A Study on the Spatiotemporal Distribution and Usage Pattern of Dockless Shared Bicycles—The Case of Nanjing

Abstract

Determining the spatiotemporal deployment strategy for dockless shared bicycles in urban blocks has always been a focal point for city managers and planners. Extensive research has delved into the usage patterns in terms of time and space, deduced travel purposes, and scrutinized the relationship between trips and the built environment. The elements of the built environment are significantly correlated with the starting and ending points of dockless shared bicycle trips, leading to a scarcity of shared bicycles in areas that are more frequently used as starting points and an abundance of idle bicycles in areas that serve as endpoints. This paper posits that the idle state of shared bicycles is as important as their usage. Utilizing a case study of Xinjiekou Central District in Nanjing, China, we propose a framework for analyzing the temporal and spatial usage and idleness of shared bicycles. We also discuss the impact of various factors, such as proximity to transit stations, land use, and road accessibility, on the different usage and idle states of dockless shared bicycles. The findings reveal that the public transportation system has a similar influence on both the utilization and idleness of dockless shared bicycles, indicating that areas with a dense concentration of transportation services experience greater demand for shared bicycles as both origins and destinations. The influence of other factors on the usage and idleness of dockless shared bicycles varies significantly, resulting in either a shortage or surplus of these bicycles. Consequently, based on the findings regarding the use and idleness of dockless shared bicycles, we formulate a redistribution and zone-based management strategy for shared bicycles. This paper offers new insights into the spatiotemporal distribution and utilization of shared bicycles under the influence of different built environments, contributing to the further optimization of dockless shared bicycle resource allocation.