Skip to main content

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

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, access via your institution.

Notes

  1. 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).

  2. See e.g. Bozeman 2000; Georghiou and Roessner (2000) for recent reviews of the central issues related to this question; for reviews of the related econometric issues see e.g. Klette et al. (2000); Hall and Van Reenen (2000).

  3. For recent studies on the impact of public R&D expenditure on business R&D at country or sector level see e.g. Guellec and van Pottelsberghe de la Potterie (2003) (17 OECD countries); Bönte (2004) (West German manufacturing industries).

  4. Versions of the questionnaire in German, French and Italian are available in http://www.kof.ethz.ch.

  5. 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).

  6. 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.

  7. 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Bönte, W. (2004). Spillovers from publicly financed business R&D: Some empirical evidence from Germany. Research Policy, 33, 1635–1655.

    Article  Google Scholar 

  • Bozeman, B. (2000). Technology transfer and public policy: A review of research and theory. Research Policy, 29, 627–655.

    Article  Google Scholar 

  • Fritsch, M., & Franke, G. (2004). Innovation, regional knowledge spillovers and R&D co-operation. Research Policy, 33, 245–255.

    Article  Google Scholar 

  • Georghiou, L., & Roessner, D. (2000). Evaluating technology programmes: Tools and methods. Research Policy, 29, 657–678.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Hall, B., & van Reenen, J. (2000). How effective are fiscal incentives for R&D? A review of the evidence. Research Policy, 29, 449–469.

    Article  Google Scholar 

  • Hall, B. H., Link, A. N., & Scott, J. T. (2003). Universities as research partners. Review of Economics and Statistics, 85(2), 485–491.

    Article  Google Scholar 

  • Heckman, J., Ichimura, H., Smith, J., & Todd, P. (1998). Characterizing selection bias using experimental data. Econometrica, 66(5), 1017–1098.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Mansfield, E. (1998). Academic research and industrial innovation: An update of empirical findings. Research Policy, 26, 773–776.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Nelson, R. R. (1986) Institutions supporting technical advance in industry. American Economic Review, Papers & Proceedings, 76(2), 186–189.

    Google Scholar 

  • OECD (1999). Special isssue on public/private partnerships in STI review no. 23.

  • OECD (2002). Benchmarking industry-science relationships. Paris: OECD.

    Google Scholar 

  • OECD (2003). Turning science into business, patenting and licensing at public research organizations. Paris: OECD.

    Google Scholar 

  • Rosenbaum, B. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.

    Article  Google Scholar 

  • 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.

    Google Scholar 

Download references

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

Authors

Corresponding author

Correspondence to Spyros Arvanitis.

Appendix

Appendix

Table A.1 Composition of the dataset of KTT-active firms by industry, firm size
Table A.2 Probit estimates of the instrument equations for EDUC, REAS, CONS and INFR respectively
Table A.3 Propensity to research activities (REAS yes/no); educational activities (EDUC1 yes/no); consulting activities (CONS yes/no); activities related to technical infrastructure (INFR Yes/No)
Table A.4 Descriptive statistics of the variables of the innovation equations
Table A.5 Correlation matrix of the variables of the innovation equations

Rights and permissions

Reprints 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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10961-007-9061-z

Keywords

  • Knowledge and technology transfer
  • Innovation activities
  • R&D activities

JEL Classification

  • O30