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Empirical Modeling Analysis of Potential Commute Demand for Carsharing in Shanghai, China

Author

Listed:
  • Qian Duan

    (Key Laboratory of Road and Traffic Engineering of Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China)

  • Xin Ye

    (Key Laboratory of Road and Traffic Engineering of Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China)

  • Jian Li

    (Key Laboratory of Road and Traffic Engineering of Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China)

  • Ke Wang

    (Key Laboratory of Road and Traffic Engineering of Ministry of Education, College of Transportation Engineering, Tongji University, Shanghai 201804, China)

Abstract

Carsharing is an emerging commute mode in China, which may produce social and environmental benefits. This paper aims to develop a commute mode choice model to explore influential factors and quantify their impacts on the potential demand for carsharing in Shanghai. The sample data were obtained from a revealed preference (RP) and stated preference (SP) survey and integrated with level-of-service attributes from road and transit networks. The RP survey collected commuters’ trip information and socioeconomic and demographic characteristics. In the SP survey, four hypothetical scenarios were designed based on carsharing’s unit price to collect commuters’ willingness to shift to carsharing. Data fusion method was applied to fuse RP and SP models. The joint model identified the target group of choosing carsharing with certain socioeconomic and demographic attributes, such as gender, age, income, household member, household vehicle ownership, and so on. It also indicates that the value of time (VOT) for carsharing is 35.56 RMB Yuan (5.08 US Dollar)/h. The elasticity and marginal effect analysis show that the direct elasticity of carsharing’s fare on its potential demand is −0.660, while the commuters, who have a more urgent plan on car purchase or are more familiar with the carsharing service, have much higher probabilities to choose carsharing as their commute modes. The developed model is expected to be applied to the urban travel demand model, providing references for the formulation of carsharing operation scheme and government policy.

Suggested Citation

  • Qian Duan & Xin Ye & Jian Li & Ke Wang, 2020. "Empirical Modeling Analysis of Potential Commute Demand for Carsharing in Shanghai, China," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:620-:d:308766
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    References listed on IDEAS

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    2. Fan Gao & Jinjun Tang & Zhitao Li, 2022. "Effects of spatial units and travel modes on urban commuting demand modeling," Transportation, Springer, vol. 49(6), pages 1549-1575, December.

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