IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i3p851-d312374.html
   My bibliography  Save this article

Spatio-Temporal Usage Patterns of Dockless Bike-Sharing Service Linking to a Metro Station: A Case Study in Shanghai, China

Author

Listed:
  • Qiang Yan

    (School of Transportation Engineering, Tongji University, 4800 Cao’an Highway, Shanghai 201804, China
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

  • Kun Gao

    (Department of Architecture and Civil Engineering, Chalmers University of Technology, SE-412 96 Gothenburg, Sweden)

  • Lijun Sun

    (School of Transportation Engineering, Tongji University, 4800 Cao’an Highway, Shanghai 201804, China
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

  • Minhua Shao

    (School of Transportation Engineering, Tongji University, 4800 Cao’an Highway, Shanghai 201804, China
    Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

Abstract

The dockless bike-sharing (DLBS) system serves as a link between metro stations and travelers’ destinations (or originations). This paper aims to uncover spatio-temporal usage patterns of dockless bike-sharing service linking to metro stations for supporting scientific planning and management of the dockless bike-sharing system. A powerful visualization tool was used to analyze the differences in usage patterns in workdays and weekends. The travel distance distributions of using dockless bike-sharing near metro stations were investigated to shed light on the service area of the dockless bike-sharing system. Agglomerative hierarchical clustering was applied to analyze differences in usage patterns of metro stations located in different areas. The results show that the usage patterns of dockless bike-sharing on weekends are different from those on workdays. The average travel distance using the dockless bike-sharing system at weekends is significantly larger than that of workdays. The travel distance distribution could be nicely fitted by the Fréchet distribution of the Generalized Extreme Value (GEV) distribution family. The usage characteristics of shared bikes are correlated with land use and population density around metro stations. No matter in urban or suburban areas, there is a great demand for bike-sharing in densely populated areas with intensive land development, such as university towns in suburban areas. This study improves the understandings regarding the usage patterns of the DLBS system serving as a link between the final destinations (or originations) and metro stations. The results can be helpful to the operation and demand management of DLBS.

Suggested Citation

  • Qiang Yan & Kun Gao & Lijun Sun & Minhua Shao, 2020. "Spatio-Temporal Usage Patterns of Dockless Bike-Sharing Service Linking to a Metro Station: A Case Study in Shanghai, China," Sustainability, MDPI, vol. 12(3), pages 1-14, January.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:851-:d:312374
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/3/851/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/3/851/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuan Li & Zhenjun Zhu & Xiucheng Guo, 2019. "Operating Characteristics of Dockless Bike-Sharing Systems near Metro Stations: Case Study in Nanjing City, China," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    2. Li, Hao & Gao, Kun & Tu, Huizhao, 2017. "Variations in mode-specific valuations of travel time reliability and in-vehicle crowding: Implications for demand estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 250-263.
    3. Kou, Zhaoyu & Cai, Hua, 2019. "Understanding bike sharing travel patterns: An analysis of trip data from eight cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 785-797.
    4. Zhao, Pengjun & Li, Shengxiao, 2017. "Bicycle-metro integration in a growing city: The determinants of cycling as a transfer mode in metro station areas in Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 46-60.
    5. Xinwei Ma & Yanjie Ji & Yuchuan Jin & Jianbiao Wang & Mingjia He, 2018. "Modeling the Factors Influencing the Activity Spaces of Bikeshare around Metro Stations: A Spatial Regression Model," Sustainability, MDPI, vol. 10(11), pages 1-12, October.
    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. Montes, Alejandro & Geržinic, Nejc & Veeneman, Wijnand & van Oort, Niels & Hoogendoorn, Serge, 2023. "Shared micromobility and public transport integration - A mode choice study using stated preference data," Research in Transportation Economics, Elsevier, vol. 99(C).
    2. Yu, Qing & Xie, Yingkun & Li, Weifeng & Zhang, Haoran & Liu, Xiaolei & Shang, Wen-Long & Chen, Jinyu & Yang, Dongyuan & Yan, Jinyue, 2022. "GPS data in urban bicycle-sharing: Dynamic electric fence planning with assessment of resource-saving and potential energy consumption increasement," Applied Energy, Elsevier, vol. 322(C).
    3. van Kuijk, Roy J. & de Almeida Correia, Gonçalo Homem & van Oort, Niels & van Arem, Bart, 2022. "Preferences for first and last mile shared mobility between stops and activity locations: A case study of local public transport users in Utrecht, the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 285-306.
    4. Nikolaos-Fivos Galatoulas & Konstantinos N. Genikomsakis & Christos S. Ioakimidis, 2020. "Spatio-Temporal Trends of E-Bike Sharing System Deployment: A Review in Europe, North America and Asia," Sustainability, MDPI, vol. 12(11), pages 1-17, June.

    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. Ying Ni & Jiaqi Chen, 2020. "Exploring the Effects of the Built Environment on Two Transfer Modes for Metros: Dockless Bike Sharing and Taxis," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    2. Gan, Zuoxian & Yang, Min & Zeng, Qingcheng & Timmermans, Harry J.P., 2021. "Associations between built environment, perceived walkability/bikeability and metro transfer patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 171-187.
    3. Cheng, Long & Wang, Kailai & De Vos, Jonas & Huang, Jie & Witlox, Frank, 2022. "Exploring non-linear built environment effects on the integration of free-floating bike-share and urban rail transport: A quantile regression approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 175-187.
    4. Mingyang Du & Lin Cheng & Xuefeng Li & Jingzong Yang, 2019. "Investigating the Influential Factors of Shared Travel Behavior: Comparison between App-Based Third Taxi Service and Free-Floating Bike Sharing in Nanjing, China," Sustainability, MDPI, vol. 11(16), pages 1-18, August.
    5. Zhan, Zilin & Guo, Yuanyuan & Noland, Robert B. & He, Sylvia Y. & Wang, Yacan, 2023. "Analysis of links between dockless bikeshare and metro trips in Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    6. Li, Wenxiang & Chen, Shawen & Dong, Jieshuang & Wu, Jingxian, 2021. "Exploring the spatial variations of transfer distances between dockless bike-sharing systems and metros," Journal of Transport Geography, Elsevier, vol. 92(C).
    7. Dongdong Feng & Lin Cheng & Mingyang Du, 2020. "Exploring the Impact of Dockless Bikeshare on Docked Bikeshare—A Case Study in London," Sustainability, MDPI, vol. 12(15), pages 1-18, July.
    8. Chen, Qun & Pan, Xiaoyi & Liu, Fang & Xiong, Yong & Li, Zhitao & Tang, Jinjun, 2022. "Reposition optimization in free-floating bike-sharing system: A case study in Shenzhen City," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    9. Alexandros Nikitas, 2019. "How to Save Bike-Sharing: An Evidence-Based Survival Toolkit for Policy-Makers and Mobility Providers," Sustainability, MDPI, vol. 11(11), pages 1-17, June.
    10. Kunbo Shi & Long Cheng & Jonas De Vos & Yongchun Yang & Wanpeng Cao & Frank Witlox, 2021. "How does purchasing intangible services online influence the travel to consume these services? A focus on a Chinese context," Transportation, Springer, vol. 48(5), pages 2605-2625, October.
    11. Zijia Wang & Lei Cheng & Yongxing Li & Zhiqiang Li, 2020. "Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    12. Dorsa Alipour & Hussein Dia, 2023. "A Systematic Review of the Role of Land Use, Transport, and Energy-Environment Integration in Shaping Sustainable Cities," Sustainability, MDPI, vol. 15(8), pages 1-29, April.
    13. Dandan Xu & Yang Bian & Shinan Shu, 2020. "Research on the Psychological Model of Free-floating Bike-Sharing Using Behavior: A Case Study of Beijing," Sustainability, MDPI, vol. 12(7), pages 1-18, April.
    14. Lidong Zhu & Mujahid Ali & Elżbieta Macioszek & Mahdi Aghaabbasi & Amin Jan, 2022. "Approaching Sustainable Bike-Sharing Development: A Systematic Review of the Influence of Built Environment Features on Bike-Sharing Ridership," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
    15. Cai Jia & Yanyan Chen & Tingzhao Chen & Yanan Li & Luzhou Lin, 2022. "Evolutionary Game Analysis on Sharing Bicycles and Metro Strategies: Impact of Phasing out Subsidies for Bicycle–Metro Integration Model," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    16. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    17. Lu, Chang & Wu, Yuehui & Yu, Shanchuan, 2022. "A Sample Average Approximation Approach for the Stochastic Dial-A-Ride Problem on a Multigraph with User Satisfaction," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1031-1044.
    18. Bumseok Chun & Anh Nguyen & Qisheng Pan & Elaheh Mirzaaghazadeh, 2024. "Spatial Analysis of Bike-Sharing Ridership for Sustainable Transportation in Houston, Texas," Sustainability, MDPI, vol. 16(6), pages 1-19, March.
    19. Yang Liu & Yanjie Ji & Tao Feng & Zhuangbin Shi, 2020. "Use Frequency of Metro–Bikeshare Integration: Evidence from Nanjing, China," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    20. Ma, Xiaobo & Karimpour, Abolfazl & Wu, Yao-Jan, 2020. "Statistical evaluation of data requirement for ramp metering performance assessment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 248-261.

    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:gam:jsusta:v:12:y:2020:i:3:p:851-:d:312374. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.