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What Kind of Travellers Are Using Carsharing in Beijing? A Study Based on Selective Ensemble Learning

Author

Listed:
  • Wei Luo

    (Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Yi Wang

    (Department of Civil Engineering, Tsinghua University, Beijing 100091, China)

  • Pengpeng Jiao

    (Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Zehao Wang

    (Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Pengfei Zhao

    (Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

Abstract

As a new urban travel mode, carsharing is significantly different from private cars, buses and other travel modes. Therefore, clarifying the typical characteristics of carsharing, such as individual users’ attributes, travel environment and travel behaviour, is conducive to accurately grasping the development of carsharing. In this study, a selective ensemble learning model is established to analyse typical travel characteristics of carsharing. Firstly, personal characteristics, environmental characteristics and behavioural characteristics were obtained through integrating order data, global positioning system data and station information. Then, based on a consolidated view of carsharing, different types of carsharing travel characteristics were distinguished using selective ensemble learning. Lastly, all kinds of carsharing travel are described in detail. It was identified through this research that carsharing travel can be divided into four kinds: long distance for leisure and entertainment, medium and short distances for business and commuting, a mixed category of medium and short distances for business and residence, and a mixed category of long distance for business and residence. This study can provide a theoretical reference and practical basis for precise planning and design and the scientific operation of carsharing.

Suggested Citation

  • Wei Luo & Yi Wang & Pengpeng Jiao & Zehao Wang & Pengfei Zhao, 2022. "What Kind of Travellers Are Using Carsharing in Beijing? A Study Based on Selective Ensemble Learning," Sustainability, MDPI, vol. 14(1), pages 1-24, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:1:p:540-:d:717759
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    References listed on IDEAS

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    1. Nancy Bocken & Alexandra Jonca & Karolina Södergren & Jenny Palm, 2020. "Emergence of Carsharing Business Models and Sustainability Impacts in Swedish Cities," Sustainability, MDPI, vol. 12(4), pages 1-23, February.
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    3. Cláudia A. Soares Machado & Nicolas Patrick Marie De Salles Hue & Fernando Tobal Berssaneti & José Alberto Quintanilha, 2018. "An Overview of Shared Mobility," Sustainability, MDPI, vol. 10(12), pages 1-21, November.
    4. Becker, Henrik & Balac, Milos & Ciari, Francesco & Axhausen, Kay W., 2020. "Assessing the welfare impacts of Shared Mobility and Mobility as a Service (MaaS)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 228-243.
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    Cited by:

    1. Andrzej Bąk & Elżbieta Nawrocka & Daria E. Jaremen, 2022. "“Sustainability” as a Motive for Choosing Shared-Mobility Services: The Case of Polish Consumers of Uber Services," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    2. Zu, Jinyan & Kong, Hui & Xu, Yang & Zhang, Xiaohu, 2024. "Carsharing in China: Impact of system and urban factors on usage and efficiency," Journal of Transport Geography, Elsevier, vol. 117(C).

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