Tipping Point in Ride-Hailing Service Systems with Sharing Option

Abstract

This paper examines different car-sharing models offered by ride-hailing firms. In the traditional car-hailing model, customers are served individually by taxis or private cars. In the sharing-only model, all customers are willing to share the ride with other customers. In the hybrid model, customers may choose either individual or shared service provided by the same fleet of cars. Customers incur a hassle cost when they share the ride with others. We develop a queueing game-theoretic model to help a monopoly ride-hailing firm (i) determine the arrival rates that create the maximum customer value and (ii) choose admission fees that extract the maximum profits. First, we discover a tipping point in the hybrid model under the optimal customer behavior. When the hassle cost decreases to this point, (i) the optimal customer behavior immediately switches from less than 80% customers using shared service to all using it, (ii) the optimal arrival rate increases dramatically, and (iii) the rate at which a decreasing hassle cost improves the maximum customer value significantly increases. Second, when the hassle cost is higher than the tipping point, the hybrid model, with homogeneous customers using both individual and shared services, may generate higher customer value than the other two models. This means that the firm can improve customer value by assigning homogeneous customers to differentiated services, which are considered to be beneficial only when customers are heterogeneous in the conventional wisdom. Finally, we propose a profit-maximizing admission fee structure in the hybrid model to maximize the firm's profit, and we demonstrate its effectiveness.