Abstract
This study investigates the impact of a wide spectrum of Knowledge and Technology Transfer (KTT) activities (educational and research activities, activities related with technical infrastructure, and consulting) on two innovation indicators (a) in the framework of an innovation equation with variables for specific forms of KTT activities as additional determinants of innovation, and (b) based on a matched-pairs analysis for several specific forms of KTT activities. The data used in the study were collected by means of a survey of Swiss enterprises that took place at the beginning of 2005. We found that research and educational activities improve the innovation performance of firms in terms of sales of considerably modified products, research activities in addition also in terms of sales of new products. This could be shown by several methods: the innovation equation approach with instrument variables for specific forms of KTT activities as well as two matching methods.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Economics: see e.g. volume 34, issue 3 of Research Policy of April 2005 (edited by A.N. Link and D.S. Siegel) dedicated to “University-based Technology Initiatives”; “Academic Science and Entrepreneurship” (edited by A. Jaffe, J. Lerner, S. Stern and M. Thursby), forthcoming in the Journal of Economic Behaviour and Organization; volume 28, issue 3–4 of the Journal of Technology Transfer of August 2003 devoted to the “Symposium on the State of the Science and Practice of Technology Transfer”. Policy: see e.g. OECD (2003), OECD (2002) and OECD (1999).
Versions of the questionnaire in German, French and Italian are available in http://www.kof.ethz.ch.
Estimates based on an alternative specification of firm size with a linear and a quadratic term with respect to the number of employees showed a relationship of an inverse U-shape. This is in accordance with earlier findings; see e.g. Arvanitis (1997).
The expression “treatment effect” comes from the labour market research, where individuals are “treated” via a concrete policy measure. It is used here analogously for firms involved in KTT activities, even if this is not the result of any policy measure.
Firms with a focus in educational activities without the additional restriction “taking the value 0 for the variable REAS” (as in variable EDUC in Sect 5) could not be matched because the number of available control firms in this case is considerably lower than the number of treated firms.
References
Adams, J. D., Chiang, E. P., & Jensen, J. L. (2003). The Influence of Federal Laboratory R&D on Industrial Research. Review of Economics and Statistics, 85(4), 1003–1020.
Arvanitis, S. (1997). The impact of firm size on innovative activity. An empirical analysis based on Swiss firm data. Small Business Economics, 9(6), 473–490.
Arvanitis, S., & Hollenstein, H. (1996). Industrial innovation in Switzerland: A model-based analysis with survey data. In A. Kleinknecht (Ed.), Determinants of innovation. The message from new indicators. London: Macmillan.
Arvanitis, S., Kubli, U., & Woerter, M. (2005). Determinants of knowledge and technology transfer activities between firms and universities in Switzerland: An analysis based on firm data’, KOF working paper no. 115, Zurich (http://www.kof.ethz.ch/pdf/wp_117.pdf).
Barney, J., Wright, M., Ketchen, D. J. (2001). The resource-based view of the firm: Ten years after 1991. Journal of Management 27, 625–641.
Becker, W. (2003). Evaluation of the role of universities in the innovation process, Volkswirtschaftliche Diskussionsreihe Beitrag Nr. 241, Institut für Volkswirtschaftslehre Universität Augsburg, Augsburg.
Beise, M., & Stahl, H. (1999). Public research and industrial innovations in Germany. Research Policy 28, 397–422.
Bönte, W. (2004). Spillovers from publicly financed business R&D: Some empirical evidence from Germany. Research Policy, 33, 1635–1655.
Bozeman, B. (2000). Technology transfer and public policy: A review of research and theory. Research Policy, 29, 627–655.
Fritsch, M., & Franke, G. (2004). Innovation, regional knowledge spillovers and R&D co-operation. Research Policy, 33, 245–255.
Georghiou, L., & Roessner, D. (2000). Evaluating technology programmes: Tools and methods. Research Policy, 29, 657–678.
Guellec, D., & van Pottelsberghe de la Potterie B. (2003). The impact of public R&D expenditure on business R&D. Economics of Innovation and New Technology, 12(3), 225–243.
Hall, B., & van Reenen, J. (2000). How effective are fiscal incentives for R&D? A review of the evidence. Research Policy, 29, 449–469.
Hall, B. H., Link, A. N., & Scott, J. T. (2003). Universities as research partners. Review of Economics and Statistics, 85(2), 485–491.
Heckman, J., Ichimura, H., Smith, J., & Todd, P. (1998). Characterizing selection bias using experimental data. Econometrica, 66(5), 1017–1098.
Kaufmann, A., & Tödtling, F. (2001). Science-industry interaction in the process of innovation: The importance of boundary-crossing between systems. Research Policy, 30, 791–804.
Klette, T. J., Moen, J., & Griliches, Z. (2000). Do subsidies to commercial R&D reduce market failures? Microeconometric evaluation studies. Research Policy, 29, 471–495.
Klevorick, A. K., Levin, R. C., Nelson, R. R., & Winter, S. G. (1995). On the sources and significance of interindustry differences in technological opportunities. Research Policy, 24, 185–205.
Lööf, H., & Broström, A. A. (2005) Does knowledge diffusion between university and industry increase innovativeness? Working paper presented at the world bank workshop in Cambridge, September.
Mansfield, E. (1991). Academic research and industrial innovation. Research Policy, 20, 1–12.
Mansfield, E. (1998). Academic research and industrial innovation: An update of empirical findings. Research Policy, 26, 773–776.
Monjon, S., & Waelbroeck, P. (2003) Assessing spillovers from universities to firms: Evidence from French firm-level data. International Journal of Industrial Organization, 21, 1255–1270.
Nelson, R. R. (1986) Institutions supporting technical advance in industry. American Economic Review, Papers & Proceedings, 76(2), 186–189.
OECD (1999). Special isssue on public/private partnerships in STI review no. 23.
OECD (2002). Benchmarking industry-science relationships. Paris: OECD.
OECD (2003). Turning science into business, patenting and licensing at public research organizations. Paris: OECD.
Rosenbaum, B. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.
Zinkl, W., & Huber, H. (2003). Strategie für den Wissens- und Technologietransfer an den Hochschulen in der Schweiz. Basel: Mandat im Auftrag der Schweizerischen Universitätskonferenz SUK, Hauptbericht: Strategie und Politik im WTT.
Acknowledgements
This study was financially supported by the ETH-Board. Useful comments and suggestions of the participants of the Annual Conference of the Swiss Association for Economics and Statistics, Lugano, Switzerland, March 9–10 2006 are gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Arvanitis, S., Sydow, N. & Woerter, M. Do specific forms of university-industry knowledge transfer have different impacts on the performance of private enterprises? An empirical analysis based on Swiss firm data. J Technol Transfer 33, 504–533 (2008). https://doi.org/10.1007/s10961-007-9061-z
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10961-007-9061-z