Spatial heterogeneity in distance decay of using bike sharing: An empirical large-scale analysis in Shanghai

Kun Gao,Xiaobo Qu,Aoyong Li,Ying Yang

doi:10.1016/j.trd.2021.102814

Abstract

Distance decay is a vital aspect for modeling spatial interactions of human movements and an indispensable input for land use planning and travel demand prediction models. Although many studies have investigated the usage demand of bike-sharing systems in an area, research investigating the distance decay patterns of using dockless bike-sharing systems (DLBS) from a spatially heterogeneous perspective based on large-scale datasets is lacking. This study firstly utilizes massive transaction record data from DLBS in Shanghai of China and online map navigator Application Programming Interface to empirically estimate the distance decay patterns of using DLBS and reveal the spatial heterogeneity in distance decay of using DLBS across different urban contexts. Afterward, this study examines the mechanism of spatial heterogeneity in distance decay, leveraging multiple data resources including Point of Interest (POI) data, demographic data, and road network data. The associations among the distance decay of using DLBS with built environment factors are investigated by multiple linear regression. Results indicate that factors such as population density, land use entropy, branch road density, and metro station density are significantly related to larger distance decay of using DLBS, while factors such as commercial land use ratio, industrial land use ratio, and motorway density are significantly linked to smaller distance decay in Shanghai. Lastly, we further employ an adaptative geographically weighted regression to investigate the spatial divergences of the influences of built environment factors on distance decay. Results reveal notably distinct and even inverse influences of a built environment factor on the distance decay of using DLBS in different urban contexts. The findings provide insights into the distance decay patterns of using DLBS in different urban contexts and their interactions with the built environment, which can support accurate planning and management of sustainable DLBS as per specific urban characteristics.

Highlights

The bike-sharing system, as a relatively new alternative and environmentally friendly travel choice, has been increasingly prevalent in major metropolises around the world (Chen et al, 2020; Gao et al, 2021; Jin et al, 2015; Lazarus et al, 2020; Wang et al, 2021)
We estimated a global distance decay function using all data in the study area without distinguishing different analysis zone (AZ)
This study endeavors to fill up the gaps in relevant research by deciphering the spatial heterogeneity of the distance decay of using dockless bike-sharing systems (DLBS) and their relationships with the built environment based on empirical analysis in Shanghai of China

Summary

Introduction

The bike-sharing system, as a relatively new alternative and environmentally friendly travel choice, has been increasingly prevalent in major metropolises around the world (Chen et al, 2020; Gao et al, 2021; Jin et al, 2015; Lazarus et al, 2020; Wang et al, 2021). The number of deployed bikes in worldwide bike-sharing systems is estimated to reach 23.2 million by the end of 2019 (Svegander, 2020). Transportation Research Part D 94 (2021) 102814 evolved to be dockless bike-sharing systems (DLBS) with improved flexibility (Chen et al, 2020; Guo and He, 2020). DLBS is demonstrated to be beneficial for mitigating transport emissions, promoting multimodal transport connections, and improving public health (Barbour et al, 2019; Zhang and Mi, 2018). The development of DLBS encounter appearing concerns. Imbalances between supplies and demands in spatial and temporal dimensions have been a barrier for the takeup of DLBS (Wang et al, 2018; Pal and Zhang, 2017); unorderly parking and unsuited allocations of bicycles result in deuterogenic traffic issues (e.g., occupying pedestrian and driving lanes) and low utilization rates (Wang et al, 2020; Sun et al, 2019; Shui and Szeto, 2018)

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