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Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method
Journal of Advanced Transportation ( IF 2.0 ) Pub Date : 2021-07-01 , DOI: 10.1155/2021/5584008
Pei Liu 1 , Junlan Chen 1 , Heyang Sun 1 , Xiucheng Guo 1 , Yan Wang 2 , Zhenjun Zhu 3
Affiliation  

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.

中文翻译:

通过社交网络分析方法评估无桩共享单车网络的可访问性

无桩共享单车在交通运输中发挥着越来越重要的作用,尤其是在第一/最后一英里。然而,用户并不总是可以找到共享单车。本文的目的是从网络的角度评估无桩共享单车的可达性,这不仅为潜在的自行车用户,而且为城市规划者、政策制定者和自行车供应商优化共享单车系统提供决策依据。 . 考虑到自行车出行的特点,采用层次聚类算法构建无桩共享单车网络。采用社会网络分析(SNA)方法来评估自行车网络的可达性。然后,选择空间交互模型进行相关分析,以比较从 SNA 方法获得的可达性。上海的案例研究表明可达性与 SNA 指标之间存在很强的联系,相关系数为 0.779,证明了该方法的可行性。由于 SNA 方法考虑了自行车网络的交互障碍和网络结构,因此本文有助于深入了解无桩共享自行车网络的可访问性。开发的方法需要较少的数据并且易于操作。因此,它可以作为一种工具,促进共享单车的智能管理,以改善可持续的交通系统。上海的案例研究表明可达性与 SNA 指标之间存在很强的联系,相关系数为 0.779,证明了该方法的可行性。由于 SNA 方法考虑了自行车网络的交互障碍和网络结构,因此本文有助于深入了解无桩共享自行车网络的可访问性。开发的方法需要较少的数据并且易于操作。因此,它可以作为一种工具,促进共享单车的智能管理,以改善可持续的交通系统。上海的案例研究表明可达性与 SNA 指标之间存在很强的联系,相关系数为 0.779,证明了该方法的可行性。由于 SNA 方法考虑了自行车网络的交互障碍和网络结构,因此本文有助于深入了解无桩共享自行车网络的可访问性。开发的方法需要较少的数据并且易于操作。因此,它可以作为一种工具,促进共享单车的智能管理,以改善可持续的交通系统。由于 SNA 方法考虑了自行车网络的交互障碍和网络结构,因此本文有助于深入了解无桩共享自行车网络的可访问性。开发的方法需要较少的数据并且易于操作。因此,它可以作为一种工具,促进共享单车的智能管理,以改善可持续的交通系统。由于 SNA 方法考虑了自行车网络的交互障碍和网络结构,因此本文有助于深入了解无桩共享自行车网络的可访问性。开发的方法需要较少的数据并且易于操作。因此,它可以作为一种工具,促进共享单车的智能管理,以改善可持续的交通系统。
更新日期:2021-07-01
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