Optimal Targeting Strategies in a Network Under Complementarities

The goal of the present paper is to analyze the optimal targeting strategies of a planner (say a monopolist) who aims to increase the aggregate action of agents (consumers' purchase). Agents are embedded in a social network and their actions influence each other. Actions are complements, determined by a reaction to the exposure to neighbors's actions. The description includes best responses as in strategic games and mechanical influences as in contagion or mimesis. When the reaction function is linear, the optimal planner's strategies are explicit, characterized by well-known centralities indices. When the reaction function is concave or convex but not linear, new features pertaining to the pattern of the agents' attention and the joint impact between pairs determine the optimal strategy. The value of information on the impact structure is shown to be (almost always) positive and related to some form of heterogeneity between agents