Abstract
Online platforms that match customers with suitable service providers utilize a wide variety of platform designs: some create a searchable directory of one side of the market (i.e., Airbnb, Google Local Services); some allow both sides of the market to search and initiate contact (i.e., Care.com, Upwork); others implement centralized matching (i.e., Amazon Home Services, TaskRabbit). This paper compares these platform designs in terms of their efficiency of matchmaking, as proxied by the amount of communication needed to facilitate a good market outcome. We find that the relative performance of these designs is driven by whether the preferences of agents on each side of the market is easy to describe or satisfy. ``Easy to describe'' means that the preferences can be readily captured in a short questionnaire, and ``easy to satisfy'' means that an agent has high preferences for many potential partners. For markets with suitable characteristics, each of the above designs is able to provide performance guarantees that are asymptotically close to the best possible using any conceivable system of matchmaking. The analysis provides prescriptive insights for online platforms.
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