Marketing Department's Lecture

Theme：Usage Uncertainty and Pricing Schemes in the Ride-Hailing Industry: A Structural Approach

Speaker： Miao Wei (the NUS Business School)

Time：2019-11-11 14:00

Address：Room 1008, Mingde Business Building

Language：English/Chinese

Abstract：

The ride-hailing industry is a critical pillar of modern transportation infrastructure and generates massive amounts of revenue. Due to spatial mismatch and search friction, the conventional taxi business model, which is based on street hailing, leads to substantial matching inefficiency. With the advent of geolocation-based mobile apps, ride-hailing firms can now effectively bridge demand and supply via digitalized matching technology and benefit from more flexibility in setting their pricing menus. In this paper, we analyze an exogenous event in which the largest taxi operator in Singapore added an origin-destination-based flat-fare option to its existing metered fare option. We empirically examine the effect of flat-fare pricing vis-à-vis metered pricing on the outcome of this two-sided marketplace. Specifically, we model taxi drivers’ location choices as a dynamic spatial oligopoly game in which vacant drivers decide where to search for passengers, given the search behaviors of their competitors, in the presence of trip uncertainties. We leverage the large number of agents in the taxi industry and solve for the oblivious equilibrium (Weintraub, Benkard, and Van Roy 2008), in which each taxi driver’s policy function is based on their beliefs about the transition of average industry 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 find that drivers are risk averse on flat-fare trips, especially during peak hours when trip uncertainty is higher, and riders’ risk aversion on metered trips also confers a risk premium on the flat-fare pricing option. Finally, we run counterfactual experiments to quantify the economic value of risk aversion for both riders and drivers, and evaluate the benefit of a booking system that enables flat fares. Our findings have important managerial implications for the rapidly expanding ride-hailing industry.

Keywords：

Ride-hailing Industry, Pricing Schemes, Risk Aversion, Uncertainty, Oblivious Equilibrium, Dynamic Spatial Oligopoly Game

Short biography：

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.