Abstract
Scarcity is an essential issue in service marketing. This study examined scarcity in a game-theoretic setting. It focused on the role of customer evaluations, through satisfaction ratings, on a technology-enabled peer-to-peer sharing economy platform in achieving stable provider–user matching. The model shows that an appropriate market design employing a user-proposing version of Gale and Shapley's (1962) deferred acceptance algorithm for a ride-sharing platform where many users approach a few providers can help avoid congestion and ensure stable matching. To manage scarcity, the model uses a customer satisfaction rating system that modifies the widely used batch matching algorithm by matching highly rated riders much faster than their low-rated peers. A platform's ability to offer time-bound stable matching for highly-rated users during scarcity is likely to help it maintain a competitive edge.
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