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Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method

机译:Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method

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摘要

Dockless sharing bikes play an increasingly significant role in transit transfer, especially for the first/last mile. However, it is not always accessible for users to find sharing bicycles. The objective of this paper is to assess the accessibility of dockless sharing bikes from a network perspective, which would provide a decision-making basis not only for potential bike users but also for urban planners, policymakers, and bicycle suppliers to optimize sharing-bike systems. Considering bicycle travel characteristics, a hierarchical clustering algorithm was applied to construct the dockless sharing-bike network. The social network analysis (SNA) method was adopted to assess the accessibility of the bike network. Then, a spatial interaction model was chosen to conduct a correlation analysis to compare the accessibility obtained from the SNA approach. The case study of Shanghai indicates a strong connection between the accessibility and the SNA indicators with the correlation coefficient of 0.779, which demonstrates the feasibility of the proposed method. This paper contributes to a deep understanding of dockless sharing-bike network accessibility since the SNA approach considers both the interaction barriers and the network structure of a bicycle network. The developed methodology requires fewer data and is easy to operate. Thus, it can serve as a tool to facilitate the smart management of sharing bikes for improving a sustainable transportation system.

著录项

  • 来源
    《Journal of advanced transportation》 |2021年第6期|5584008.1-5584008.13|共13页
  • 作者单位

    Southeast Univ, Sch Transportat, 2 Dongnandaxue Rd, Nanjing 211189, Peoples R China;

    Southeast Univ, Chien Shiung Wu Coll SEU, 2 Dongnandaxue Rd, Nanjing 211189, Peoples R China;

    Nanjing Forestry Univ, Coll Automobile & Traff Engn, 159 Longpan Rd, Nanjing 211189, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 英语
  • 中图分类
  • 关键词

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