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University knowledge and firm innovation: evidence from European countries

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Abstract

In recent decades, firms have intensified the exploration of external sources of knowledge to enhance their innovation capabilities. This paper presents an empirical analysis of the factors that affect the importance of academic knowledge for firms’ innovation activities. An integrated approach that simultaneously considers country- and firm-level factors is adopted. Regarding the former factors, the analysis shows that the entrepreneurial orientation of university and the quality of academic research increase the importance of knowledge transfers from universities to firms. This suggests that the environmental and institutional context contributes to cross-national disparities in university-industry interactions and the effectiveness of knowledge transfer. In regard to the latter factors, the results indicate that firms oriented toward open search strategies and radical innovations are more likely to draw knowledge from universities. Furthermore, firms belonging to high technology sectors and firms with high absorptive capacity place greater value on the various links with universities. With respect to firm size, the estimates show an inverted U-shaped relation with the importance of universities as a source of knowledge.

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Notes

  1. Due to the criteria used to select observations and missing values for some variables, the final sample only includes 14 of the 16 countries available. Norway and Ireland do not have any observations that meet the above mentioned criteria.

  2. For Patents and GERD business-university the source of data is Eurostat and 2006 is the reference year.

  3. Quacquarelli Symonds (QS) is a British company specialized in education and study abroad. The company releases annual university rankings to compare the world's top universities. Today, the rankings are known as the QS World University Rankings and are considered as one of the three most influential university rankings in the world, along with the Times Higher Education World University Rankings and the Academic Ranking of World Universities.

  4. With ordinal dependent variables, the assumptions of ordinary least square estimator are violated (normality and homoscedasticity of error term) which can lead to incorrect inferences. Ordered logit and ordered probit models provide consistent estimates. For more details, see Greene (2008).

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Acknowledgments

We would like to thank the participants at the International Conference on Technology Transfer, Urbino, Italy and at The Christmas Workshop, Hohenheim, Germany. We are grateful for comments and suggestions from Francesco Venturini (discussant). We thank Lisa Tarzia for the revision of the paper. Andrea Bellucci acknowledges the support from the FP7 Marie Curie Actions of the European Commission, via the Intra European Fellowship (Grant Agreement Number PIEF-GA-2012-331728). Luca Pennacchio (l.pennacchio@unina.it) acknowledges the support of REPOS project.

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Bellucci, A., Pennacchio, L. University knowledge and firm innovation: evidence from European countries. J Technol Transf 41, 730–752 (2016). https://doi.org/10.1007/s10961-015-9408-9

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