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Science Parks’ tenants versus out-of-Park firms: who innovates more? A duration model

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Abstract

We study the successfulness of Science Parks (SPs) as seedbeds of innovation. We investigate whether SPs enhance the innovative output of their tenants and if tenants outperform comparable outside-SPs firms. We rely on original matching datasets regarding in- and out-SP Finnish firms and their patenting activity over 1970–2002. We estimate and compare the ‘before-versus-after’ hazard rates of patenting of both samples. The results suggest that, given the existence of a common tendency to slow down the pace at which all firms patent during their life cycle, Park tenants exhibit a comparatively better performance. Results are robust to various model specifications and to Wald tests performed over the pooled samples.

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Notes

  1. See Sect. 2 for a review of the literature

  2. Innovation has also been one of the priorities of the Finnish Presidency of the Council of the European Union (II semester 2006, www.eu2006.fi).

  3. Among others: Heckman et al. (1997, 1998, 1998); Heckman and Smith (1999); Ichimura and Taber (2001); Heckman and Navarro-Lozano (2004) and Smith and Todd (2005).

  4. A regional perspective is also guiding Kang’s (2004) analysis of the Korean experience, which aims to establish development models for SPs depending upon the framework conditions under which the Parks are supposed to be built.

  5. According to the IASP official definition “A Science Park is an organization managed by specialized professionals, whose main aim is to increase the wealth of its community by promoting the culture of innovation and the competitiveness of its associated businesses and knowledge-based institutions. To enable these goals to be met, a Science Park stimulates and manages the flow of knowledge and technology amongst universities, R&D institutions, companies and markets; it facilitates the creation and growth of innovation-based companies through incubation and spin-off processes; and provides other value-added services together with high quality space and facilities.” (IASP International Board, 6 February 2002). The fact that the Parks considered in the study are either members of Tekel or IASP or both makes them easily distinguishable from business parks and similar initiatives, thus eliminating a possible source of heterogeneity.

  6. No information could be obtained about the remaining three Science Parks.

  7. Sheehan (2001) finds response rates to oscillate between 21.6% and 36% and Jobber and Saunders (1993) indicate that the rate of response in business-oriented studies is more sensitive than consumers’ ones to characteristics as the number of questions, the length of the survey, etc.

  8. The type of companies we refer to are Nokia, Sonera, Orion and the like.

  9. These samples look very tiny indeed but one should bear in mind that patenting in Finland is not a ‘massive’ phenomenon. The NBPR has in fact dealt with 2200–2900 patent files per year over the period the 1998–2002. Furthermore, the number of patents applications at the Finnish level has steadily decreased during the last decade, often in favour of EPO, PCT, etc. applications.

  10. The strength of Cox’s approach—where the hazard is of the form λ (t; x) = κ(x) λ 0 (t), κ (·) > 0 is a nonnegative function of x and λ 0 (t) > 0 is the baseline hazard—is that the effect of the covariates can be estimated very generally, without having to specify the baseline hazard.

  11. Otherwise, the estimated covariance matrix would not be appropriate for hypothesis testing. See Lin and Wei (1989), Struthers and Kalbfleish (1984), Hosmer and Lemeshow (1999), and Box-Steffensmeier and Zorn (2002) in this respect.

  12. About martingale and Schoenfeld residuals see Sasieni and Winnett (2003) and Borgan and Langholz (2005). About their use see Cleves et al. (2002).

  13. All the tables, in their full versions, are available from the author, upon request.

  14. Wald tests are chi-square statistics, pure significance tests against the null hypothesis that a parameter is zero, i.e., that the corresponding variable has no effect given that the other variables are in the model (Greene 2000)

  15. Table 1A, in Appendix, shows the result of the Wald tests obtained while holding the number of observations constant.

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Acknowledgements

I am particularly indebted to Pierre Regibeau, Steve Pudney, David Audretsch, Marco Francesconi, Gabriella Conti and Otto Toivanen. Thanks also go to Zoltan Acs, Mariana Mazzucato and the participants in various seminars and conferences, especially the EARIE 2006, for helpful comments. The usual disclaimers apply.

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  1. VTT Technical Research Centre of Finland, P.O. Box 1000, VTT, 02044, Finland

    Mariagrazia Squicciarini

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  1. Mariagrazia Squicciarini
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Correspondence to Mariagrazia Squicciarini.

Appendix

Appendix

Table 1A Merged samples: Onoff Wald test with constant # observations
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Squicciarini, M. Science Parks’ tenants versus out-of-Park firms: who innovates more? A duration model. J Technol Transfer 33, 45–71 (2008). https://doi.org/10.1007/s10961-007-9037-z

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