Position Ranking and Auctions for Online Marketplaces

Leon Yang Chu (), Hamid Nazerzadeh () and Heng Zhang ()
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Leon Yang Chu: University of Southern California, Los Angeles, Los Angeles, California 90089
Hamid Nazerzadeh: University of Southern California, Los Angeles, Los Angeles, California 90089
Heng Zhang: University of Southern California, Los Angeles, Los Angeles, California 90089

Management Science, 2020, vol. 66, issue 8, 3617-3634

Abstract: 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 impose 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.

Keywords: e-commerce platforms; position auctions; consumer search; seller externalities; mechanism design; social surplus maximization (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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