Understanding the lock-in effect of on-demand ride-hailing services

Abstract

On-demand ride-hailing platforms have recently been criticized for being less efficient than traditional street-hailing services in certain scenarios. To characterize this phenomenon, we propose “the lock-in effect” in ride-hailing services, in which initial matches are locked in despite better matches becoming possible later. To better understand the lock-in effect and mitigate its negative impacts, we propose a matching-flexible reactive ride-hailing framework with realistic operation settings. Case studies using real-world data are conducted to explore the existence conditions and impacts of the lock-in effect. The key findings are: (i) The lock-in effect in ride-hailing services tends to occur in low-supply scenarios. Its inefficiencies primarily affect either service rate or total service distance (but not simultaneously). (ii) The proposed mitigation strategy enhances ride-hailing efficiency across all supply scenarios (low-supply and high-supply) and demand patterns (dense, medium, and sparse demand). The findings will support the efficient operation and management of on-demand mobility services.