Share or Solo? Individual and Social Choices in Ride-Hailing
67 Pages Posted: 1 Oct 2020 Last revised: 7 Oct 2021
Date Written: August 16, 2020
Ride-hailing platforms offer riders pooling services to share rides with other riders. The introduction of shared rides mitigates the driver shortage and reduces rider wait times, especially in rush hours, but it may compromise riders' privacy, space, and security. We study a queueing model in which riders wait for drivers and choose whether to join the queue and if joining, whether to take a shared or solo ride without observing the real-time system congestion. In the case of a shared ride is chosen, the rider may need to wait for another fellow rider for carpool. We analyze and compare the choices by decentralized riders and the centralized social planner of joining rates and sharing probabilities, under First-In-First-Out (FIFO) and Priority-For-Sharing (PFS) service disciplines. We discover that, under the FIFO discipline, self-interested riders in equilibrium always under-share, compared to the socially optimal solution. This leads to under-join behavior by riders due to thinner effective system capacity compared to that of the socially optimal system. In contrast, under the PFS discipline, riders may over-share to gain priority over solo riders, regardless of negative sharing externality. Nonetheless, in equilibrium, the social planner can induce decentralized riders to choose the socially optimal arrival rate by charging a toll fee and to choose the socially optimal sharing probability by appropriate social, monetary, or priority schemes. Furthermore, we conduct a numerical study with the ride-hailing data of Chicago in August 2019. Comparing the empirical sharing behavior with the socially optimal solution from our calibrated model, we discover that the practical sharing fraction is lower (resp., greater) than the socially-optimal one in residential areas (resp., downtown) during morning rush hours. And the opposite occurs during evening rush hours.
Keywords: Sharing Economy, Ride-Hailing, Ride-Sharing, Queuing Economics
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