IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i18p13576-d1237559.html
   My bibliography  Save this article

Study on the Relationship between the Spatial Distribution of Shared Bicycle Travel Demand and Urban Built Environment

Author

Listed:
  • Lili Yang

    (College of Transportation, Jilin University, Changchun 130022, China)

  • Simeng Fei

    (College of Transportation, Jilin University, Changchun 130022, China)

  • Hongfei Jia

    (College of Transportation, Jilin University, Changchun 130022, China)

  • Jingdong Qi

    (Changchun Municipal Engineering Design & Research Institute, Changchun 130022, China)

  • Luyao Wang

    (Shenyang Urban Planning & Design Institute, Shenyang 110004, China)

  • Xinning Hu

    (College of Transportation, Jilin University, Changchun 130022, China)

Abstract

As a green and sustainable trip mode, shared bicycles play an essential role in completing short-distance trips in cities. This paper proposes a method to analyze the impact of the urban built environment on the distribution of shared bicycles in a small-scale space. First, the Fishnet function of ArcGIS is utilized to divide the study area into grids of 500 m × 500 m. Then, three indicators are proposed to describe the characteristics of the urban built environment, including point of information (POI) comprehensive index, the intensity of public transportation coverage, spatial accessibility, providing them the ways to be assigned to the grids. Finally, the multivariable linear regression model and support vector regression (SVR) models are applied to reveal the impacts of built environment factors on the spatial distribution of shared bicycles. Results show that SVR models based on linear kernel function, Gaussian radial basis kernel function, and Polynomial kernel function can achieve better analysis results. The SVR model based on the Gaussian radial basis function shows higher explanatory power (adjusted R 2 = 0.978) than the multivariable linear regression model (adjusted R 2 = 0.847). This paper can aid in understanding the demand and supply of shared bicycles and help operators or governments to improve service quality.

Suggested Citation

  • Lili Yang & Simeng Fei & Hongfei Jia & Jingdong Qi & Luyao Wang & Xinning Hu, 2023. "Study on the Relationship between the Spatial Distribution of Shared Bicycle Travel Demand and Urban Built Environment," Sustainability, MDPI, vol. 15(18), pages 1-16, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13576-:d:1237559
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/18/13576/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/18/13576/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mao Ye & Yajing Chen & Guixin Yang & Bo Wang & Qizhou Hu, 2020. "Mixed Logit Models for Travelers’ Mode Shifting Considering Bike-Sharing," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
    2. Wang, Kailai & Akar, Gulsah, 2019. "Gender gap generators for bike share ridership: Evidence from Citi Bike system in New York City," Journal of Transport Geography, Elsevier, vol. 76(C), pages 1-9.
    3. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system," Journal of Transport Geography, Elsevier, vol. 54(C), pages 218-227.
    4. Caggiani, Leonardo & Colovic, Aleksandra & Ottomanelli, Michele, 2020. "An equality-based model for bike-sharing stations location in bicycle-public transport multimodal mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 251-265.
    5. Zhang, Ying & Thomas, Tom & Brussel, Mark & van Maarseveen, Martin, 2017. "Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China," Journal of Transport Geography, Elsevier, vol. 58(C), pages 59-70.
    6. Maas, Suzanne & Attard, Maria & Caruana, Mark Anthony, 2020. "Assessing spatial and social dimensions of shared bicycle use in a Southern European island context: The case of Las Palmas de Gran Canaria," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 81-97.
    7. Mohammad Javad Koohsari & Rachel Cole & Koichiro Oka & Ai Shibata & Akitomo Yasunaga & Tomoya Hanibuchi & Neville Owen & Takemi Sugiyama, 2020. "Associations of built environment attributes with bicycle use for transport," Environment and Planning B, , vol. 47(9), pages 1745-1757, November.
    8. Xing, Yingying & Wang, Ke & Lu, Jian John, 2020. "Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 87(C).
    9. 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. Kumar Dey, Bibhas & Anowar, Sabreena & Eluru, Naveen, 2021. "A framework for estimating bikeshare origin destination flows using a multiple discrete continuous system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 119-133.
    2. 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).
    3. Kyoungok Kim, 2024. "Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass: a case study from Seoul," Transportation, Springer, vol. 51(4), pages 1373-1407, August.
    4. Liu, Hung-Chi & Lin, Jen-Jia, 2019. "Associations of built environments with spatiotemporal patterns of public bicycle use," Journal of Transport Geography, Elsevier, vol. 74(C), pages 299-312.
    5. Mix, Richard & Hurtubia, Ricardo & Raveau, Sebastián, 2022. "Optimal location of bike-sharing stations: A built environment and accessibility approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 126-142.
    6. De Zhao & Ghim Ping Ong & Wei Wang & Wei Zhou, 2021. "Estimating Public Bicycle Trip Characteristics with Consideration of Built Environment Data," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    7. 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).
    8. Wang, Xudong & Cheng, Zhanhong & Trépanier, Martin & Sun, Lijun, 2021. "Modeling bike-sharing demand using a regression model with spatially varying coefficients," Journal of Transport Geography, Elsevier, vol. 93(C).
    9. Rodrigo Mora & Pablo Moran, 2020. "Public Bike Sharing Programs Under the Prism of Urban Planning Officials: The Case of Santiago de Chile," Sustainability, MDPI, vol. 12(14), pages 1-20, July.
    10. Wang, Kailai & Chen, Yu-Jen, 2020. "Joint analysis of the impacts of built environment on bikeshare station capacity and trip attractions," Journal of Transport Geography, Elsevier, vol. 82(C).
    11. 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.
    12. 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 1-27, August.
    13. Ji, Shujuan & Liu, Xiaojie & Wang, Yuanqing, 2024. "The role of road infrastructures in the usage of bikeshare and private bicycle," Transport Policy, Elsevier, vol. 149(C), pages 234-246.
    14. Zhou, Xiaolu & Wang, Mingshu & Li, Dongying, 2019. "Bike-sharing or taxi? Modeling the choices of travel mode in Chicago using machine learning," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    15. 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.
    16. 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.
    17. Mao Ye & Yajing Chen & Guixin Yang & Bo Wang & Qizhou Hu, 2020. "Mixed Logit Models for Travelers’ Mode Shifting Considering Bike-Sharing," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
    18. 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.
    19. Zacharias, John & Meng, Si'an, 2021. "Environmental correlates of dock-less shared bicycle trip origins and destinations," Journal of Transport Geography, Elsevier, vol. 92(C).
    20. Mohammad Anwar Alattar & Caitlin Cottrill & Mark Beecroft, 2021. "Sources and Applications of Emerging Active Travel Data: A Review of the Literature," Sustainability, MDPI, vol. 13(13), pages 1-17, June.

    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:15:y:2023:i:18:p:13576-:d:1237559. 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.