Revenue-Maximizing Mechanisms with Strategic Customers and Unknown, Markovian Demand

• 成果类型: Article
• 署名作者: Gershkov, Alex; Moldovanu, Benny; Strack, Philipp
• 署名单位: Hebrew University of Jerusalem; Hebrew University of Jerusalem; University of Surrey; University of Bonn; University of California System; University of California Berkeley
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2017.2724
• 发表日期: 2018
• 页码: 2031-2046
• 关键词: revenue management; strategic consumer behavior; name your own price; Markov arrival process

摘要

We show that appropriate dynamic pricing strategies can be used to draw benefits from the presence of consumers who strategically time their purchase even if the arrival process is not known. In our model, a seller sells a stock of objects to a stream of randomly arriving long-lived agents. Agents are privately informed about their values, and about their arrival time to the market. The seller needs to learn about future demand from past arrivals. We characterize the revenue-maximizing direct mechanism. While the optimal mechanism cannot be reduced to posted prices (and requires personalized prices), we also present a simple, learn and then sell mechanism that is able to extract a large fraction of the maximal revenue. In this mechanism, the seller first charges a relatively low price that allows learning about the arrival process, and in a second stage, the seller charges the optimal posted price given the previously obtained information.