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

Alex Gershkov, Benny Moldovanu, Philipp Strack
2018 Management science  
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
more » ... chanism. 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 Introduction Revenue Management -broadly speaking, the study of the dynamic allocation of capacity and its pricing under uncertain, fluctuating demand -has been pioneered on an industrial scale by airline companies in the * We are grateful to the area editor Serguei Netessine, the associate editor and three referees for helpful comments. A previous version of this paper has been circulated under the title "Demand Uncertainty and Dynamic Allocation with Strategic Agents". We also wish to thank mid 70's. These practices have rapidly spread to the allocation of fixed capacities in hotel booking, freight transportation, car rentals and holiday resorts, the retail of seasonal and style goods (e.g., groceries and apparel), electricity generation, e-business (online advertising and broadcasting, allocation of bandwidth), and event management (sports, concerts, etc...).
doi:10.1287/mnsc.2017.2724 fatcat:ufrbxgbtqncs3jsk2rqmqe2hba