Pricing Strategies under Behavioral Observational Learning in Social Networks
研究了垄断企业在社交网络中考虑用户行为观察学习时的最优定价策略，发现信息揭示定价能控制未来顾客的信息，而入门折扣可能无效。
The increasing pervasiveness of social networks allows users to share purchase behaviors with their online friends. In this study, we examine optimal pricing strategies of a monopolistic firm using an analytical model that accounts for behavioral observational learning in social networks. We show that a seller could potentially control the information available to future customers and induce behavioral observational learning, using an information‐revealing pricing strategy. This result suggests that offering introductory discounts is not always an effective method to boost purchases in social networks. It could prevent the behavioral observational learning that would increase future customers' willingness to pay.