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Analyzing E-Bikers’ Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model

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  • Tao Wang

    (School of Architecture and Transportation, Guilin University of Electronic Technology, Jinji Road 1#, Guilin 541004, China)

  • Sihong Xie

    (School of Architecture and Transportation, Guilin University of Electronic Technology, Jinji Road 1#, Guilin 541004, China)

  • Xiaofei Ye

    (Faculty of Maritime and Transportation, Ningbo University, Fenghua Road 818#, Ningbo 315211, China)

  • Xingchen Yan

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Longpan Road 159#, Nanjing 210037, China)

  • Jun Chen

    (School of Transportation, Southeast University, Dongnandaxue Road 2#, Jiangning Development Zone, Nanjing 211189, China)

  • Wenyong Li

    (School of Architecture and Transportation, Guilin University of Electronic Technology, Jinji Road 1#, Guilin 541004, China)

Abstract

To identify and quantify the factors that influence the risky riding behaviors of electric bike riders, we designed an e-bike rider behavior questionnaire (ERBQ) and obtained 573 valid samples through tracking surveys and random surveys. An exploratory factor analysis was then conducted to extract four scales: riding confidence, safety attitude, risk perception, and risky riding behavior. Based on the exploratory factor analysis, a structural equation model (SEM) of electric bike riding behaviors was constructed to explore the intrinsic causal relationships among the variables that affect the risky e-bike riding behavior. The results show that the relationship between riding confidence and risky riding behavior is mediated by risk perception and safety attitudes. Safety attitude was found to be significantly associated with risky riding behaviors. Specifically, herd mentality is most closely related to safety attitudes, which means that those engaged in e-bike traffic management and safety education should pay special attention to riders’ psychological management and education. Risk perception has a direct path to risky riding behaviors. Specifically, stochastic evaluation and concern degree are significantly related to e-bike riders’ risk perception. The findings of this study provide an empirical basis for the creation of safety interventions for e-bike riders in China.

Suggested Citation

  • Tao Wang & Sihong Xie & Xiaofei Ye & Xingchen Yan & Jun Chen & Wenyong Li, 2020. "Analyzing E-Bikers’ Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model," IJERPH, MDPI, vol. 17(13), pages 1-18, July.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:13:p:4763-:d:379456
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    References listed on IDEAS

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    Cited by:

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    2. Jiayu Huang & Ziyi Song & Linlin Xie & Zeting Lin & Liping Li, 2023. "Analysis of Risky Riding Behavior Characteristics of the Related Road Traffic Injuries of Electric Bicycle Riders," IJERPH, MDPI, vol. 20(7), pages 1-12, March.
    3. Bichen Wang & Peng Jing & Chengxi Jiang, 2023. "Combining SEM, fsQCA and BNs to Explore E-Bike Riders’ Helmet Wearing Intentions under the Impact of Mandatory Policies: An Empirical Study in Zhenjiang," Sustainability, MDPI, vol. 15(24), pages 1-25, December.

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