Improving Ride-Hailing Platform Operations in Dynamic Markets: A Drivers' Switching Perspective

Improving the performance of the operations of ride-hailing platforms (RHPs) by adequately considering drivers' switching behaviors is becoming crucial for their profitability and sustainability. This study explores how to optimize the operations of RHPs by investigating the impact of commission rates on drivers' switching behaviors in a dynamic mobility market. Two queue-theory-based mathematical models have been developed to explore the relationship between commission rates, drivers' switching behaviors, and critical platform parameters in optimizing the operations of RHPs. Numerical examples are presented to demonstrate the applicability of such models in determining the best commission rate to optimize the operations of RHPs in duopoly and fully competitive market conditions. The findings suggest that understanding the intricate relationship between commission rates, drivers' switching behaviors, and critical platform parameters is significant for RHPs in formulating appropriate strategies and policies to ensure their sustainable operations.