Managing Market Thickness in Online Business-to-Business Markets

Kostas Bimpikis (), Wedad J. Elmaghraby (), Ken Moon () and Wenchang Zhang ()
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Kostas Bimpikis: Graduate School of Business, Stanford University, Stanford, California 94305
Wedad J. Elmaghraby: Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742
Ken Moon: The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Wenchang Zhang: Kelley School of Business, University of Indiana, Bloomington, Indiana 47405

Management Science, 2020, vol. 66, issue 12, 5783-5822

Abstract: We explore marketplace design in the context of a business-to-business platform specializing in liquidation auctions. Even when the platform’s aggregate levels of supply and demand remain fixed, we establish that the platform’s ability to use its design levers to manage the availability of supply over time yields significant value. We study two such levers, each using the platform’s availability of supply as a means to incentivize participation from buyers who decide strategically when/how often to participate. First, the platform’s listing policy sets the ending times of incoming auctions (hence, the frequency of market clearing). Exploiting a natural experiment, we illustrate that consolidating auctions’ ending times to certain weekdays increases the platform’s revenues by 7.3% mainly by inducing a higher level of bidder participation. The second lever is a recommendation system that can be used to reveal information about real-time market thickness to potential bidders. The optimization of these levers highlights a novel trade-off. Namely, when the platform consolidates auctions’ ending times, more bidders may participate in the marketplace (demand-side competition); but ultimately auctions for substitutable goods cannibalize one another (supply-side competition). To optimize these design decisions, we estimate a structural model that endogenizes bidders’ dynamic behavior, that is, their decisions on whether/how often to participate in the marketplace and how much to bid. We find that appropriately designing a recommendation system yields an additional revenue increase (on top of the benefits obtained by optimizing the platform’s listing policy) by reducing supply-side cannibalization and altering the composition of participating bidders.

Date: 2020
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Citations: View citations in EconPapers (11)

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