Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method
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 perspecti...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2021/5584008 |
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| _version_ | 1832565254346768384 |
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| author | Pei Liu Junlan Chen Heyang Sun Xiucheng Guo Yan Wang Zhenjun Zhu |
| author_facet | Pei Liu Junlan Chen Heyang Sun Xiucheng Guo Yan Wang Zhenjun Zhu |
| author_sort | Pei Liu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b424fe3fe7634ba9a31a625e47989ce5 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-b424fe3fe7634ba9a31a625e47989ce52025-02-03T01:08:52ZengWileyJournal of Advanced Transportation0197-67292042-31952021-01-01202110.1155/2021/55840085584008Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis MethodPei Liu0Junlan Chen1Heyang Sun2Xiucheng Guo3Yan Wang4Zhenjun Zhu5School of Transportation, Southeast University, No. 2 Dongnandaxue Road, Nanjing 211189, ChinaSchool of Transportation, Southeast University, No. 2 Dongnandaxue Road, Nanjing 211189, ChinaSchool of Transportation, Southeast University, No. 2 Dongnandaxue Road, Nanjing 211189, ChinaSchool of Transportation, Southeast University, No. 2 Dongnandaxue Road, Nanjing 211189, ChinaChien-Shiung Wu College of SEU, Southeast University, No. 2 Dongnandaxue Road, Nanjing 211189, ChinaCollege of Automobile and Traffic Engineering, Nanjing Forestry University, No. 159 Longpan Road, Nanjing 211189, ChinaDockless 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.http://dx.doi.org/10.1155/2021/5584008 |
| spellingShingle | Pei Liu Junlan Chen Heyang Sun Xiucheng Guo Yan Wang Zhenjun Zhu Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method Journal of Advanced Transportation |
| title | Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method |
| title_full | Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method |
| title_fullStr | Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method |
| title_full_unstemmed | Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method |
| title_short | Assessing Accessibility of Dockless Sharing-Bike Networks by the Social Network Analysis Method |
| title_sort | assessing accessibility of dockless sharing bike networks by the social network analysis method |
| url | http://dx.doi.org/10.1155/2021/5584008 |
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