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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

The Journal of Technology Transfer volume 33, pages 504–533 (2008)Cite this article

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.

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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.

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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.

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Authors and Affiliations

  1. KOF Swiss Economic Institute, ETH Zurich, Zurich, 8092, Switzerland

    Spyros Arvanitis, Nora Sydow & Martin Woerter

Authors
  1. Spyros Arvanitis
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  2. Nora Sydow
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  3. Martin Woerter
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Correspondence to Spyros Arvanitis.

Appendix

Appendix

Table A.1 Composition of the dataset of KTT-active firms by industry, firm size
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Table A.2 Probit estimates of the instrument equations for EDUC, REAS, CONS and INFR respectively
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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)
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Table A.4 Descriptive statistics of the variables of the innovation equations
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Table A.5 Correlation matrix of the variables of the innovation equations
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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

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Keywords

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

JEL Classification

  • O30