Operation strategies of hybrid ride-hailing platform with robotaxi service
Shan Chen, Ming Li, Jiafu Su, Linlin WangPurpose
The hybrid ride-hailing platform integrating robotaxi service is emerging with the global practices of robotaxi service. The paper investigates the decision-making to allocate regular and robotaxi service within the platform.
Design/methodology/approach
The paper explores a hybrid ride-hailing platform that operates two divisions of regular and robotaxi service with single-homing passengers and drivers. To allocate regular and robotaxi service considering the reaction of passengers and drivers, the paper employs game-based models to derive the optimal decisions and generate further insights through comparative and numerical analysis.
Findings
The stronger cross-side network effect generally reduces platform profits. Controlling driver scale is a strategic tool for operational optimization. The platform secures higher profits through a partial coverage strategy that limits the total driver scale, and by a full coverage strategy that expands driver scale to the maximum when differentiation is high. When passenger trust in robotaxi and passenger conversion rates are high, the platform tends to shift toward partial coverage, controlling the driver scale to increase vehicle utilization and sustain premium pricing for higher profitability.
Originality/value
This research examines the optimal allocation and pricing strategies for hybrid ride-hailing platforms and provides practical decision support for platform managers and policymakers.