Volume 39 Issue 3
Jun.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(3): 111-120
HU Cheng, HUANG Helai, LI Xintong, HAN Chunyang, JIANG Qianshan, YANG Qiushi. Travel Decision-making Behaviors of Urban Electric Bicycle Users Considering Psychological Latent Variables[J]. Journal of Transport Information and Safety, 2021, 39(3): 111-120. doi: 10.3963/j.jssn.1674-4861.2021.03.014
Citation: HU Cheng, HUANG Helai, LI Xintong, HAN Chunyang, JIANG Qianshan, YANG Qiushi. Travel Decision-making Behaviors of Urban Electric Bicycle Users Considering Psychological Latent Variables[J]. Journal of Transport Information and Safety, 2021, 39(3): 111-120. doi: 10.3963/j.jssn.1674-4861.2021.03.014
shu

Travel Decision-making Behaviors of Urban Electric Bicycle Users Considering Psychological Latent Variables

doi: 10.3963/j.jssn.1674-4861.2021.03.014
  • 1.

    School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China

  • 2.

    Smart Transport Key Laboratory of Hunan Province, Central South University, Changsha 410075, China

  • 3.

    Hunan Provincial Traffic Police Corps, Changsha 410199, China

  • Received Date: 2021-01-26
    Abstract
  • This paper aims to explore electric bicycle users'behavioral responses to different management policies of electric bicycles issued in 2018.A survey is conducted to collect socio-demographic characteristics, travel habits, psychological characteristics of electric bicycle users, and their decision-making against different policies.A multiple indicators and multiple causes model is constructed considering several latent variables such as policy acceptability to obtain the fitted value of the latent variables.Then a hybrid choice model taking the latent variables as explanatory variables is applied to analyze the impacts of social-demographic related variables, travel habit variables, and psychological latent variables on the travel decision of electric bicycle users.The results show that: ①The psychological characteristics of electric bicycle users significantly affect their travel decision-making, and travelers with higher policy acceptability tend to adopt positive behaviors.②Economic factors prompt the travelers to continue to use illegal electric bicycles or violate the policy.③Subsidies for scraping illegal electric bicycles can neutralize the impact ofeconomic factors on decision-making and can promote low-income families to purchase electric bicycles fitting the standard.④The implementation of the policy will promote the mode switching from electric-bicycle traffic to car traffic.

     

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