Buy-It-Now or Take-a-Chance: Price Discrimination Through Randomized Auctions

• 成果类型: Article
• 署名作者: Celis, L. Elisa; Lewis, Gregory; Mobius, Markus; Nazerzadeh, Hamid
• 署名单位: Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; Microsoft; University of Southern California
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2014.2009
• 发表日期: 2014
• 页码: 2927-2948
• 关键词: Online advertising; Real-Time Bidding; advertisement exchange; Optimal auctions

摘要

Increasingly detailed consumer information makes sophisticated price discrimination possible. At fine levels of aggregation, demand may not obey standard regularity conditions. We propose a new randomized sales mechanism for such environments. Bidders can buy-it-now at a posted price, or take-a-chance in an auction where the top d > 1 bidders are equally likely to win. The randomized allocation incentivizes high-valuation bidders to buy-it-now. We analyze equilibrium behavior and apply our analysis to advertiser bidding data from Microsoft Advertising Exchange. In counterfactual simulations, our mechanism increases revenue by 4.4% and consumer surplus by 14.5% compared to an optimal second-price auction.