Valentina Assenova, Management, The Wharton School
Abstract: Existing research on the diffusion of innovations has focused on the benefits of using central influencers to trigger adoption cascades in networks. Yet, prior work has not examined how influencers’ role complexity moderates these benefits. Role complexity pertains to being embedded in complex networks with multiple types of ties, for example, co-authorship and co-patenting ties. This paper examines and offers evidence that influencers’ role complexity moderates the benefits of eigenvector centrality in network-based diffusion processes. Using data from a network-based intervention seeding influencers, I demonstrate that influencers’ role complexity undermined adoption among their contacts. The findings reveal important scope conditions on the benefits of using central influencers to diffuse innovations through networks.