Share or Solo? Platform's and Social Choices in Ride-Hailing

Abstract

Ride-hailing platforms offer riders pooling services, enabling them to share rides with other riders. The introduction of shared rides can mitigate the driver shortage and reduce rider wait times, especially in rush hours, but it may compromise riders' privacy, space, and security. This paper investigates a queueing model in which riders decide whether to join the queue and, if joining, whether to opt for a shared or solo ride based on past experiences of the wait times of each option. In the event of choosing a shared ride, riders may need to wait for another fellow rider for carpooling. We examine the optimal prices for inducing self-interested riders to choose a joining rate and a sharing likelihood that maximize throughput, revenue, or social welfare. The optimal joining rate and sharing likelihood under revenue maximization are consistently lower than those under social welfare maximization and volume maximization. As the sharing experience improves (i.e., the potentially negative sharing externality stochastically increases) and the sharing likelihood remains constant (in alignment with observations from a Chicago dataset), the revenue-maximizing shared price rises while, surprisingly, the revenue-maximizing solo price decreases. This is because the platform needs to compensate solo riders more due to a more congested system resulting from increased ride uptake. Under social welfare maximization, the price difference between solo and shared rides is less than that under revenue maximization, yet, counterintuitively, the actual prices are not necessarily lower. Lastly, we conduct a numerical study using ride-hailing data from Chicago in August 2019, corroborating our theoretical findings.

Keywords: Sharing Economy, Ride-Hailing, Ride-Sharing, Queuing Economics