IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i17p7690-d1471517.html
   My bibliography  Save this article

Nonlinear and Threshold Effects of the Built Environment on Dockless Bike-Sharing

Author

Listed:
  • Ming Chen

    (Shanghai Investigation, Design and Research Institute Co., Ltd., 65 Linxin Road, Shanghai 200335, China)

  • Ting Wang

    (College of Transportation Engineering, Tongji University, Shanghai 200070, China
    The Key Laboratory of Road and Traffic Engineering, Ministry of Education, 4800 Cao’an Road, Shanghai 201804, China)

  • Zongshi Liu

    (College of Transportation Engineering, Tongji University, Shanghai 200070, China
    The Key Laboratory of Road and Traffic Engineering, Ministry of Education, 4800 Cao’an Road, Shanghai 201804, China)

  • Ye Li

    (College of Transportation Engineering, Tongji University, Shanghai 200070, China
    The Key Laboratory of Road and Traffic Engineering, Ministry of Education, 4800 Cao’an Road, Shanghai 201804, China)

  • Meiting Tu

    (College of Transportation Engineering, Tongji University, Shanghai 200070, China
    The Key Laboratory of Road and Traffic Engineering, Ministry of Education, 4800 Cao’an Road, Shanghai 201804, China)

Abstract

Dockless bike-sharing mobility brings considerable benefits to building low-carbon transportation. However, the operators often rush to seize the market and regulate the services without a good knowledge of this new mobility option, which results in unreasonable layout and management of shared bicycles. Therefore, it is meaningful to explore the relationship between the built environment and bike-sharing ridership. This study proposes a novel framework integrated with the extreme gradient boosting tree model to evaluate the impacts and threshold effects of the built environment on the origin–destination bike-sharing ridership. The results show that most built environment features have strong nonlinear effects on the bike-sharing ridership. The bus density, the industrial ratio, the local population density, and the subway density are the key explanatory variables impacting the bike-sharing ridership. The threshold effects of the built environment are explored based on partial dependence plots, which could improve the bike-sharing system and provide policy implications for green travel and sustainable transportation.

Suggested Citation

  • Ming Chen & Ting Wang & Zongshi Liu & Ye Li & Meiting Tu, 2024. "Nonlinear and Threshold Effects of the Built Environment on Dockless Bike-Sharing," Sustainability, MDPI, vol. 16(17), pages 1-18, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7690-:d:1471517
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/17/7690/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/17/7690/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Zhitao Li & Yuzhen Shang & Guanwei Zhao & Muzhuang Yang, 2022. "Exploring the Multiscale Relationship between the Built Environment and the Metro-Oriented Dockless Bike-Sharing Usage," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    3. Wang, Donggen & Cao, Xinyu, 2017. "Impacts of the built environment on activity-travel behavior: Are there differences between public and private housing residents in Hong Kong?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 25-35.
    4. Yi Lu & Guibo Sun & Chinmoy Sarkar & Zhonghua Gou & Yang Xiao, 2018. "Commuting Mode Choice in a High-Density City: Do Land-Use Density and Diversity Matter in Hong Kong?," IJERPH, MDPI, vol. 15(5), pages 1-13, May.
    5. Felipe González & Carlos Melo-Riquelme & Louis Grange, 2016. "A combined destination and route choice model for a bicycle sharing system," Transportation, Springer, vol. 43(3), pages 407-423, May.
    6. Wafic El-Assi & Mohamed Salah Mahmoud & Khandker Nurul Habib, 2017. "Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto," Transportation, Springer, vol. 44(3), pages 589-613, May.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Yacan & Li, Jingjing & Su, Duan & Zhou, Huiyu, 2023. "Spatial-temporal heterogeneity and built environment nonlinearity in inconsiderate parking of dockless bike-sharing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    2. Pengfei Lin & Jiancheng Weng & Quan Liang & Dimitrios Alivanistos & Siyong Ma, 2020. "Impact of Weather Conditions and Built Environment on Public Bikesharing Trips in Beijing," Networks and Spatial Economics, Springer, vol. 20(1), pages 1-17, March.
    3. 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.
    4. Zhang, Haoran & Song, Xuan & Long, Yin & Xia, Tianqi & Fang, Kai & Zheng, Jianqin & Huang, Dou & Shibasaki, Ryosuke & Liang, Yongtu, 2019. "Mobile phone GPS data in urban bicycle-sharing: Layout optimization and emissions reduction analysis," Applied Energy, Elsevier, vol. 242(C), pages 138-147.
    5. Wang, Ruoxuan & Wu, Jianping & Qi, Geqi, 2022. "Exploring regional sustainable commuting patterns based on dockless bike-sharing data and POI data," Journal of Transport Geography, Elsevier, vol. 102(C).
    6. Hu, Beibei & Zhong, Zhenfang & Zhang, Yanli & Sun, Yue & Jiang, Li & Dong, Xianlei & Sun, Huijun, 2022. "Understanding the influencing factors of bicycle-sharing demand based on residents’ trips," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    7. Bakó, Barna & Berezvai, Zombor & Isztin, Péter & Vigh, Enikő Zita, 2020. "Does Uber affect bicycle-sharing usage? Evidence from a natural experiment in Budapest," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 290-302.
    8. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    9. Mingyang Du & Lin Cheng, 2018. "Better Understanding the Characteristics and Influential Factors of Different Travel Patterns in Free-Floating Bike Sharing: Evidence from Nanjing, China," Sustainability, MDPI, vol. 10(4), pages 1-14, April.
    10. He, Mingwei & He, Chengfeng & Shi, Zhuangbin & He, Min, 2022. "Spatiotemporal heterogeneous effects of socio-demographic and built environment on private car usage: An empirical study of Kunming, China," Journal of Transport Geography, Elsevier, vol. 101(C).
    11. Tomasz Bieliński & Łukasz Dopierała & Maciej Tarkowski & Agnieszka Ważna, 2020. "Lessons from Implementing a Metropolitan Electric Bike Sharing System," Energies, MDPI, vol. 13(23), pages 1-21, November.
    12. Ahmad Adeel & Bruno Notteboom & Ansar Yasar & Kris Scheerlinck & Jeroen Stevens, 2021. "Sustainable Streetscape and Built Environment Designs around BRT Stations: A Stated Choice Experiment Using 3D Visualizations," Sustainability, MDPI, vol. 13(12), pages 1-21, June.
    13. Kajosaari, Anna & Hasanzadeh, Kamyar & Kyttä, Marketta, 2019. "Residential dissonance and walking for transport," Journal of Transport Geography, Elsevier, vol. 74(C), pages 134-144.
    14. Anowar, Sabreena & Eluru, Naveen & Hatzopoulou, Marianne, 2017. "Quantifying the value of a clean ride: How far would you bicycle to avoid exposure to traffic-related air pollution?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 66-78.
    15. Mariano J. Rabassa & Mariana Conte Grand & Christian M. García-Witulski, 2021. "Heat warnings and avoidance behavior: evidence from a bike-sharing system," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 23(1), pages 1-28, January.
    16. Hyungkyoo Kim, 2020. "Seasonal Impacts of Particulate Matter Levels on Bike Sharing in Seoul, South Korea," IJERPH, MDPI, vol. 17(11), pages 1-17, June.
    17. Duan, Zhengyu & Zhao, Haoran & Li, Zhenming, 2023. "Non-linear effects of built environment and socio-demographics on activity space," Journal of Transport Geography, Elsevier, vol. 111(C).
    18. Lingzhu Zhang & Yu Ye & Wenxin Zeng & Alain Chiaradia, 2019. "A Systematic Measurement of Street Quality through Multi-Sourced Urban Data: A Human-Oriented Analysis," IJERPH, MDPI, vol. 16(10), pages 1-24, May.
    19. Hu, Yujie & Zhang, Yongping & Lamb, David & Zhang, Mingming & Jia, Peng, 2019. "Examining and optimizing the BCycle bike-sharing system – A pilot study in Colorado, US," Applied Energy, Elsevier, vol. 247(C), pages 1-12.
    20. Zhaowei Yin & Yuanyuan Guo & Mengshu Zhou & Yixuan Wang & Fengliang Tang, 2024. "Integration between Dockless Bike-Sharing and Buses: The Effect of Urban Road Network Characteristics," Land, MDPI, vol. 13(8), pages 1-24, August.

    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:16:y:2024:i:17:p:7690-:d:1471517. 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.