Pricing Strategies Under Behavioral Observational Learning in Social Networks

Liangfei Qiu, Andrew Whinston
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引用次数: 24

Abstract

The increasing pervasiveness of social networks allows users to share purchase behaviors with their online friends. In the present 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 by 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.
社会网络中行为观察学习下的定价策略
社交网络的日益普及使得用户能够与他们的在线好友分享购买行为。在本研究中,我们使用一个考虑社会网络中行为观察学习的分析模型来检验垄断企业的最优定价策略。我们表明,卖家可以潜在地控制未来客户可获得的信息,并通过使用信息披露定价策略诱导行为观察学习。这一结果表明,在社交网络中提供介绍性折扣并不总是促进购买的有效方法。它可能会阻止行为观察学习,而行为观察学习可能会增加未来客户的支付意愿。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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