Understanding the Operational Dynamics of Mobility Service Providers: A Case of Uber

The rise of mobility service providers (MSPs) is reforming the traditional taxi service (TTS) market. MSPs differ from TTS with the core idea of using technology to optimally match riders with drivers, features like ride-sharing and surge pricing, and are not entry-regulated. It is of great significance to understand how MSPs operate and how we can integrate them with TTS for efficient urban mobility. Unfortunately, little is known about MSPs due to limited data revealed by them. In this study, we collect and mine the trajectory data of online drivers who serve Uber (one of the largest MSP) to demystify how Uber drives their drivers. We analyze the trip patterns of different Uber services and reveal their market share, trip metrics, and the spatial distributions of trip origins and destinations. We explore how MSPs improve the driver-rider matching efficiency and empirically validate the enormous efficiency gap between TTS and MSPs. In the end, we debunk the surge price as an instrument to restore driver-rider balance theory and show that drivers choose to chase or avoid the high surge areas depending on various other factors such as traffic congestion, time and location, and availability of alternate travel options as well. The results of this article provide insightful knowledge about the supply side of MSPs and contribute to new ideas on improving TTS and regulating MSPs.