Modeling the Impacts of Driver Income Distributions on Online Ride-Hailing Services

Abstract

The online ride-hailing taxi brings new vitality into the traditional taxi market, as well as new issues and challenges. The pricing and profit distribution of online ride-hailing services is one of the major concerns. This study focuses on the pricing and income distribution in the online ride-hailing system. Queuing system model and birth and death process theory are introduced to describe the driver's flow process in the network. The social welfare maximization model and the platform profit maximization model are constructed based on the dynamic pricing mechanism, from the government's and platform's standpoint, respectively. Through numerical experiments, this paper analyzes the income distribution of drivers under different settings and the influence of different factors (average travel time, psychologically expected price of drivers and passengers, and probability of driver leaving the system) on the proportion of income distribution. The results show that the drivers' income distribution proportion is higher in the pursuit of social welfare maximization than that in the pursuit of platform profit maximization, and in different benefit pursuit models, various factors have a certain influence on the driver's income distribution proportion. The proposed method and conclusion in this study can be considered as references for online ride-hailing market supervision and policy-making.