Abstract Balancing supply and demand for a dockless bike-sharing system is difficult as users are allowed to pick up and return bikes anywhere within a large service area. One strategy to help manage the amount of dockless bikes scattered within a service area is to offer monetary rewards for users who would be willing to pick up bikes scattered around some central location or to return their bikes at this central location. We develop a modeling framework to analyze the effectiveness of using dynamic incentive schemes for balancing the amount of bikes in the system to minimize the expected operating cost. Using an extensive set of numerical experiments, we illustrate specific operation environments under which these dynamic incentive schemes would be most effective for reducing the operating cost of the system. We find that the use of dynamic pickup and return rewards can generate very substantial cost reductions in an operating environment with a high traffic intensity of bike return outside the central location and a high overall traffic intensity of bike returns relative to bike pickups in the system. We also find that return rewards are generally more cost-effective than pickup rewards.
Highlights The first to study dynamic incentive schemes in inventory balancing of bike-sharing. Provide insights in studying effective incentive schemes for bike-sharing firms. Illustrate specific environments under which these schemes would be most effective. The pickup/return rewards achieve substantial cost reduction in bike sharing system. The return rewards are generally more cost-effective than pickup rewards.
Dynamic incentive schemes for managing dockless bike-sharing systems
2021-12-15
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Dockless bike-sharing systems: what are the implications?
Taylor & Francis Verlag | 2020
|Forecasting usage and bike distribution of dockless bike-sharing using journey data
IET | 2020
|Understanding the usage of dockless bike sharing in Singapore
Taylor & Francis Verlag | 2018
|