Share or Solo? Individual and Social Choices in Ride-Hailing

Ride-hailing platforms offer riders pooling service to share rides with other riders. On the one hand, pooling service mitigates congestion and decreases rider wait times in rush hours, and sharing riders benefit from reduced prices. On the other hand, sharing riders may compromise on privacy and space when riding with strangers, and may take more time to reach their destinations. We derive a queueing model that considers solo ride and shared ride together, where riders are strategic in choosing which ride to participate. We analyze and compare the decentralized rider decisions and the centralized social planner decisions. In most cases, a smaller fraction of riders choose shared rides compared to that under the socially optimal decision, which we call under-share. Nonetheless, riders can always be induced to choose the socially optimal strategy in equilibrium under a proper monetary, social, or priority scheme. Interestingly, under the priority scheme, overshare can happen, whereas without the priority scheme the decentralized riders behave social-optimally in the same arrival rate and sharing externality range. In contrast to that individual riders always over-join an unobservable M/M/1 queue (compared to the social optimal), riders always under-join the queue in our model with an additional ride-sharing option. Moreover, the social planner may restrict the number of riders even if the arrival rate is below the socially optimal one. This is because social welfare may be a bimodal function of the arrival rate under the assumption that all riders join. At last, we conduct a numerical study with the ride-hailing data of Chicago, and discover that though under-share occurs in residential areas during morning rush hours and in downtown during evening rush hours, the observed sharing fractions are very close to the optimal ones. Over-share occurs during the same time interval but in the opposite areas.