Optimal Nonlinear Pricing in Social Networks Under Asymmetric Network Information
研究了当客户私下持有本地网络信息时，企业如何在社交网络中制定定价决策，发现最优定价会权衡邻居消费的传染性与自身消费动机，从而产生数量溢价或折扣菜单。
How should a firm make pricing decisions in social networks when the customers hold in private their local network information? In “Optimal Nonlinear Pricing in Social Networks Under Asymmetric Network Information,” Zhang and Chen develop a solution approach based on calculus of variations and positive neighbor affiliation to tackle this problem. They show that the optimal pricing compromises the capitalization of the susceptibility to neighbor consumption with the motivation of one’s own consumption, which gives rise to a menu of quantity premium or quantity discount. In the Erdös and Rényi graph (a special case of the social network model in this paper), they find that the pricing scheme does not screen network positions; consequently, the firm can offer a simple uniform price. The authors also find that, in the context of two-way connections, the firm-optimal consumption becomes linear in customer degree in the scale-free network.