Strategy Cluster Workshop: Julia Brennecke
Knowledge networks consisting of links between knowledge elements and social networks composed of interactions between inventors both play a critical role for firm innovation. Taking a multilevel network approach, this study integrates research on the two types of networks and investigates how the knowledge network of a firm influences work-related interactions among its inventors. To this end, I associate inventors with specific knowledge elements in the firm’s knowledge network and examine how this association affects the inventors’ popularity and activity in a work-related advice network. Empirically, I combine survey data on 135 inventors working in a multinational high-tech firm with information derived from the firm’s 1031 patents. Results from multilevel exponential random graph models (ERGM) show that different dimensions of the inventors’ knowledge derived from the knowledge network shape their embeddedness in the advice network in unique ways. The study demonstrates how structural features of the firm’s knowledge stock influence interpersonal interactions among its inventors thereby affecting the intra-organizational diffusion of knowledge and the social process of generating innovation.