Driving a More Prosperous Future
Market Formation, Pricing, and Revenue Sharing in Ride Hailing Services
Manufacturing & Service Operations Management, September 2025
Problem definition: We empirically study the market for ride-hailing services. In particular, we explore the following questions: (i) How do the two-sided market and prices jointly form in ride-hailing marketplaces? (ii) Does surge pricing create value and for whom? How can its efficiency be improved? (iii) Can platforms' strategy on revenue sharing with drivers be improved? (iv) What is the value generated by ride-hailing services, including hosting rival taxi services on ride-hailing apps? Methodology/Results: We develop a discrete choice model for the formation of mutually dependent demand (customer side) and supply (driver side) that jointly determine pricing. Using this model and a comprehensive data set obtained from the largest mobile ride platform in China, we estimate customer and driver price elasticities and other factors that affect market participation for the company's two main markets, namely basic ride-hailing and Taxi services. Based on these estimation results and counterfactual analysis, we demonstrate that surge pricing improves customer and driver welfare as well as platform revenues, while counterintuitively reducing Taxi revenues on the platform. However, surge pricing should be avoided during non-peak hours as it can hurt both customer and platform surplus. We show that platform revenues can be improved by increasing drivers' revenue share from the current levels. Finally, we estimate that the platform's basic ride-hailing services generated customer value equivalent to 13.25 Billion USD in China in 2024, and hosting rival Taxi services on the platform boosted customer surplus by 3.6 Billion USD. Managerial Implications: Our empirical framework provides ride-hailing companies a way to estimate demand and supply functions, which can help with optimization of multiple aspects of their operations. Our findings suggest that ride-hailing platforms can improve profits by containing surge-pricing to peak hours only and boosting supply by increasing driver compensation. Finally, our results demonstrate that restricting ride-hailing services create significant welfare losses while including taxi services on ride-hail platforms generate substantial economic value
Liu Ming, Tunay I. Tunca, Yi Xu, and Weiming Zhu
Logistics Service Provider Technology Report
Logistics Service Provider Technology Report
The Logistics Service Provider Technology Report (LSPTR) will be an annual report published by the University of Maryland’s Supply Chain Management Center that aims to provide technology spend visibility for logistics service providers (LSPs) in a variety of areas.
We find that LSPs do not know how much to invest in technology because public filings do not disclose specifics about IT spend, consulting firms have limited data to back their perspectives, and industry analysts are bias and do not collect hard data. Shippers also cannot compare providers' technology capabilities or investments due to LSPs alignment with strategy being unclear despite marketing various capabilities, and they cannot compare their partners’ technology investment within their segment or the broader market.
Publishing an annual technology report compiling technology spend data will provide a solution to the identified problems and create value for stakeholder groups including, but not limited to: LSPs, software vendors, hardware vendors, shippers, industry associations, trade groups, shareholders, and consulting firms.
The report will encompass all technology-related expenditures of the companies who opt in to provide a complete perspective of LSP interest, activity, and spend on technology, with an initial proof-of-concept/pilot addressing 2 key sub-sets of technology in 2025: AI and robotics.
Geoff Milsom - UMD Professor
Jaclyn Wilton - Advisor
Maggie McGuire - Fellow
Ryan Sachar - UMD Undergraduate Student
Ivy Zheng - UMD Undergraduate Student