Abstract
As an emerging mode of transport, bike-sharing is being quickly accepted by Chinese residents due to its convenience and environmental friendliness. As hotspots for bike-sharing, railway-station service areas attract thousands of bikes during peak hours, which can block roads and pedestrian walkways. Of the many works devoted to the connection between bikes and rail, few have addressed the spatial‒temporal pattern of bike-sharing accumulating around station service areas. In this work, we investigate the distribution patterns of bike-sharing in station service areas, which are influenced not only by railway-station ridership but also by the built environment around the station, illustrating obvious spatial heterogeneity. To this end, we established a geographic weighted regression (GWR) model to capture this feature considering the variables of passenger flow and the built environment. Using the data from bike-sharing in Beijing, China, we applied the GWR model to carry out a spatiotemporal characteristic analysis of the relationship between bike-sharing usage in railway-station service areas and its determinants, including the passenger flow in stations, land use, bus lines, and road-network characteristics. The influence of these factors on bike-sharing usage is quite different in time and space. For instance, bus lines are a competing mode of transport with bike-sharing in suburban areas but not in city centers, whereas industrial and residential areas could also heavily affect the bike-sharing demand as well as railway-station ridership. The results of this work can help facilitate the dynamic allocation of bike-sharing and increase the efficiency of this emerging mode of transport.
Highlights
In recent years, bike-sharing has grown significantly in many Chinese cities, as it caters to the public transport policies of convenience, sustainability, and energy saving [1,2]
Bike-sharing usage was defined as a dependent variable, which was affected by many factors, including the passenger flow into the station, the passenger flow out of the station, and the built environment
This study can be summarized as follows: The bike-sharing usage around rail transit stations is mainly affected by the passenger flow into and out of stations, land use, bus lines, and road-network characteristics
Summary
Bike-sharing has grown significantly in many Chinese cities, as it caters to the public transport policies of convenience, sustainability, and energy saving [1,2]. Bike-sharing has benefits for short-distance travel and connecting “the last kilometer” in a given city [3], which is especially evident in the vicinity of rail transit stations. Bike-sharing is a convenient way for residents to travel, but it suffers from some shortcomings, such as unreasonable bicycle parking and the failure to transfer bikes in time. A better understanding of the spatiotemporal characteristics of bike-sharing is needed and could provide management and operational support for enterprises and government departments [4,5,6]. Station service areas are especially interesting for their unique characteristics that affect bike-sharing usage
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