A relational approach to knowledge spillovers in biotech. Network structures as drivers of inter-organizational citation patterns

In this paper, we analyze the geography of knowledge spillovers in biotech by investigating the way in which knowledge ties are organized. Following a relational account on knowledge spillovers, we depict knowledge networks as complex evolving structures that build on pre-existing knowledge and previously formed ties. In economic geography, there is still little understanding of how structural network forces (like preferential attachment and closure) shape the structure and formation of knowledge spillover networks in space. Our study investigates the knowledge spillover networks of biotech firms by means of inter-organizational citation patterns based on USPTO biotech patents in the years 2008-2010. Using a Stochastic Actor-Oriented Model (SAOM), we explain the driving forces behind the decision of actors to cite patents produced by other actors. Doing so, we address directly the endogenous forces of knowledge dynamics.

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