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The impact of research and technology organizations on firm competitiveness. Measurement and determinants

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Abstract

The objective of this work is to evaluate the impact of research and technology organizations (RTO) on firm competitiveness. To this end, we develop a framework that includes strategies to deal with the methodological problems highlighted in the literature. The main features of this framework are the definition and classification of different types of impacts, the estimation of (rough) quantitative measures of them and the development of a multivariate model to explain the different impacts including the traditional indicators of firm characteristics and their relationships. The empirical work is based on a database constructed from information from the responses to a questionnaire designed specifically to estimate the impact of RTOs on Spanish firms, and information from the Spanish Innovation Survey. Our findings show that firms are able to recognize the influence of these relationships on different technical, economic, investment and intangible impacts and to roughly estimate their economic impact, and that several characteristics of these relationships affect the impact of RTOs.

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Notes

  1. An exception is the study by Brown et al. (1991) which covers a broader set of strategies.

  2. That is, we compare two different treatments instead of one treatment versus non treatment.

  3. This was the latest wave available at the start of this study.

  4. Around 20% of firms wrongly categorized their partners. Some university institutes or PROs were categorized as TIs and, conversely, some TIs were put into the PRO category.

  5. For a more in depth analysis of these differences, see Barge-Gil et al. (2008).

  6. It is crucial to point out that the overall impact of PROs in productive sector competitiveness is much higher, as there are many indirect impacts stemming from training and academics’ own research. In other words, our analysis should not be seen as an evaluation of universities’ performance overall, but only of their more usual third mission activities. However, in the case of TIs our analysis can be regarded as an evaluation of these organizations as a whole since their activities are oriented entirely towards improving competitiveness through joint research and the provision of innovation services.

  7. These impact categories are highly interrelated, especially over time. An examination of these interrelations, however, is beyond the scope of this study, but it is an interesting topic for future research.

  8. In the sense that we limit the influences of outliers by applying winsorization.

  9. Anecdotal evidence suggest that this result might be due not so much to the actual interaction with a university, but to the greater initial distance between the R&D and other firm departments in the case of those firms interacting with them, compared to the situation in firms that interact with TIs.

  10. We are aware that the proper econometric way to perform the analysis would rely on instrumental variables. However, small sample size and the absence of good instruments led us to take the ‘more simple’ empirical strategy based on regressions with controls (Jaffe 2002).

  11. The authors are grateful to an anonymous referee for highlighting this point.

  12. Unfortunately, we do not have data on total money contracted during the previous 5 years. However, we think that 3 years is a good proxy for this ideal measure.

  13. In the case of quantitative impact we proved both robust least squares and Tobit. The high number of zero values made us opt for the Tobit estimations.

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Acknowledgments

The authors acknowledge the financial support of FEDIT and the help provided by the Spanish Institute of Statistics. They also thank participants in DRUID 2009 Summer Conference for the comments received and Ángela Vásquez-Urriago for excellent research assistance. The usual disclaimer applies.

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Authors and Affiliations

  1. Department of Foundations of Economic Analysis II (Quantitative Economics), Complutense University, 28223, Madrid, Spain

    Andrés Barge-Gil

  2. Laboratory for Analysis and Assessment of Technical Change, Carlos III University, C/ Madrid 126, 28902, Getafe, Madrid, Spain

    Aurelia Modrego

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  1. Andrés Barge-Gil
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  2. Aurelia Modrego
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Correspondence to Andrés Barge-Gil.

Appendices

Appendix 1: Survey questionnaire (impacts)

figure afigure a

Appendix 2: Factorial analysis

See Table 4.

Table 4 Factorial analysis
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Barge-Gil, A., Modrego, A. The impact of research and technology organizations on firm competitiveness. Measurement and determinants. J Technol Transf 36, 61–83 (2011). https://doi.org/10.1007/s10961-009-9132-4

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