Tunay Tunca Directory Page
Tunay Tunca
Dean's Professor of Management Science and Operations Management
PhD, Stanford University
Tunay Tunca is the Dean’s Professor of Management Science and Operations Management at the Robert H. Smith School of Business at University of Maryland. He received his M.S. in Management Science from University of Rochester, and M.S. in Financial Mathematics and Ph.D. in Business Administration from Stanford University. Prior to joining University of Maryland, he was an Associate Professor of Operations, Information, and Technology at Stanford GSB. Professor Tunca has also been a visiting scholar at the Sloan School of Business at Massachusetts Institute of Technology, Wharton School of Business at University of Pennsylvania, Yahoo Inc., and Hewlett-Packard. His research interests are in economics of operations management focusing on theoretical and empirical analysis of supply chains, innovative operations, and sharing economy business models. His work has won awards and recognitions from Management Science, M&SOM, iFORM, POMS, and CSAMSE. He is the winner of several teaching awards at the Smith School, including the Allen J. Krowe Teaching Excellence Award in 2014 and 2019, and Distinguished Teaching Awards in 2015-2019. He currently serves as an Associate Editor for the journals Management Science and M&SOM.
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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