The effect of traffic status on dockless bicycle-sharing: Evidence from Shanghai, China

Abstract

Dockless bicycle sharing (DBS) has become a popular form of public transport worldwide over recent years, which contributes mightily to solving the increasingly frequent traffic congestion and parking issues in urban areas. However, its spatiotemporal usage patterns and determinants have not been fully investigated. In particular, the existing studies have not provided clear insight into the effect of traffic status on DBS trips. To address this shortcoming, this study proposes a model framework to understand DBS from multiple aspects. Within this framework, descriptive statistics and visualisation methods are employed to explore the spatiotemporal travel patterns of DBS in the downtown area of Shanghai. By adopting spatial panel models, the impacts of the built environment, weather, and traffic status on DBS in different regions are examined, and the heterogeneity analysis of traffic status factors is further conducted. The results have shown that DBS in Shanghai has obvious tidal distribution characteristics. The supply of DBS exceeds the demand in the peripheral areas of the city, while the opposite is true in the city centre. In addition, the traffic state index, bus stop density, residential and commercial land area have a positive contribution to DBS usage and have obvious positive spatial spillover effects. The results from the heterogeneity analysis have revealed that the influencing mechanism of DBS usage varies by location and riding duration. These findings of the present paper can provide an effective basis for DBS demand distribution forecasting, regional rebalancing, and connecting traffic planning, thereby facilitating the usage of DBS, promoting intermodal transport, and reducing carbon emissions.