Managing Congestion in a Matching Market via Demand Information Disclosure

Ni Huang (), Gordon Burtch, Yumei He () and Yili Hong ()
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Ni Huang: Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146
Yumei He: Freeman School of Business, Tulane University, New Orleans, Louisiana 70118
Yili Hong: Miami Herbert Business School, University of Miami, Coral Gables, Florida 33146

Information Systems Research, 2022, vol. 33, issue 4, 1196-1220

Abstract: Congestion is a common issue in digital platform markets, wherein users tend to focus their attention on a subset of popular peers. We examine this issue in the context of online dating, considering the potential efficacy of an informational intervention, namely, the disclosure of peers’ recent demand. In doing so, we first note that the benefits of disclosing demand information are not altogether clear in this context, a priori, because dating platforms are distinct from other platforms in several important respects. On the one hand, dating platforms facilitate social relationships, rather than trade in goods and services. Therefore, they operate on different norms and typically lack common levers that platform operators employ to balance supply and demand, such as pricing mechanisms and reputation systems. Dating app users may therefore pay greater attention to the quality implications of peer demand information, worsening congestion. On the other hand, demand information disclosure may be atypically effective at mitigating congestion in a dating context because, in addition to opportunity costs of time and effort, daters also bear fears of social rejection, leading them to shy away from in-demand peers. We evaluate our treatment’s efficacy in mitigating congestion and improving matching efficiency, conducting a randomized field experiment at a large mobile dating platform. Our results show that the intervention is particularly effective at improving matching efficiency when presented in tandem with a textual message-framing cue that highlights the capacity implications of the peer demand information. Heterogeneity analyses further indicate that these effects are driven primarily by those users who most contend with congestion in the form of competition, namely, male users and those who rely more heavily upon outbound messages for matches.

Keywords: information disclosure; congestion; matching efficiency; online dating; platform design (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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