The Ohio State University
The authors propose a dynamic pricing strategy for maximizing the revenue of a seller who wishes to sell a divisible service (good) to buyers (agents) embedded in a social network. They investigate the case where the seller can perfectly price discriminate the socially interconnected buyers with positive social influences on each other. They assume that each buyer purchases a non-negative quantity of the service depending both on her internal valuations and on the purchases of her neighbors in the social network. They relax the usual game theoretic assumption of strategic agents and assume a more realistic model of myopic buyers who choose actions that maximize their present utility and do not take into account the effect of their current actions to their future payoffs.