Algorithmic Assortment Curation: An Empirical Study of Buybox in Online Marketplaces

Santiago Gallino (), Nil Karacaoglu () and Antonio Moreno ()
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Santiago Gallino: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Nil Karacaoglu: Fisher College of Business, Ohio State University, Columbus, Ohio 43210
Antonio Moreno: Harvard Business School, Harvard University, Boston, Massachusetts 02163

Manufacturing & Service Operations Management, 2025, vol. 27, issue 3, 917-934

Abstract: Problem definition : Online marketplaces have revolutionized online sales by creating platforms that connect millions of buyers and sellers. Although the presence of numerous third-party sellers attracts customers, it also results in a proliferation of listings for each product, making it difficult for customers to choose between the available options. To address this issue, online marketplaces employ algorithmic tools to curate and present different product listings to customers. Although tools that assist customers in choosing between different products , such as recommender systems and reviews, have been studied extensively, there is limited evidence regarding tools that help customers choose between different listings of the same product . This paper focuses on the buybox algorithm, an algorithmic tool that prominently presents one option as the default choice to customers. Methodology/results : We assess the influence of the buybox on marketplace dynamics by examining its staggered introduction within a major product category in a leading online marketplace. Our results show that the implementation of buybox increases the number of orders and enhances the efficiency of the customer journey. This is evidenced by an increase in conversion rates and a more pronounced buybox effect on the mobile channel, where search frictions are higher compared with the desktop channel. The introduction of buybox simplifies the process of posting new products on the marketplace, potentially reducing friction for sellers. We find supporting evidence for this hypothesis, because the number of sellers offering a product increases after the introduction of buybox. Managerial implications : Our analysis reveals that a buybox is an effective tool for reducing search frictions and stimulating competition among sellers. Customers benefit from lower prices and higher average quality levels when competition in a buybox is intense. However, the marketplace becomes more concentrated following the introduction of the buybox, representing an unintended consequence that platforms and vendors should manage. Our study contributes to the growing literature on algorithms in platforms by examining how algorithmic curation affects marketplace participants and overall marketplace dynamics.

Keywords: algorithmic curation; buybox; empirical operations; marketplace operations; online marketplaces; retail operations (search for similar items in EconPapers)
Date: 2025
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