Endogenous Matching in University-Industry Collaboration: Theory and Empirical Evidence from the United Kingdom - Banal-Estañol, Albert; Macho-Stadler, Inés; Pérez-Castrillo, David (Management Science, 2018)
We use a two-sided matching framework to analyze collaboration between heterogeneous academics and firms. We consider both horizontal and vertical characteristics—those related to affinity (e.g., preferences for a type of scientific research) and those related to ability (e.g., capacity to produce high-quality scientific output). We build a unique data set based on the teams of academics and firms that proposed research projects to the UK’s Engineering and Physical Sciences Research Council. Our results are suggestive of positive assortative matching in terms of ability and type, while the matching is negative assortative in terms of their interactions. The most able and the most applied academics are the ones that are more likely to propose collaborative as opposed to noncollaborative projects. Data are available at https://doi.org/10.1287/mnsc.2016.2680 . This paper was accepted by David Hsu, entrepreneurship and innovation.