IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i13p4763-d379456.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/13/4763/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/13/4763/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elliot Fishman & Christopher Cherry, 2016. "E-bikes in the Mainstream: Reviewing a Decade of Research," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 72-91, January.
    2. Wang, Jian & Peeta, Srinivas & Lu, Lili & Li, Tao, 2019. "Multiclass information flow propagation control under vehicle-to-vehicle communication environments," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 96-121.
    3. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
    4. Raut, Rakesh D. & Priyadarshinee, Pragati & Gardas, Bhaskar B. & Jha, Manoj Kumar, 2018. "Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 98-123.
    5. Xingchen Yan & Tao Wang & Xiaofei Ye & Jun Chen & Zhen Yang & Hua Bai, 2018. "Recommended Widths for Separated Bicycle Lanes Considering Abreast Riding and Overtaking," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    6. Wang, Jian & Peeta, Srinivas & He, Xiaozheng, 2019. "Multiclass traffic assignment model for mixed traffic flow of human-driven vehicles and connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 139-168.
    7. Changxi Ma & Dong Yang & Jibiao Zhou & Zhongxiang Feng & Quan Yuan, 2019. "Risk Riding Behaviors of Urban E-Bikes: A Literature Review," IJERPH, MDPI, vol. 16(13), pages 1-18, June.
    8. Wang, Jian & Gong, Siyuan & Peeta, Srinivas & Lu, Lili, 2019. "A real-time deployable model predictive control-based cooperative platooning approach for connected and autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 271-301.
    9. Yusep Suparman & Henk Folmer & Johan Oud, 2014. "Hedonic price models with omitted variables and measurement errors: a constrained autoregression–structural equation modeling approach with application to urban Indonesia," Journal of Geographical Systems, Springer, vol. 16(1), pages 49-70, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lining Liu & Xiaofei Ye & Tao Wang & Xingchen Yan & Jun Chen & Bin Ran, 2022. "Key Factors Analysis of Severity of Automobile to Two-Wheeler Traffic Accidents Based on Bayesian Network," IJERPH, MDPI, vol. 19(10), pages 1-17, May.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jin Xie & Xiaofei Ye & Zhongzhen Yang & Xingchen Yan & Lili Lu & Zhen Yang & Tao Wang, 2019. "Impact of Risk and Benefit on the Suppliers’ and Managers’ Intention of Shared Parking in Residential Areas," Sustainability, MDPI, vol. 12(1), pages 1-17, December.
    2. Wang, Jian & Lu, Lili & Peeta, Srinivas, 2022. "Real-time deployable and robust cooperative control strategy for a platoon of connected and autonomous vehicles by factoring uncertain vehicle dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 88-118.
    3. Jun Li & Jiachao Shen & Bicen Jia, 2021. "Exploring Intention to Use Shared Electric Bicycles by the Extended Theory of Planned Behavior," Sustainability, MDPI, vol. 13(8), pages 1-13, April.
    4. Xiaofei Ye & Yi Zhu & Tao Wang & Xingchen Yan & Jun Chen & Bin Ran, 2022. "Level of Service Model of the Non-Motorized Vehicle Crossing the Signalized Intersection Based on Riders’ Perception Data," IJERPH, MDPI, vol. 19(8), pages 1-17, April.
    5. Gu, Xiaoning & Chen, Chao & Feng, Tao & Yao, Baozhen, 2024. "A novel regional traffic control strategy for mixed traffic system with the construction of congestion warning communities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    6. Zhang, Fang & Lu, Jian & Hu, Xiaojian, 2022. "Integrated path controlling and subsidy scheme for mobility and environmental management in automated transportation networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    7. Jenkins, Michael & Lustosa, Lucio & Chia, Victoria & Wildish, Sarah & Tan, Maria & Hoornweg, Daniel & Lloyd, Meghann & Dogra, Shilpa, 2022. "What do we know about pedal assist E-bikes? A scoping review to inform future directions," Transport Policy, Elsevier, vol. 128(C), pages 25-37.
    8. Anat Meir, 2022. "Can Complete-Novice E-Bike Riders Be Trained to Detect Unmaterialized Traffic Hazards in the Urban Environment? An Exploratory Study," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    9. Dan Zhou & Mengying Chang & Guobin Gu & Xin Sun & Huizhi Xu & Wenhan Wang & Tao Wang, 2022. "Analysis of Risky Driving Behavior of Urban Electric Bicycle Drivers for Improving Safety," Sustainability, MDPI, vol. 14(3), pages 1-19, January.
    10. Wang, Jian & Peeta, Srinivas & Lu, Lili & Li, Tao, 2019. "Multiclass information flow propagation control under vehicle-to-vehicle communication environments," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 96-121.
    11. Yating Zhu & Xiaofei Ye & Jun Chen & Xingchen Yan & Tao Wang, 2020. "Impact of Cruising for Parking on Travel Time of Traffic Flow," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    12. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    13. Najaf, Pooya & Thill, Jean-Claude & Zhang, Wenjia & Fields, Milton Greg, 2018. "City-level urban form and traffic safety: A structural equation modeling analysis of direct and indirect effects," Journal of Transport Geography, Elsevier, vol. 69(C), pages 257-270.
    14. Wang, Jian & Zhou, Anye & Liu, Zhiyuan & Peeta, Srinivas, 2024. "Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).
    15. Ziwen Ling & Christopher R. Cherry & John H. MacArthur & Jonathan X. Weinert, 2017. "Differences of Cycling Experiences and Perceptions between E-Bike and Bicycle Users in the United States," Sustainability, MDPI, vol. 9(9), pages 1-18, September.
    16. Ding, Yu & Lu, Huapu, 2016. "Activity participation as a mediating variable to analyze the effect of land use on travel behavior: A structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 52(C), pages 23-28.
    17. Kurmankhojayev, Daniyar & Li, Guoyuan & Chen, Anthony, 2024. "Link criticality index: Refinement, framework extension, and a case study," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    18. Scheiner, Joachim, 2010. "Social inequalities in travel behaviour: trip distances in the context of residential self-selection and lifestyles," Journal of Transport Geography, Elsevier, vol. 18(6), pages 679-690.
    19. Jara-Díaz, Sergio & Rosales-Salas, Jorge, 2017. "Beyond transport time: A review of time use modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 209-230.
    20. Kroesen, Maarten & van Wee, Bert, 2022. "Understanding how accessibility influences health via active travel: Results from a structural equation model," Journal of Transport Geography, Elsevier, vol. 102(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:13:p:4763-:d:379456. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.