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An empirical evaluation of different usage pattern between car-sharing battery electric vehicles and private ones

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  • Wang, Wanying
  • Zhang, Qiang
  • Peng, Zhanglin
  • Shao, Zhen
  • Li, Xuefang

Abstract

As a non-ownership business mode, a car-sharing service system has received an extensive popularization recently. Many related studies based on the theoretical and questionnaire analyses have confirmed the existence of differences in usage patterns between car-sharing users and private users. Nowadays, usage data provides a new way to analyze and understand the usage pattern of vehicles, which can improve user experience. To study the usage of car-sharing cars and private ones, namely, to study their usage patterns, this paper proposes an evaluation indicator system for usage pattern based on the battery electric vehicle (BEV) data. The evaluation indicator system is based on the state transition approach and describes the usage pattern of BEVs from three dimensions. The travel temporal and travel spatial dimensions describe the time and space characteristics of usage pattern. The decision-making dimension, as a cause of state transition at the micro level, describes the decision-making pattern according to a conceptual psychological model. Finally, an empirical study using the promotion is undertaken to explore differences in the performance of the two BEV types using the real-world usage data. Results show that the evaluation indicator system can identify the differences in usage pattern between car-sharing BEVs and private ones effectively and objectively from different perspectives.

Suggested Citation

  • Wang, Wanying & Zhang, Qiang & Peng, Zhanglin & Shao, Zhen & Li, Xuefang, 2020. "An empirical evaluation of different usage pattern between car-sharing battery electric vehicles and private ones," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 115-129.
    • Handle: RePEc:eee:transa:v:135:y:2020:i:c:p:115-129
    DOI: 10.1016/j.tra.2020.03.014
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    3. 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).
    4. Soltani, Ali & Allan, Andrew & Khalaj, Fahimeh & Pojani, Dorina & Mehdizadeh, Milad, 2021. "Ridesharing in Adelaide: Segmentation of users," Journal of Transport Geography, Elsevier, vol. 92(C).
    5. Ecer, Fatih, 2021. "A consolidated MCDM framework for performance assessment of battery electric vehicles based on ranking strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    6. Wael Alosaimi & Md Tarique Jamal Ansari & Abdullah Alharbi & Hashem Alyami & Saquib Ali & Alka Agrawal & Raees Ahmad Khan, 2021. "Toward a Unified Model Approach for Evaluating Different Electric Vehicles," Energies, MDPI, vol. 14(19), pages 1-19, September.

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