Collaborative Networks as Determinants of Knowledge Diffusion Patterns

This paper examines if interpersonal networks help explain two widely documented patterns of knowledge diffusion: (1) geographic localization of knowledge flows, and (2) localization of knowledge flows within firm boundaries. I measure knowledge flows using patent citation data, and employ a novel regression framework based on choice-based sampling to estimate the probability of knowledge flow between inventors of any two patents. As expected, intra-regional and intra-firm knowledge flows are found to be stronger than those across regional or firm boundaries. I explore if these patterns can be explained by direct and indirect network ties between inventors, as inferred from past collaborations between them. The existence of a tie is found to be associated with a greater probability of knowledge flow, with the probability decreasing as the path length (geodesic) increases. Further, the effect of regional or firm boundaries on knowledge flow decreases once interpersonal ties have been accounted for. In fact, being in the same region or firm is found to have little additional effect on the probability of knowledge flow between inventors that already have close network ties. The overall evidence is consistent with a view that interpersonal networks are important in determining observed patterns of knowledge diffusion