Modelling passengers' reaction to dynamic prices in ride-on-demand services: A search for the best fare

Abstract

In emerging ride-on-demand (RoD) services such as Uber and Didi (in China), dynamic prices play an important role in regulating supply and demand, trying to improve the service quality for both drivers and passengers. In this paper, we take a new perspective to study RoD services besides the supply or demand, and focus on passengers' reaction to dynamic prices. Passengers' reaction can be regarded as a process of searching for the best price before getting on a car, and the searching process reflects passengers' demand elasticity -- “how eager they are requesting a ride”. We collect data of passengers' reaction from a real RoD service provider in China, and analyze the patterns of passengers' reaction. The analysis results show that both the dynamic prices and passengers' demand elasticity influence their reaction. We then adopt and extend a previous model for sequential search from a known distribution to understand passengers' reaction, and use our data to obtain the search costs under various circumstances, which could be interpreted as passengers' demand elasticity. Insights on the search cost and other relevant quantities are discussed. Our expectation is that the result of the study should be helpful not only for service providers in designing dynamic pricing algorithms, but also for passengers and policy makers in understanding the effects and implications of dynamic pricing.