Optimal Influence Under Observational Learning

Abstract

We study the optimal targeting problem of a firm that seeks to maximize the diffusion of a product in a society where agents learn from their neighbors. The firm can seed the product to a subset of the population and our goal is to find which the optimal subset to target is. We provide a condition that characterizes the optimal targeting strategy for any network structure. The key parameter in this condition is the agents' decay centrality, which takes into account how close an agent is to others, in a way that distant agents are weighted less than closer ones.

Keywords: Social Networks, Targeting, Diffusion, Observational Learning, Decay Centrality

JEL Classification: D83, D85, M37, H23