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Revealing the Varying Impact of Urban Built Environment on Online Car-Hailing Travel in Spatio-Temporal Dimension: An Exploratory Analysis in Chengdu, China

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  • Tian Li

    (School of Automotive and Traffic Engineering, Jiangsu University, Jiangsu 212013, China
    School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 264209, China)

  • Peng Jing

    (School of Automotive and Traffic Engineering, Jiangsu University, Jiangsu 212013, China)

  • Linchao Li

    (School of Transportation, Southeast University, Nanjing 210096, China)

  • Dazhi Sun

    (School of Automotive and Traffic Engineering, Jiangsu University, Jiangsu 212013, China
    School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 264209, China)

  • Wenbo Yan

    (School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 264209, China)

Abstract

Online car-hailing travel is an increasingly popular mode of urban transport. A fundamental understanding of the relationship between the urban built environment and online car-hailing travel is essential for developing the corresponding traffic strategy and addressing sustainable urban planning and design. However, the varying impact of the urban built environment on online car-hailing travel in the spatial dimension has not been sufficiently investigated. This paper aims to fill this gap by using geographically weighted regression (GWR) to check the spatial heterogeneity of the likely influence. The result shows that the GWR model is superior to the global model (OLS) from the perspective of goodness of fit. The study finds that the recreation and entertainment Point of Interest (POI) and the residential district POI are the most influential factors on night online car-hailing travel. Land-use mix is found to have a positive effect on online car-hailing travel, and online car-hailing services can be a complementary mode for public transport, especially in suburban areas.

Suggested Citation

  • Tian Li & Peng Jing & Linchao Li & Dazhi Sun & Wenbo Yan, 2019. "Revealing the Varying Impact of Urban Built Environment on Online Car-Hailing Travel in Spatio-Temporal Dimension: An Exploratory Analysis in Chengdu, China," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:5:p:1336-:d:210715
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    References listed on IDEAS

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    Cited by:

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    5. Yang, Xiong & Zhuge, Chengxiang & Shao, Chunfu & Huang, Yuantan & Hayse Chiwing G. Tang, Justin & Sun, Mingdong & Wang, Pinxi & Wang, Shiqi, 2022. "Characterizing mobility patterns of private electric vehicle users with trajectory data," Applied Energy, Elsevier, vol. 321(C).
    6. Rosita De Vincentis & Federico Karagulian & Carlo Liberto & Marialisa Nigro & Vincenza Rosati & Gaetano Valenti, 2022. "A Data-Driven Approach to Analyze Mobility Patterns and the Built Environment: Evidence from Brescia, Catania, and Salerno (Italy)," Sustainability, MDPI, vol. 14(21), pages 1-14, November.
    7. Gang Li & Ruining Zhang & Shujuan Guo & Junyi Zhang, 2022. "Analysis of Ride-Hailing Passenger Satisfaction and Life Satisfaction Based on a MIMIC Model," Sustainability, MDPI, vol. 14(17), pages 1-18, September.
    8. Jinjun Tang & Fan Gao & Fang Liu & Wenhui Zhang & Yong Qi, 2019. "Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM," Sustainability, MDPI, vol. 11(19), pages 1-19, October.

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