Designing rating-based mechanisms for dockless bike-sharing: Behavioral incentives and sustainable mobility

As a widely adopted mode of urban mobility, dockless bike-sharing offers flexible and affordable short-distance transport. However, the unregulated nature of dockless systems often leads to operational difficulties, such as improper parking and equipment misuse by users, which create unverifiable damages for bike-sharing firms and additional operational costs. We analyze the optimal design of a user rating-based incentive mechanism to promote user effort and mitigate these damages. The proposed mechanism features a simple, binary rating structure that depends only on the user’s most recent behavior. Users receive favorable access unless the most severe form of damage is observed, in which case penalties are applied. This structure induces high-effort behavior through the threat of future exclusion while avoiding the complexity of tracking full behavioral histories. We characterize the conditions under which the firm benefits from implementing this mechanism, highlighting the trade-off between the cost of providing incentives and the gains from reduced damages and lower rebalancing or maintenance needs. By linking operational improvements to broader goals of sustainable and equitable mobility, our findings provide theoretical support for simplified rating systems observed in practice and offer policy-relevant insights for behavior-based digital governance in the sharing economy.