【公开学术报告】Usage Uncertainty and Pricing Scheme in a Two-sided Market: A Structural Analysis of the Ride-hailing Industry

Topic: Usage Uncertainty and Pricing Scheme in a Two-sided Market: A Structural Analysis of the Ride-hailing Industry （双边市场中的使用不确定性与定价策略：网约车行业的结构分析）

Date & Time: 9:30-11:00am, Mon. 23^rd, September 2019

Venue: Room 2101, Tongji Building A

Language: English

Speaker：Dr. Wei MIAO (National University of Singapore)

ABSTRACT

Due to spatial mismatch and search friction, the conventional taxi business model based on street hailing leads to substantial matching inefficiency. With the advent of geolocation-based mobile apps, ride-hailing firms now can effectively bridge demand and supply via centralized matching technology, and have more flexibility in setting their pricing menus as well. In this paper, we take advantage of an exogenous event that the largest taxi operator in Singapore added an origin-destination-based flat fare option to its existing metered fare option, to empirically examine the the effect of flat rate pricing vis-à-vis usage-based pricing on the outcome of this two-sided marketplace. Specifically, we model taxi drivers’ location choices as a dynamic spatial oligopoly game in which forward-looking drivers decide where to search for passengers given search behaviors of their competitors in the presence of trip uncertainties. We tackle the curse of dimensionality issue by leveraging the large number of agents in the taxi industry and solving for the Oblivious Equilibrium (Weintraub, Benkard, and Van Roy 2008), where taxi drivers' policy functions are based on their beliefs of the transition of the industry average states. We then plug supply estimates into the demand system and recover demand parameters with a parametric aggregate level matching function that accounts for matching inefficiency on street hail trips. We show that drivers are risk-averse on flat fare trips, especially during peak hours when trip uncertainty is higher; riders’ risk aversion on metered trips also grants a risk premium for the flat fare pricing option. Finally, we run two counterfactual experiments to quantify the economic value of risk-aversion presented by both riders and drivers, and evaluate the benefit of the booking system that enables such flat fare. Our findings have important managerial implications for the rapidly expanding ride-hailing industry.

Guest Bio:

Miao Wei is a Ph.D. candidate in Quantitative Marketing at the NUS Business School, National University of Singapore. He received a B.A. in Economics from Fudan University in 2014. His research interests span digital marketing, platform economics, and incentive design, and he employs quantitative methods including structural models and field experimental methods in his research. In his job market paper, he develops a novel dynamic structural model to investigate how passengers and drivers respond to flat fare pricing versus metered pricing when there is trip uncertainty in the ride-hailing industry. He also works on the causes and solutions to driver fraud in the taxi industry and contest design.