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Analysis of the potential demand for battery electric vehicle sharing: Mode share and spatiotemporal distribution

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  • Jin, Fanglei
  • Yao, Enjian
  • An, Kun

Abstract

Carsharing is considered one of the solutions to urban transport problems. As a new mode in the urban transport system in China, there are still initial questions of how carsharing will perform and what the impacts will be. Accordingly, this study considers battery electric vehicle sharing and investigates its potential demand, with Beijing as the case study. A nested logit model is established and calibrated to analyze mode choice behavior. Further, real trip data is used to estimate the potential demand for battery electric vehicle sharing. In addition, the temporal and spatial distribution of potential demand, the impact of battery electric vehicle sharing on the mode split, and the impact of pricing strategies are analyzed. The results show that an optimistic mode split of battery electric vehicle sharing is 4.23% when the average distance between travelers and stations is 0.5 km. The main source of potential demand is public transport. However, the substitution effect of battery electric vehicle sharing for private vehicles is weak. The potential trips are concentrated in the morning peak period, mainly starting in residential or integrative areas, and ending in commercial areas or green spaces. Commuting and long-distance trips are more sensitive to decreases in price, such that they are more likely to be completed as battery electric vehicle sharing trips. This price decrease could also increase the potential trip ratio during the evening peak period. These findings are useful to governments and operators for implementing policies such as station planning, relocation, and pricing strategies.

Suggested Citation

  • Jin, Fanglei & Yao, Enjian & An, Kun, 2020. "Analysis of the potential demand for battery electric vehicle sharing: Mode share and spatiotemporal distribution," Journal of Transport Geography, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:jotrge:v:82:y:2020:i:c:s0966692319305149
    DOI: 10.1016/j.jtrangeo.2019.102630
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    Cited by:

    1. Yong Wang & Jingxin Zhou & Yaoyao Sun & Xiuwen Wang & Jiayi Zhe & Haizhong Wang, 2022. "Electric Vehicle Charging Station Location-Routing Problem with Time Windows and Resource Sharing," Sustainability, MDPI, vol. 14(18), pages 1-31, September.
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    3. Jin, Fanglei & An, Kun & Yao, Enjian, 2020. "Mode choice analysis in urban transport with shared battery electric vehicles: A stated-preference case study in Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 95-108.

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