Joint knowledge generation in European R&D networks: Results from a latent regression - index function model

The objective of this study is to explore the determinants of inter-organisational knowledge generation within European networks of R&D collaboration. It is argued that social capital is a key determinant for successful knowledge generation. Thus, factors that are conducive for the development of social capital like geographical proximity, collaboration duration and intensity are expected to have a positive influence on inter-organisational knowledge generation. Determinants of inter-organisational knowledge generation are investigated by casting a probit model in the form of a latent regression - index function model. Units of analysis are dyads of organisations that jointly participated in projects of the Fifth EU Framework Programme (FP5). The data used in this study derives from a survey among FP5 participants and the EUPRO database. Our findings suggest that crossing national border has a significant positive rather than negative effect on the generation of scientific knowledge [measured in terms of co-publications]. This can be attributed to the participation rules and proposal selection procedures of the Framework Programmes. Another important result is that university-university dyads have the highest probability not only to jointly generate scientific knowledge, but also to jointly generate knowledge that resulted in commercial outcome. In contrast, industry-industry dyads show a low probability for both types of knowledge generation. This result is probably due to the fact that inter-organisational knowledge generation entails disclosure of knowledge, which is actually a task of universities but problematic for industry organisations.