Double Sided Platforms with Stochastic Supply and Demand

Abstract

We consider a double-sided platform which objective is to match customers with providers. Such platforms are the enablers of the so-called gig economy or crowdworking phenomenon. Double sided platforms offer convenience for customers and flexibility for workers. For instance, in the context of ride hailing the convenience translates in customers requesting rides anytime from any location to any destination (within some boundaries). Moreover, drivers are flexible to decide when to be available to accept requests and when to be unavailable. Therefore, by design, supply and demand are stochastic. We model these features following a queueing theoretic approach. In the single class case, the problem can be viewed as a typical queueing system with a stochastically changing number of available servers. We analyze the stability of such system and obtain diffusion approximations to quantify its performance. We discuss how our results can be generalized to the context of a closed queueing network