Driver collusion in ride‐hailing platforms
Manish Tripathy, Jiaru Bai, H. Sebastian Heese
Abstract
ABSTRACT Many on‐demand service platforms employ state‐dependent pricing strategies to balance supply capacity and customer demand. In the context of ride‐hailing platforms, it has been observed that drivers strategically exploit the structure of such pricing policies by coordinating with each other to deactivate some drivers in order to create an artificial shortage of supply capacity and trigger so‐called surge pricing . We develop a simple and high‐level analytical framework to structurally characterize the drivers of such collusive behavior and the consequences for drivers and the platform. We find that collusive driver behavior is more likely in settings where customers exhibit moderate sensitivity to waiting time. For some of these cases, if customers continue to request service under driver collusion, the platform may benefit from the higher surge prices. For settings where driver collusion is harmful to the platform, we consider two possible mitigation strategies: a bonus payment structure to eliminate the drivers' incentives to collude, which comes at a direct cost to the platform, and a freeze period after deactivating the app during which drivers cannot reactivate. We show that with the appropriate duration, such a freeze period can effectively eliminate driver collusion without any direct costs to the platform.