Managing Congestion in a Matching Market via Demand Information Disclosure

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 largemobile 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 whomost contendwith congestion in the formof competition, namely, male users and thosewho relymore heavily upon outboundmessages formatches.