Flow-Integrated Efficiency Assessment of Shared Bicycles and Its Influencing Factors: A Case Study of Beijing

As dockless bike-sharing systems rapidly expanded across China, scholars have increasingly examined bicycle usage efficiency across locations and its relationship to the geographical environment. Existing studies rely primarily on big data to evaluate location-specific efficiency using Time-to-Booking (ToB)—the idle duration before a bicycle is rented at a given location. This indicator, however, ignores network flow effects: bicycles departing from the same location may reach destinations with vastly different ToB values. This gap is addressed by incorporating the destination ToB after each trip, developing a flow-integrated ToB index for central Beijing. Analysis reveals that the improved index exhibits significant spatial heterogeneity while maintaining the overall distribution pattern of the original metric, indicating that most bicycles flow to areas with efficiency similar to that of their origin. The flow-integrated index compresses the efficiency range—maximum values decrease, minimum values increase—suggesting greater spatial balance in usage efficiency. Bicycles in the city center consistently show higher usage efficiency than those in peripheral areas. Multiple factors influence usage efficiency with significant spatial heterogeneity. Understanding of bike-sharing efficiency is advanced, and practical insights are provided for operators and urban planners in developing refined management strategies.