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Exploring the Multiscale Relationship between the Built Environment and the Metro-Oriented Dockless Bike-Sharing Usage

Author

Listed:
  • Zhitao Li

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Yuzhen Shang

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Guanwei Zhao

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
    Institute of Land Resources and Coastal Zone, Guangzhou University, Guangzhou 510006, China)

  • Muzhuang Yang

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China
    Institute of Land Resources and Coastal Zone, Guangzhou University, Guangzhou 510006, China)

Abstract

Dockless bike-sharing systems have become one of the important transport methods for urban residents as they can effectively expand the metro’s service area. We applied the ordinary least square (OLS) model, the geographically weighted regression (GWR) model and the multiscale geographically weighted regression (MGWR) model to capture the spatial relationship between the urban built environment and the usage of bike-sharing connected to the metro. A case study in Beijing, China, was conducted. The empirical result demonstrates that the MGWR model can explain the varieties of spatial relationship more precisely than the OLS model and the GWR model. The result also shows that, among the proposed built environment factors, the integrated usage of bike-sharing and metro is mainly affected by the distance to central business district (CBD), the Hotels-Residences points of interest (POI) density, and the road density. It is noteworthy that the effect of population density on dockless bike-sharing usage is only significant at weekends. In addition, the effects of the built environment variables on dockless bike-sharing usage also vary across space. A common feature is that most of the built environment factors have a more obvious impact on the metro-oriented dockless bike-sharing usage in the eastern part of the study area. This finding can provide support for governments and urban planners to efficiently develop a bike-sharing-friendly built environment that promotes the integration of bike-sharing and metro.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:4:p:2323-:d:751943
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    References listed on IDEAS

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    Cited by:

    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. Lyu, Tao & Wang, Yuanqing & Ji, Shujuan & Feng, Tao & Wu, Zhouhao, 2023. "A multiscale spatial analysis of taxi ridership," Journal of Transport Geography, Elsevier, vol. 113(C).
    3. Suyang Yuan & Weiwei Dai & Yunhan Zhang & Jianqiang Yang, 2024. "Cycling Greenway Planning towards Sustainable Leisure and Recreation: Assessing Network Potential in the Built Environment of Chengdu," Sustainability, MDPI, vol. 16(14), pages 1-26, July.
    4. Qinglin Jia & Tao Zhang & Long Cheng & Gang Cheng & Minjie Jin, 2022. "The Impact of the Neighborhood Built Environment on the Walking Activity of Older Adults: A Multi-Scale Spatial Heterogeneity Analysis," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    5. Yancun Song & Kang Luo & Ziyi Shi & Long Zhang & Yonggang Shen, 2023. "Nonlinear Influence and Interaction Effect on the Imbalance of Metro-Oriented Dockless Bike-Sharing System," Sustainability, MDPI, vol. 16(1), pages 1-18, December.
    6. 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.

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