Abstract
Academic startups are thought to locate in their parent university’s home region because being in the vicinity of a university provides cost advantages in accessing academic knowledge and resources. In this paper we analyze the importance of a different mechanism, namely, social ties between academic entrepreneurs and university researchers, for enabling and facilitating the access to academic knowledge and resources, and therefore for the location of academic startups. We employ unique data on academic startups from regions with more than one university and find that only the parent university influences academic entrepreneurs’ decisions to stay in the region while other universities in the same region play no role. Our findings suggest that the mere local availability of a university may not per se guarantee access to knowledge and resources; social ties are additionally required. The importance of social ties implies that academic knowledge and resources are not necessarily local public good. This holds implications for universities’ role in stimulating regional development.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The university regular funds consist of salaries and funds for infrastructure (e.g., equipment, buildings, etc.).
The data on universities’ funds from private industry do not contain information about the location of the donating companies. However, previous research indicates that university–industry linkages are predominantly local (Fritsch and Schwirten 1999; Slavtchev 2010) and that the R&D spending of private firms for universities decrease very sharply with the distance (Mansfield and Lee 1996).
Obtaining data on academic startups is not an easy task. In Germany, there are no official data on academic startups. For instance, the Employment History Panel of the Institute for Labor Research contains information on the employment history of all employees subject to social insurance. Unfortunately, it does not contain information about individuals that have never been employed (e.g., university students and graduates), nor employees not subject to social insurance as well as public servants (e.g., professors). Moreover, a step towards entrepreneurship is hardly identifiable if the firm owner is not subject to social insurance. Identifying and surveying academic entrepreneurs is hardly possible too, in particular if they start their business after having left the alma mater.
Universities in Berlin and the Federal State of Brandenburg that surrounds Berlin and is in commuting distance have been not considered because the capital Berlin is a very specific case and thereby likely to be a particularly attractive location.
In this period, only very few professors left the university, solely due to retirement or to take a position at another university.
Prior to the survey, personal interviews with a random sample of professors were conducted to validate the questionnaire.
There is no evidence for potential biases due to selection. There are no significant differences in the response rates between universities, departments, and regions. Moreover, there are no significant differences in the observable characteristics of professors that responded to the survey and such that did not. Finally, the personal interviews with the professors did not suggest that there could be a bias towards more local startups because professors might be more likely to recall them.
Contrary to smaller regions (e.g., NUTS3) that may include a single city, the German planning regions represent spatial economic entities (cf. Federal Office for Building and Regional Planning 2003). In particular, the planning regions comprise a core city and its surrounding, and account, therefore, for commuter distances and other daily economic transactions.
Information on university professors is obtained from the Federal Statistical Office.
Other indicators like publications and research grants have been often used to measure the intensity of academic R&D. However, they are less suitable to proxy for the amount of not codified, tacit knowledge embodied in individuals (Hornbostel 2001).
We assume that the industry of the most common private collaboration partner of the research group in which the entrepreneur was previously employed and/or supervised is technologically related, because collaboration requires technological proximity. Using input–output tables does not seem appropriate since they are less precise (i.e., available only at the two-digit level of the industrial classification) and because they include market transactions that are not necessarily related to knowledge flows. Using aggregations of industries within the same upper-level class of the standard industrial classification is also likely imprecise because industries in the same upper-level class are not necessarily related while there might be technologically-related industries that belong to different upper-level classes. Finally, identifying technological relatedness through patent data (IPC classes or citations) does not seem appropriate either, because academic startups typically have no or very few patents in the very early phase.
Information on both R&D and non-R&D employment is taken from the German Social Insurance Statistics at the Institute for Employment Research.
Woodward et al. (2006) also found a rather small effect of localization economies.
Correlation between variables are reported in Table 5 in the Appendix.
Information on both university professors and graduates is obtained from the Federal Statistical Office.
Since the estimated coefficients for the ‚placebo’ variables are always statistically not significant, we do not report the results of this robustness check. However, all results are available on request.
References
Astebro, T., & Bazzazian, N. (2011). Universities, entrepreneurship and local economic development. In M. Fritsch (Ed.), Handbook of research on entrepreneurship and regional development. Cheltenham: Edward Elgar.
Audretsch, D. B., & Feldman, M. P. (1996). Innovative clusters and the industry life cycle. Review of Industrial Organization, 11, 253–273.
Audretsch, D. B., & Stephan, P. E. (1996). Company-scientist locational links: The case of biotechnology. American Economic Review, 86, 641–652.
Autant-Bernard, C., Billand, P., Frachisse, D., & Massard, N. (2007). Social distance versus spatial distance in R&D cooperation: empirical evidence from European collaboration choices in micro and nanotechnologies. Papers in Regional Science, 86, 495–519.
Baltzopoulos, A., & Broström, A. (2011). Attractors of talent: Universities, regions, and alumni entrepreneurs. Regional Studies. doi:10.1080/00343404.2011.602335.
Bauernschuster, S., Falck, O., & Heblich, S. (2010). Social capital access and entrepreneurship. Journal of Economic Behavior & Organization, 76, 821–833.
Belderbos, R., Carree, M., & Lokshin, B. (2004). Cooperative R&D and firm performance. Research Policy, 33, 1477–1492.
Berggren, A., & Lindholm Dahlstrand, A. (2009). Creating an entrepreneurial region: Two waves of academic spin-offs from Halmstad University. European Planning Studies, 17, 1171–1189.
Boschma, R. (2005). Proximity and innovation: A critical assessment. Regional Studies, 39, 61–74.
Braunerhjelm, P. (2008). Specialization of regions and universities: The new versus the old. Industry and Innovation, 15, 253–275.
Buenstorf, G., & Klepper, S. (2009). Heritage and agglomeration: The Akron tyre cluster revisited. Economic Journal, 119, 705–733.
Carlton, D. W. (1979). Why new firms locate where they do: An economic model. In W. C. Wheaton (Ed.), Interregional movements and regional growth. Washington: Urban Institute.
Carlton, D. W. (1983). The location and employment choices of new firms: An econometric model with discrete and continuous endogenous variables. Review of Economics and Statistics, 65, 440–449.
Coleman, J. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, 95–120.
Colombo, M. G., & Delmastro, M. (2002). How effective are technology incubators?: Evidence from Italy. Research Policy, 31, 1103–1122.
Dahl, M. S., & Sorenson, O. (2009). The embedded entrepreneur. European Management Review, 6, 172–181.
Di Gregorio, D., & Shane, S. (2003). Why do some universities generate more start-ups than others? Research Policy, 32, 209–227.
Dorfman, N. S. (1983). Route 128: The development of a regional high technology economy. Research Policy, 12, 299–316.
Egeln, J., Gottschalk, S., & Rammer, C. (2004). Location decisions of spin-offs from public research institutions. Industry & Innovation, 11, 207–223.
European Commission. (2006a). Community strategic guidelines for rural development (programming period 2007 to 2013). Official Journal of the European Union, 2006/144/EC, 20–29.
European Commission. (2006b). Entrepreneurship education in Europe: Fostering entrepreneurial mindsets through education and learning. Final Proceedings of the “Conference on Entrepreneurship Education” in Oslo, October 26–27.
Federal Office for Building and Regional Planning. (2003). Aktuelle Daten zur Entwicklung der Staedte, Kreise und Gemeinden. Band 17, Bonn.
Feldman, M. P. (2000). Where science comes to life: University biosciences, commercial spin-offs and regional economic development. Journal of Comparative Policy Analysis, Research and Practice, 2, 345–361.
Feldman, M., & Desrochers, P. (2001). Research universities and local economic development: Lessons from the history of the Johns Hopkins University. Industry and Innovation, 10, 5–25.
Feldman, M. P., & Francis, J. (2003). Fortune favours the prepared region: The case of entrepreneurship and the Capitol region biotechnology cluster. European Planning Studies, 11, 765–788.
Feldman, M. P., & Francis, J. (2004). Homegrown solutions: Fostering cluster formation. Economic Development Quarterly, 18, 127–137.
Feldman, M. P., Francis, J., & Bercovitz, J. (2005). Creating a cluster while building a firm: Entrepreneurs and the formation of industrial clusters. Regional Studies, 39, 129–141.
Figueiredo, O., Guimaraes, P., & Woodward, D. (2002). Home-field advantage: Location decisions of Portuguese entrepreneurs. Journal of Urban Economics, 52, 341–361.
Fritsch, M., & Schwirten, C. (1999). Enterprise–university co-operation and the role of public research institutions in regional innovation systems. Industry and Innovation, 6, 69–83.
Glaeser, E. L., Kerr, W. R., & Ponzetto, G. A. M. (2010). Clusters of entrepreneurship. Journal of Urban Economics, 67, 150–168.
Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91, 481–510.
Gulati, R. (1995). Does familiarity breed trust? The implications of repeated ties for contractual choice in alliances. Academy of Management Journal, 38, 85–112.
Hornbostel, S. (2001). Third party funding of German universities. An indicator of research activity. Scientometrics, 50, 523–537.
Kenney, M., Nelson, A., & Patton, D. (2009). The university-centric high-tech cluster of Madison, United States. In J. Potter & G. Miranda (Eds.), Clusters, innovation and entrepreneurship (pp. 167–192). Paris: OECD.
Klepper, S. (1996). Entry, exit, growth, and innovation over the product life cycle. American Economic Review, 86, 562–583.
Lerner, J. (1995). Venture capitalists and the oversight of private firms. The Journal of Finance, 50, 301–318.
Lindelöf, P., & Löfsten, H. (2003). Science park location and new technology-based firms in Sweden—Implications for strategy and performance. Small Business Economics, 20, 245–258.
Lindholm Dahlstarand, A. (1997). Entrepreneurial spin-off enterprises in Goeteborg, Sweden. European Planning Studies, 5, 659–673.
Lindholm Dahlstarnd, A. (1999). Technology-based SMEs in the Goeteborg Region: Their origin and interaction with universities and large firms. Regional Studies, 33, 379–389.
Löfsten, H., & Lindelöf, P. (2002). Science parks and the growth of new technology-based firms—academic-industry links, innovation and markets. Research Policy, 31, 859–876.
Lööf, H., & Broström, A. (2008). Does knowledge diffusion between university and industry increase innovativeness? Journal of Technology Transfer, 33, 73–90.
Lundvall, B. A. (1993). Explaining interfirm cooperation and innovation. Limits of the transaction-cost approach. In G. Gragner (Ed.), The embedded firm on the socioeconomics of industrial networks. London: Routledge.
Mansfield, E., & Lee, J.-Y. (1996). The modern university: Contributor to industrial innovation and recipient of industrial R&D support. Research Policy, 25, 1047–1058.
Maskell, P., & Malmberg, A. (1999). The competitiveness of firms and regions. ‘Ubiquitification’ and the importance of localized learning. European Urban and Regional Studies, 6, 9–25.
Michelacci, C., & Silva, O. (2007). Why so many local entrepreneurs? Review of Economics and Statistics, 89, 615–633.
OECD. (2006). The new rural paradigm, policy and governance. Working paper on territorial policy in rural areas. OECD, Paris.
O’Shea, R. P., Allen, T. J., Chevalier, A., & Roche, F. (2005). Entrepreneurial orientation, technology transfer and spinoff performance of U.S. universities. Research Policy, 34, 994–1009.
Powell, W. W., Koput, K. W., Bowie, J. I., & Smith-Doerrs, L. (2002). The spatial clustering of science and capital: Accounting for biotech firm–venture capital relationships. Regional Studies, 36, 291–305.
Roberts, E. (1991). Entrepreneurs in high technology: Lessons from MIT and beyond. New York: Oxford University Press.
Roberts, E., & Eesley, C. (2011). Entrepreneurial impact: The role of MIT. Foundations and Trends in Entrepreneurship, 7, 1–149.
Segal, N. S. (1986). Universities and technological entrepreneurship in Britain: Some implications of the Cambridge phenomenon. Technovation, 4, 189–204.
Shane, S. (2004). Academic entrepreneurship: University Spinoffs and wealth creation. Cheltenham: Edward Elgar.
Slavtchev, V. (2010). Proximity and the transfer of academic knowledge: Evidence from the spatial pattern of industry collaborations of East German professors. Regional Studies. doi:10.1080/00343404.2010.487058.
Sorensen, O., & Stuart, T. E. (2001). Syndication networks and the spatial distribution of venture capital investments. American Journal of Sociology, 106, 1546–1588.
Wicksteed, S. Q. (1985). The Cambridge phenomenon: The growth of high technology industry in a university town. Cambridge: Swavesey.
Woodward, D., Figueiredo, O., & Guimaraes, P. (2006). Beyond the Silicon Valley: University R&D and high-technology location. Journal of Urban Economics, 60, 15–32.
Wright, M., Clarisse, B., Mustar, P., & Lockett, A. (2007). Academic entrepreneurship in Europe. Cheltenham: Edward Elgar.
Zucker, L. G., Darby, M. R., & Brewer, M. B. (1998). Intellectual human capital and the birth of U.S. biotechnology enterprises. American Economic Review, 88, 290–306.
Acknowledgments
We thank Tom Astebro, Stefan Bauernschuster, Werner Bönte, Oliver Falck, Olav Sorenson and seminar participants at the Council for Regional Economics for insightful comments and suggestions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Heblich, S., Slavtchev, V. Parent universities and the location of academic startups. Small Bus Econ 42, 1–15 (2014). https://doi.org/10.1007/s11187-013-9470-3
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11187-013-9470-3