Diffusion by Imitation: The Importance of Targeting Agents

We study the optimal targeting strategy of a planner who seeks to maximize the diffusion of an action in a network where agents imitate successful past behavior of their neighbors. We find that the optimal targeting strategy depends on two parameters: (i) the likelihood of the action being more successful than its alternative and (ii) the planner's patience. More specifically, when the planner's preferred action has higher probability of being more successful than its alternative, then the optimal strategy for an infinitely patient planner is to concentrate all the targeted agents in one connected group; whereas when this probability is lower it is optimal to spread them uniformly around the network. Interestingly, for a very impatient planner, the optimal targeting strategy is exactly the opposite. Our results highlight the importance of knowing a society's exact network structure for the efficient design of targeting strategies, especially in settings where the agents are positionally similar.