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Analysis of the Multi-Scale Spatial Heterogeneity of Factors Influencing the Electric Bike-Sharing Travel Demand in Small and Medium-Sized Cities

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  • Xin Wang

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Zhiyuan Peng

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Xuefeng Li

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Mingyang Du

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Fangzheng Lyu

    (Department of Geography, Virginia Tech, Blacksburg, VA 24061, USA)

  • Jeon-Young Kang

    (Department of Geography, Kyung Hee University, Seoul 02447, Republic of Korea
    Department of Climate-Social Science Convergence, Kyung Hee University, Seoul 02447, Republic of Korea)

  • Kangjae Lee

    (Department of Convergence and Fusion System Engineering, Kyungpook National University, Sangju 37224, Republic of Korea)

  • Dong Liu

    (Division of Computational Social Science, School of Humanities and Social Science, The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), Longgang District, Shenzhen 518172, China)

Abstract

The spatial heterogeneity of the electric bike-sharing (EBS) travel demand in small and medium-sized cities is influenced by a combination of the built environment, socio-economic gradients, transportation accessibility, and residents’ travel behavior patterns, and is significantly different from the shared travel characteristics of developed cities. In order to explore the influencing mechanisms of the EBS travel demand under different travel distance scales in small and medium-sized cities, this paper utilizes multi-source data from Tongxiang, Zhejiang Province, including operational data of EBS and built environment data. This paper analyzes the impact of the built environment on the EBS travel demand and its spatial heterogeneity across various distance scales from a local perspective. The results demonstrate that the fit of the multiscale geographically weighted regression (MGWR) model is superior to that of the geographically weighted regression (GWR) and the ordinary least squares (OLS) model. The explanatory variables exhibit significant spatial heterogeneity in their influence on the demand for EBS trips across different distance scenarios. The density of primary roads demonstrates a positive correlation with EBS travel demand in the western urban core area, but it is negatively correlated with travel demand in the eastern urban core area. Accommodation services show a negative correlation with long-distance EBS travel demand in the urban core area and the northern city, but they are positively correlated with short-distance EBS travel demand in the urban core area. There is competition between long-distance EBS and public transportation in city centers. However, short-distance EBS and public transportation exhibit a complementary relationship in the urban periphery. The research findings are beneficial for gaining a deeper understanding of the patterns of change in the EBS travel demand and promoting the refined and sustainable development of shared transportation.

Suggested Citation

  • Xin Wang & Zhiyuan Peng & Xuefeng Li & Mingyang Du & Fangzheng Lyu & Jeon-Young Kang & Kangjae Lee & Dong Liu, 2025. "Analysis of the Multi-Scale Spatial Heterogeneity of Factors Influencing the Electric Bike-Sharing Travel Demand in Small and Medium-Sized Cities," Sustainability, MDPI, vol. 17(23), pages 1-24, November.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:23:p:10437-:d:1799813
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