Driving Forces Behind Relational Knowledge Sourcing in Clusters: Single- and Multilevel Approaches

Abstract

The critical importance of knowledge sourcing as learning relationships and its impact on innovation have been widely discussed in the cluster literature. The aim of this paper is twofold. First, inspired by the relational turn in economic geography, this paper reviews the driving forces of relational knowledge sourcing in clusters. Particularly, it discusses the critical factors of inter-organizational knowledge sourcing embedded at node (agency), dyadic (proximity), and structural (network micro-determinants) levels. In doing so, it goes beyond the cluster literature and builds on concepts and evidence in multiple related fields ranging from network science to behavioral studies, to relational inequality theory and evolutionary economic geography. Second, it synthesizes and extends the scholarly debate on knowledge sourcing in clusters by addressing a multilevel perspective. This article raises multiple theoretically informed research questions for future empirical cluster studies and underlines potential implications for cluster and place-based innovation policies.