IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v163y2022icp353-369.html
   My bibliography  Save this article

Measuring the vulnerability of bike-sharing system

Author

Listed:
  • Zhang, Liye
  • Xiao, Zhe
  • Ren, Shen
  • Qin, Zheng
  • Goh, Rick Siow Mong
  • Song, Jie

Abstract

As a complex system, the bike-sharing system suffers from system failures, which can increase travel costs and impair user satisfaction. We proposed a concept of the vulnerability of bike-sharing system and a method to measure it. The method depends on the cost changes due to additional travel time induced by the failure of bike docking stations. It can capture the traffic mode transfer in the context of multi-modal traffic system, such as walking, bus, and subway. Moreover, to investigate the impact of network structure on the vulnerability, we developed the centrality measuring methods, and a community detection model for the bike-sharing system. Subsequently, the proposed methods are applied to Citi Bike in New York City, the largest bike-sharing system in the USA. The results show that the most vulnerable bike docking stations are located far from bus and railway stations, with low docking station density in their surrounding areas. We also found that the number of nearby bicycle stations, bus stops, and subway stations have a negative correlation with the vulnerability index. In contrast, the degree centrality and trip betweenness centrality are positively associated with the index. The proposed vulnerability analysis method can help urban planners to evaluate the design of a bike-sharing system and buttress operators to optimize maintenance planning.

Suggested Citation

  • Zhang, Liye & Xiao, Zhe & Ren, Shen & Qin, Zheng & Goh, Rick Siow Mong & Song, Jie, 2022. "Measuring the vulnerability of bike-sharing system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 353-369.
    • Handle: RePEc:eee:transa:v:163:y:2022:i:c:p:353-369
    DOI: 10.1016/j.tra.2022.05.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856422001409
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2022.05.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Derrible, Sybil & Kennedy, Christopher, 2010. "The complexity and robustness of metro networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3678-3691.
    2. Jiang, Ruoyun & Lu, Qing-Chang & Peng, Zhong-Ren, 2018. "A station-based rail transit network vulnerability measure considering land use dependency," Journal of Transport Geography, Elsevier, vol. 66(C), pages 10-18.
    3. Mor Kaspi & Tal Raviv & Michal Tzur, 2017. "Bike-sharing systems: User dissatisfaction in the presence of unusable bicycles," IISE Transactions, Taylor & Francis Journals, vol. 49(2), pages 144-158, February.
    4. Elliot Fishman, 2016. "Bikeshare: A Review of Recent Literature," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 92-113, January.
    5. Mishra, Sabyasachee & Welch, Timothy F. & Jha, Manoj K., 2012. "Performance indicators for public transit connectivity in multi-modal transportation networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1066-1085.
    6. Sun, Daniel (Jian) & Guan, Shituo, 2016. "Measuring vulnerability of urban metro network from line operation perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 348-359.
    7. Akbarzadeh, Meisam & Salehi Reihani, Sayed Farzin & Samani, Keivan Aghababaei, 2019. "Detecting critical links of urban networks using cluster detection methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 288-298.
    8. Berdica, Katja, 2002. "An introduction to road vulnerability: what has been done, is done and should be done," Transport Policy, Elsevier, vol. 9(2), pages 117-127, April.
    9. Oded Cats & Erik Jenelius, 2014. "Dynamic Vulnerability Analysis of Public Transport Networks: Mitigation Effects of Real-Time Information," Networks and Spatial Economics, Springer, vol. 14(3), pages 435-463, December.
    10. Jenelius, Erik, 2009. "Network structure and travel patterns: explaining the geographical disparities of road network vulnerability," Journal of Transport Geography, Elsevier, vol. 17(3), pages 234-244.
    11. Chen, Zhiwei & Guo, Yujie & Stuart, Amy L. & Zhang, Yu & Li, Xiaopeng, 2019. "Exploring the equity performance of bike-sharing systems with disaggregated data: A story of southern Tampa," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 529-545.
    12. Sun, Daniel(Jian) & Ding, Xueqing, 2019. "Spatiotemporal evolution of ridesourcing markets under the new restriction policy: A case study in Shanghai," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 227-239.
    13. Reggiani, Aura & Nijkamp, Peter & Lanzi, Diego, 2015. "Transport resilience and vulnerability: The role of connectivity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 81(C), pages 4-15.
    14. Lugo, Adonia E., 2013. "CicLAvia and human infrastructure in Los Angeles: ethnographic experiments in equitable bike planning," Journal of Transport Geography, Elsevier, vol. 30(C), pages 202-207.
    15. Daniel (Jian) Sun & Yuhan Zhao & Qing-Chang Lu, 2015. "Vulnerability Analysis of Urban Rail Transit Networks: A Case Study of Shanghai, China," Sustainability, MDPI, vol. 7(6), pages 1-18, May.
    16. Cui, Yuchen & Mishra, Sabyasachee & Welch, Timothy F., 2014. "Land use effects on bicycle ridership: a framework for state planning agencies," Journal of Transport Geography, Elsevier, vol. 41(C), pages 220-228.
    17. Nassir, Neema & Hickman, Mark & Malekzadeh, Ali & Irannezhad, Elnaz, 2016. "A utility-based travel impedance measure for public transit network accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 26-39.
    18. Bell, Michael G. H., 2000. "A game theory approach to measuring the performance reliability of transport networks," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 533-545, August.
    19. Kaspi, Mor & Raviv, Tal & Tzur, Michal, 2016. "Detection of unusable bicycles in bike-sharing systems," Omega, Elsevier, vol. 65(C), pages 10-16.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ma, Xinwei & Zhang, Shuai & Wu, Tao & Yang, Yizhe & Yu, Jiajie, 2023. "Can dockless and docked bike-sharing substitute each other? Evidence from Nanjing, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    2. Sun, Daniel (Jian) & Guan, Shituo, 2016. "Measuring vulnerability of urban metro network from line operation perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 348-359.
    3. Nan Zhang & Daniel J. Graham & Daniel Hörcher & Prateek Bansal, 2021. "A causal inference approach to measure the vulnerability of urban metro systems," Transportation, Springer, vol. 48(6), pages 3269-3300, December.
    4. Li, Tao & Rong, Lili & Yan, Kesheng, 2019. "Vulnerability analysis and critical area identification of public transport system: A case of high-speed rail and air transport coupling system in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 55-70.
    5. Lu, Qing-Chang & Zhang, Lei & Xu, Peng-Cheng & Cui, Xin & Li, Jing, 2022. "Modeling network vulnerability of urban rail transit under cascading failures: A Coupled Map Lattices approach," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    6. Kashin Sugishita & Yasuo Asakura, 2021. "Vulnerability studies in the fields of transportation and complex networks: a citation network analysis," Public Transport, Springer, vol. 13(1), pages 1-34, March.
    7. Caterina Malandri & Luca Mantecchini & Filippo Paganelli & Maria Nadia Postorino, 2021. "Public Transport Network Vulnerability and Delay Distribution among Travelers," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
    8. Noguchi, Hiroki & Fuse, Masaaki, 2020. "Rethinking critical node problem for railway networks from the perspective of turn-back operation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    9. Hong, Liu & Ye, Bowen & Yan, Han & Zhang, Hui & Ouyang, Min & (Sean) He, Xiaozheng, 2019. "Spatiotemporal vulnerability analysis of railway systems with heterogeneous train flows," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 725-744.
    10. Jing Liu & Huapu Lu & He Ma & Wenzhi Liu, 2017. "Network Vulnerability Analysis of Rail Transit Plans in Beijng-Tianjin-Hebei Region Considering Connectivity Reliability," Sustainability, MDPI, vol. 9(8), pages 1-17, August.
    11. Rodríguez-Núñez, Eduardo & García-Palomares, Juan Carlos, 2014. "Measuring the vulnerability of public transport networks," Journal of Transport Geography, Elsevier, vol. 35(C), pages 50-63.
    12. Li, Tao & Rong, Lili, 2021. "Impacts of service feature on vulnerability analysis of high-speed rail network," Transport Policy, Elsevier, vol. 110(C), pages 238-253.
    13. Yi Shen & Gang Ren & Bin Ran, 2021. "Cascading failure analysis and robustness optimization of metro networks based on coupled map lattices: a case study of Nanjing, China," Transportation, Springer, vol. 48(2), pages 537-553, April.
    14. Lin Zhang & Jian Lu & Bai-bai Fu & Shu-bin Li, 2018. "A Review and Prospect for the Complexity and Resilience of Urban Public Transit Network Based on Complex Network Theory," Complexity, Hindawi, vol. 2018, pages 1-36, December.
    15. Li, Tao & Rong, Lili, 2020. "A comprehensive method for the robustness assessment of high-speed rail network with operation data: A case in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 666-681.
    16. Jing, Weiwei & Xu, Xiangdong & Pu, Yichao, 2020. "Route redundancy-based approach to identify the critical stations in metro networks: A mean-excess probability measure," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    17. Sun, Lishan & Huang, Yuchen & Chen, Yanyan & Yao, Liya, 2018. "Vulnerability assessment of urban rail transit based on multi-static weighted method in Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 108(C), pages 12-24.
    18. Almotahari, Amirmasoud & Yazici, Anil, 2021. "A computationally efficient metric for identification of critical links in large transportation networks," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    19. Lu, Qing-Chang, 2018. "Modeling network resilience of rail transit under operational incidents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 227-237.
    20. Qing-Chang Lu & Shan Lin, 2019. "Vulnerability Analysis of Urban Rail Transit Network within Multi-Modal Public Transport Networks," Sustainability, MDPI, vol. 11(7), pages 1-14, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:163:y:2022:i:c:p:353-369. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.