the enactment of the US Bayh–Dole Act more than 30 years ago, many American cities and regions are increasingly viewing universities as potential engines of economic growth. In these new socioeconomic scenarios, the role of entrepreneurial universities is not only generates/transfers knowledge but also contributes/provides leadership for the creation of entrepreneurial thinking, actions, and institutions. Previous studies have shown the university’s role in economic development, but no empirical study has analyzed the entrepreneurial activity generated by university students per university at the country/regional level of analysis. The purpose of this paper is to explore the impact of the university’s entrepreneurial activity on regional competitiveness. Adopting the institutional economics and the endogenous growth approaches, a proposed conceptual framework was developed and tested with structural equation modeling using data from 102 universities located in 56 NUTS II of 12 European countries. Our results evidenced that informal factors (e.g., attitudes, role models) have a higher influence on university entrepreneurial activity than formal factors (e.g., support measures, education and training). Our results also evidenced a higher contribution of universities on regional competitiveness, in particular, when we used social measures (talent human capital) instead economic measures (GDP per capita).
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GUESSS is an international research project using a geographical and temporal comparison to investigate the entrepreneurial intention and activity of students. For further information, see http://www.guesssurvey.org/.
Known as EUMIDA, this project aimed to build a complete census of European universities and included a pilot data collection with particular emphasis on those universities that are research-active. For further information, see http://datahub.io/es/dataset/eumida.
For further information, see http://epp.eurostat.ec.europa.eu/portal/page/portal/region_cities/regional_statistics/data/database.
Regarding to the NUTS regions, there are some universities linked to one NUT. On average, 1.8 universities are represented by each NUT. But it is also influenced by the NUT classification in each country because there are some countries where this classification is not so disaggregated. For this reason, to try to “control” the regional effect, we introduce high-income regions. Of course, a good way will be to create proxies by the 56 NUTS and introduce them in the model, but in our case it was not possible.
For further information, see http://www.timeshighereducation.co.uk/world-university-rankings/.
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The authors wish to acknowledge the anonymous reviewers for their comments and feedback that have helped shape this paper. Maribel Guerrero recognizes the support of Mexico’s National Council of Science and Technology (CONACYT). David Urbano acknowledges the financial support from the projects ECO2013-44027-P (Spanish Ministry of Economy & Competitiveness) and 2014/SGR/1626 (Economy & Knowledge Department -Catalan Government-).
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Guerrero, M., Urbano, D. & Fayolle, A. Entrepreneurial activity and regional competitiveness: evidence from European entrepreneurial universities. J Technol Transf 41, 105–131 (2016). https://doi.org/10.1007/s10961-014-9377-4
- Entrepreneurial activity
- Institutional economics
- Endogenous economic growth
- Regional competitiveness
- Entrepreneurial universities
- M13 (New Firms; Startups)
- L26 (Entrepreneurship)
- I23 (Higher Education Research Institutions)
- I28 (Education Government Policy)