Improving the fate of a Bike: A Usage-Continuity-Driven predictive framework for Bike-Sharing rebalancing under sparse demand

Key Points

• This predictive framework enhances bike-sharing rebalancing, leading to improved usage continuity across various scenarios.
• By optimizing bike placement and availability, the framework can significantly reduce user wait times by up to 30%.
• Observational analysis incorporates demand patterns and user behavior to inform rebalancing strategies effectively.
• Improved algorithms may enable sustainability in bike-sharing systems, although further validation in diverse regions is needed.