Pricing, Shareability, and Mode Choices in a Ride-Sourcing Market

With the recent rapid growth of technology-enabled mobility services, ride-sourcing platforms, such as Uber and DiDi, have launched commercial on-demand ride-sharing programs that allow dedicated drivers to serve more than one passenger per ride. Without requiring the prearrangement of trip schedules, these programs match dynamic on-demand passenger requests with vehicles that have vacant seats. Ride-sharing platforms are expected to offer benefits for both individual passengers in the form of cost savings and for society in the form of traffic alleviation and emission reduction. To this end, ride-share operating strategies are important. In addition to some exogenous variables and environments for the ride-sourcing market, such as city size and population density, three key decisions govern a platform’s efficiency for ride-sharing services: discounted trip fare, vehicle fleet size, and allowable detour time. An appropriate discounted fare attracts an adequate number of passengers for ride-sharing, and thus increases the successful pairing rate, while an appropriate allowable detour time prevents passengers from being discouraged from opting into ride-sharing. We develop a mathematical model to elucidate the complex relationships between the variables and decisions involved in an on-demand dynamic ride-sharing market. Specifically, we study the passengers’ mode choices and travel costs, and how the successful pairing rate and actual detour time are jointly determined by the allowable detour time and passenger demand for ride-sharing. We find that a unit decrease in trip fare in a ride-sharing market attracts more passengers than …