Modeling and regulating a ride-sourcing market integrated with vehicle rental services

• Main Authors: MO, Dong, WANG, Hai, CAI, Zeen, SZETO, W. Y., CHEN, Xiqun (Michael)
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Bi-level optimization; Regulatory policies; Ride-sourcing; Social welfare; Vehicle rental service; Artificial Intelligence and Robotics; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/9355; https://ink.library.smu.edu.sg/context/sis_research/article/10355/viewcontent/ssrn_4325150_sv.pdf
• Institution: Singapore Management University

With the popularity of on-demand ride services worldwide, ride-sourcing platforms must maintain an adequate fleet size and cope with growing travel demand. Recently, platforms have attempted to provide vehicle rental services to drivers who do not own cars, then recruited them to provide on demand ride services. This helps lower the entry barrier for drivers and offers another profitable business for platforms. From the government's perspective, however, it is challenging to coordinately regulate a ride-sourcing business and vehicle rental business. This paper proposes a bi-level optimization model to investigate how the government regulates the ride-sourcing market integrated with vehicle rental services. Specifically, how the government designs regulatory policies for minimum driver wage and maximum vehicle rental fee at the upper level, and how a monopoly profit-oriented platform optimizes riders’ price, drivers’ wage, and vehicle rental fee at the lower level. We derive an analytical phase diagram for the two policies and present the government's decisions in five mutually exclusive regions with respect to regulatory effects, i.e., ineffective region, minimum-driver-wage-effective region, maximum-rental-fee-effective region, coordinated policy region, and infeasible region. Our theoretical and numerical results indicate that the government should precisely coordinate the two policies to achieve higher total social welfare, i.e., the weighted sum of rider surplus, driver surplus, and platform profit. We also prove that if the weights of all stakeholders in social welfare are equal, the platform's vehicle rental business will achieve zero profit when the total social welfare is maximized. The proposed model and analytical results generate managerial insights and provide suggestions for government regulation and platform operations management in the ride-sourcing market integrated with vehicle rental services.