Collaborative Networks as Determinants of Knowledge Diffusion Patterns

Abstract

This paper examines whether interpersonal networks help explain two widely documented patterns of knowledge diffusion: (1) geographic localization of knowledge flows, and (2) concentration 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, intraregional and intrafirm knowledge flows are found to be stronger than those across regional or firm boundaries. I explore whether these patterns can be explained by direct and indirect network ties among inventors, as inferred from past collaborations among 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. Furthermore, 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 among inventors who 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.