Quantifying the relationship between mobility patterns and socioeconomic status of dockless bike-sharing users

Yu Yang, Tianli Gao, Zikun Xu, Yongping Zhang, Chenxin Liu, Fan Shang and Ruiqi Li
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Yu Yang: UrbanNet Lab, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, P. R. China
Tianli Gao: UrbanNet Lab, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, P. R. China2School of Information Engineering, Xi’an Mingde Institute of Technology, Xi’an 710124, P. R. China
Zikun Xu: UrbanNet Lab, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, P. R. China
Yongping Zhang: School of Public Affairs, Zhejiang University, Hangzhou 310058, P. R. China4ZJU-CMZJ Joint Lab on Data Intelligence and Urban Future, Zhejiang University, Hangzhou 310058, P. R. China
Chenxin Liu: UrbanNet Lab, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, P. R. China
Fan Shang: UrbanNet Lab, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, P. R. China
Ruiqi Li: UrbanNet Lab, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, P. R. China

International Journal of Modern Physics C (IJMPC), 2024, vol. 35, issue 09, 1-27

Abstract: Cycling is among the healthiest, greenest, and most affordable means of transportation for a better future city, but mobility patterns of cyclists with different income have rarely been studied due to the limitation of data availability. Newly emergent dockless bike-sharing platforms that record detailed trip information provide us a unique opportunity. Attributing to its better usage flexibility and accessibility, dockless bike-sharing is booming over the past few years worldwide and reviving the cycling fashion in cities. In this work, by exploiting massive platform-collected trip records in four diversified Chinese cities, we reveal that individual mobility patterns, including radius of gyration and average travel distance, are similar among the users with different income, indicating that human beings all follow similar physical rules. However, collective mobility patterns, in terms of average range and diversity of visitation, and commuting direction, exhibit different behaviors and spatial patterns across income categories. Hotspot locations that attract a high volume of cycling activities are quite different over groups, and locations with either a lower or higher income level have a relatively low user ratio. Cyclists from lower income groups are inclined to visit less flourishing locations across all four cities, and have a higher fraction to commute toward the city center in larger cities and away from the city center in smaller cities. Middle income groups of cyclists generally have a higher visitation diversity except in Shanghai. Our findings would be helpful on designing better promotion strategies for dockless bike-sharing platforms and toward the transition to a more inclusive and sustainable transportation.

Keywords: Cycling mobility; dockless sharing bikes; socioeconomic status; green and sustainable transportation (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0129183124501080

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