Pricing and Equilibrium in On-demand Ride-Splitting Markets
Posted: 17 Apr 2019 Last revised: 13 Nov 2019
Date Written: March 21, 2019
With the recent rapid growth of technology-enabled mobility services, ride-sourcing platforms, such as Uber and DiDi, have launched commercial on-demand ride-splitting programs that allow drivers to serve more than one passenger per ride. Without requiring the prearrangement of trip schedules, these programs match on-demand passenger requests with vehicles that have vacant seats. Ride-splitting 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. In addition to some exogenous variables and environments for ride-sourcing market, such as city size and population density, three key decisions govern a platform’s efficiency for ride-splitting services: trip fare, vehicle fleet size, and allowable detour time. An appropriate discounted fare attracts an adequate number of passengers for ride-splitting, and thus increases the successful pairing rate, while an appropriate allowable detour time prevents passengers from being discouraged from opting into ride-splitting. We develop a mathematical model to elucidate the complex relationships between the variables and decisions involved in a ride-splitting market. Specifically, we propose two matching functions to characterize the matching rate and pickup time, and investigate the successful pairing rate and actual detour time that are jointly determined by the allowable detour time and passenger demand for ride-splitting. We find that a unit decrease in trip fare in a ride-splitting market attracts more passengers than in a normal non-splitting ride-sourcing market, because it not only directly increases passenger demand due to negative price elasticity, but also reduces actual detour time, which in turn indirectly increases passenger demand. As a result, both the monopoly optimum and social optimum trip fares in a ride-splitting market are lower than in a non-splitting market.
Keywords: on-demand ride-sourcing, ride-splitting, matching friction, successful pairing rate, detour time
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