Optimal pricing in social networks considering reference price effect

We study the optimal monopoly pricing strategies in a social network, in which consumers experience a network effect that is dependent on their neighbors' consumptions and a reference price which is the average price received by their neighbors. We establish a two-stage game model for any social network. Utilizing the backward induction, we derive the equilibrium price by maximizing the monopolist's profit. In addition, we apply this model to the two most commonly used network structures: the star network and the bipartite network. We find that both the network effect and the reference price effect play a critical role in deciding pricing strategies in social networks. Moreover, our numerical results demonstrate that whether to implement discriminatory pricing depends critically on the network structure. This work provides monopoly firms a useful guideline for optimal pricing decisions in social network marketing.