Joint Knowledge Production in European R&D Networks: Results from a Discrete Choice Modeling Perspective

The objective of this study is to explore the determinants of inter-organizational 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 influence the development of social capital like geographical separation, or collaboration duration and intensity are expected to have an impact on inter-organizational knowledge generation. Determinants of inter-organizational knowledge generation are investigated by casting a binary response model in the form of a latent regression – index function model. Units of analysis are dyads of organizations 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 significantly positive rather than negative effect on scientific knowledge generation [measured in terms of reported co-publication activity]. This can be attributed to the participation rules and proposal selection procedures of the Framework Programmes. Another important result is that university dyads have the highest probability not only to generate scientific knowledge jointly, but also to jointly generate knowledge that is commercially relevant. In contrast, industry dyads show a low probability for both types of knowledge generation. This result is probably due to the fact that inter-organizational knowledge generation entails disclosure of knowledge, which is actually a task of universities but problematic for industry organizations.