Position Ranking and Auctions for Online Marketplaces

• 成果类型: Article
• 署名作者: Chu, Leon Yang; Nazerzadeh, Hamid; Zhang, Heng
• 署名单位: University of Southern California
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2019.3372
• 发表日期: 2020
• 页码: 3617-3634
• 关键词: e-commerce platforms; Position auctions; consumer search; seller externalities; mechanism design; social surplus maximization

摘要

Online e-commerce platforms, such as Amazon and Taobao, connect thousands of sellers and consumers every day. In this work, we study how such platforms should rank products displayed to consumers and utilize the top and most salient slots. We present a model that considers consumers' search costs and the externalities sellers im-pose on each other. This model allows us to study a multiobjective optimization, whose objective includes consumer and seller surplus as well as the sales revenue, and derive the optimal ranking decision. In addition, we propose a surplus-ordered ranking mechanism for selling some of the top slots. This mechanism is motivated in part by Amazon's sponsored search program. We show that the Vickrey-Clarke-Groves mechanism would not be applicable to our setting and propose a new mechanism. This mechanism is near optimal, performing significantly better than those that do not incentivize sellers to reveal their private information regarding each consumer purchase, such as their profit. Moreover, we generalize our model to settings in which platforms can provide partial information about the products and facilitate the consumer search and show the robustness of our findings.