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

33 Pages Posted: 24 Sep 2022 Last revised: 4 May 2023

See all articles by Santiago Gallino

Santiago Gallino

University of Pennsylvania - Operations, Information and Decisions Department

Nil Karacaoglu

Ohio State University (OSU) - Fisher College of Business

Antonio Moreno

Harvard University - Technology & Operations Management Unit

Date Written: May 3, 2023

Abstract

Online marketplaces have revolutionized the way global sales take place, providing a platform for millions of buyers and sellers to connect. While the presence of numerous third-party sellers attracts customers to the platform, it also leads to a proliferation of listings for each product, making it challenging for customers to choose between the available options. To tackle this, online marketplaces utilize algorithmic tools to curate the presentation of different listings of a product to customers. This paper focuses on the Buybox, an algorithmic tool that chooses and presents prominently one option as the default one to
customers.
We assess the Buybox’s influence on marketplace dynamics by examining its staggered introduction within a major product category in a leading online marketplace. Our results demonstrate that Buybox’s implementation mitigates frictions for both customers and sellers and leads to a significant increase in marketplace orders . On the customer side, we observe a decrease in search frictions, as evidenced by increased conversion rates and a more pronounced Buybox effect on the mobile channel, which inherently has higher search frictions compared to the desktop. On the seller side, the number of sellers
offering a product increases after Buybox’s introduction which suggest a decrease in frictions for the sellers.
Our analysis reveals that customers obtain lower prices and higher average quality levels when competition for Buybox is intense. We also find that the marketplace becomes more concentrated following Buybox’s introduction, 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: algorithms, algorithmic curation, online marketplaces, empirical operations, Buybox

Suggested Citation

Gallino, Santiago and Karacaoglu, Nil and Moreno, Antonio, Algorithmic Assortment Curation: An Empirical Study of Buybox in Online Marketplaces (May 3, 2023). Available at SSRN: https://ssrn.com/abstract=4218952 or http://dx.doi.org/10.2139/ssrn.4218952

Santiago Gallino

University of Pennsylvania - Operations, Information and Decisions Department ( email )

3730 Walnut Street
558 & 559 Jon M. Huntsman Hall
Philadelphia, PA 19104-5340
United States

Nil Karacaoglu (Contact Author)

Ohio State University (OSU) - Fisher College of Business ( email )

Antonio Moreno

Harvard University - Technology & Operations Management Unit ( email )

Boston, MA 02163
United States

HOME PAGE: http://www.hbs.edu/faculty/Pages/profile.aspx?facId=1029325

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