IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2708-d1055524.html
   My bibliography  Save this article

A Comparison of Contributing Factors between Young and Old Riders of Motorcycle Crash Severity on Local Roads

Author

Listed:
  • Thanapong Champahom

    (Department of Management, Faculty of Business Administration, Rajamangala University of Technology Isan, Nakhon Ratchasima 30000, Thailand)

  • Chamroeun Se

    (School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Sajjakaj Jomnonkwao

    (School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Tassana Boonyoo

    (Traffic and Transport Development and Research Center (TDRC), King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand)

  • Vatanavongs Ratanavaraha

    (School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

Abstract

This study aims to identify the factors that influence the severity of motorcycle crashes on local roads, particularly given the high speeds often observed for motorcycles on these roads with low traffic volumes and numerous multi-leg intersections. Previous research has shown that a rider’s age can impact their speed behavior. To explore this issue, data on motorcycle crashes from 2015 to 2020 in Thailand—a middle-income developing country—were analyzed using a random parameter logit model with unobserved heterogeneity in means and variances, comparing young (<30-year-old) and older (>50-year-old) riders. The contributing factors were divided into four groups: driver, crash, environmental, and road factors. The transferability test yielded different results for the young rider and old rider models, indicating that it is appropriate to analyze these models separately. A constant value revealed that old riders were more likely to die in a crash than young riders. In terms of the random parameter, the local address and road surface variables were found to be significant in both models. The results of unobserved heterogeneity in means and variances identified significant variables in both models, including gender, exceeding the speed limit, lit roads, unlit roads, mobile phone use, and road surface. These findings were used to develop policy recommendations for reducing the severity of motorcycle crashes on local roads.

Suggested Citation

  • Thanapong Champahom & Chamroeun Se & Sajjakaj Jomnonkwao & Tassana Boonyoo & Vatanavongs Ratanavaraha, 2023. "A Comparison of Contributing Factors between Young and Old Riders of Motorcycle Crash Severity on Local Roads," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2708-:d:1055524
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2708/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2708/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yuan, Quan & Wang, Jueyu, 2021. "Goods movement, road safety, and spatial inequity: Evaluating freight-related crashes in low-income or minority neighborhoods," Journal of Transport Geography, Elsevier, vol. 96(C).
    2. Amjad Pervez & Jaeyoung Lee & Helai Huang & Xiaoqi Zhai, 2022. "What Factors Would Make Single-Vehicle Motorcycle Crashes Fatal? Empirical Evidence from Pakistan," IJERPH, MDPI, vol. 19(10), pages 1-14, May.
    3. Thanapol Promraksa & Thaned Satiennam & Wichuda Satiennam & Patiphan Kaewwichian & Nopadon Kronprasert, 2022. "Factors Influencing Stopping Locations of Motorcycle Riders on Signalized Urban Intersection Approaches," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    4. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    5. Muhammad Ijaz & Lan Liu & Yahya Almarhabi & Arshad Jamal & Sheikh Muhammad Usman & Muhammad Zahid, 2022. "Temporal Instability of Factors Affecting Injury Severity in Helmet-Wearing and Non-Helmet-Wearing Motorcycle Crashes: A Random Parameter Approach with Heterogeneity in Means and Variances," IJERPH, MDPI, vol. 19(17), pages 1-24, August.
    6. Thanapong Champahom & Sajjakaj Jomnonkwao & Chinnakrit Banyong & Watanya Nambulee & Ampol Karoonsoontawong & Vatanavongs Ratanavaraha, 2021. "Analysis of Crash Frequency and Crash Severity in Thailand: Hierarchical Structure Models Approach," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
    7. Ashraf Mahmud Rayed & Muhammad Atiq Ur Rehman Tariq & Mizanur Rahman & A. W. M. Ng & Md. Khairul Alam Nahid & Mahibuzzaman Mridul & Wazed Al Islam & Muhammad Mohiuddin, 2022. "An Analysis of Driving Behavior of Educated Youth in Bangladesh Considering Physiological, Cultural and Socioeconomic Variables," Sustainability, MDPI, vol. 14(9), pages 1-12, April.
    8. Heng-Yu Lin & Jian-Sing Li & Chih-Wei Pai & Wu-Chien Chien & Wen-Cheng Huang & Chin-Wang Hsu & Chia-Chieh Wu & Shih-Hsiang Yu & Wen-Ta Chiu & Carlos Lam, 2022. "Environmental Factors Associated with Severe Motorcycle Crash Injury in University Neighborhoods: A Multicenter Study in Taiwan," IJERPH, MDPI, vol. 19(16), pages 1-16, August.
    9. Ming-Heng Wang, 2022. "Investigating the Difference in Factors Contributing to the Likelihood of Motorcyclist Fatalities in Single Motorcycle and Multiple Vehicle Crashes," IJERPH, MDPI, vol. 19(14), pages 1-22, July.
    10. Carlos Lam & Chih-Wei Pai & Chia-Chang Chuang & Yu-Chun Yen & Chia-Chieh Wu & Shih-Hsiang Yu & Kuo-Sheng Hung & Wen-Ta Chiu, 2019. "Rider factors associated with severe injury after a light motorcycle crash: A multicentre study in an emerging economy setting," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-17, June.
    Full references (including those not matched with items on IDEAS)

    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. Thanapong Champahom & Chamroeun Se & Sajjakaj Jomnonkwao & Tassana Boonyoo & Amphaphorn Leelamanothum & Vatanavongs Ratanavaraha, 2023. "Temporal Instability of Motorcycle Crash Fatalities on Local Roadways: A Random Parameters Approach with Heterogeneity in Means and Variances," IJERPH, MDPI, vol. 20(5), pages 1-28, February.
    2. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    3. Nathan H. Miller, 2008. "Competition When Consumers Value Firm Scope," EAG Discussions Papers 200807, Department of Justice, Antitrust Division.
    4. Makoto Chikaraishi & Akimasa Fujiwara & Junyi Zhang & Kay Axhausen, 2011. "Identifying variations and co-variations in discrete choice models," Transportation, Springer, vol. 38(6), pages 993-1016, November.
    5. Ida, Takanori & Goto, Rei & Takahashi, Yuko & Nishimura, Shuzo, 2011. "Can economic-psychological parameters predict successful smoking cessation?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(3), pages 285-295, May.
    6. Els Breugelmans & Katia Campo & Els Gijsbrechts, 2007. "Shelf sequence and proximity effects on online grocery choices," Marketing Letters, Springer, vol. 18(1), pages 117-133, June.
    7. Partha Deb & Chenghui Li & Pravin K. Trivedi & David M. Zimmer, 2006. "The effect of managed care on use of health care services: results from two contemporaneous household surveys," Health Economics, John Wiley & Sons, Ltd., vol. 15(7), pages 743-760, July.
    8. Daniele Fabbri & Chiara Monfardini, 2016. "Opt Out or Top Up? Voluntary Health Care Insurance and the Public vs. Private Substitution," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 75-93, February.
    9. Anowar, Sabreena & Eluru, Naveen & Hatzopoulou, Marianne, 2017. "Quantifying the value of a clean ride: How far would you bicycle to avoid exposure to traffic-related air pollution?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 66-78.
    10. Falco, Paolo & Maloney, William F. & Rijkers, Bob & Sarrias, Mauricio, 2015. "Heterogeneity in subjective wellbeing: An application to occupational allocation in Africa," Journal of Economic Behavior & Organization, Elsevier, vol. 111(C), pages 137-153.
    11. Ge, Suqin & Macieira, João, 2020. "Unobserved Worker Quality and Inter-Industry Wage Differentials," GLO Discussion Paper Series 491, Global Labor Organization (GLO).
    12. Juan Carlos Martín & Concepción Román & Cira Mendoza, 2018. "Determinants for sun-and-beach self-catering accommodation selection," Tourism Economics, , vol. 24(3), pages 319-336, May.
    13. Martey, E., 2018. "Heterogeneous Demand for Quality Soybean in Northern Ghana," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277013, International Association of Agricultural Economists.
    14. Solomon Tarfasa & Roy Brouwer, 2013. "Estimation of the public benefits of urban water supply improvements in Ethiopia: a choice experiment," Applied Economics, Taylor & Francis Journals, vol. 45(9), pages 1099-1108, March.
    15. van der Kroon, Bianca & Brouwer, Roy & van Beukering, Pieter J.H., 2014. "The impact of the household decision environment on fuel choice behavior," Energy Economics, Elsevier, vol. 44(C), pages 236-247.
    16. Ke Wang & Xin Ye, 2021. "Development of alternative stochastic frontier models for estimating time-space prism vertices," Transportation, Springer, vol. 48(2), pages 773-807, April.
    17. Atella, Vincenzo & Deb, Partha, 2008. "Are primary care physicians, public and private sector specialists substitutes or complements? Evidence from a simultaneous equations model for count data," Journal of Health Economics, Elsevier, vol. 27(3), pages 770-785, May.
    18. Anoek Castelein & Dennis Fok & Richard Paap, 2020. "A multinomial and rank-ordered logit model with inter- and intra-individual heteroscedasticity," Tinbergen Institute Discussion Papers 20-069/III, Tinbergen Institute.
    19. Takanori Ida & Kazuhito Ogawa, 2012. "Inequality aversion, social discount, and time discount rates," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 39(5), pages 314-329, April.
    20. Peter Haan, 2005. "State Dependence and Female Labor Supply in Germany: The Extensive and the Intensive Margin," Discussion Papers of DIW Berlin 538, DIW Berlin, German Institute for Economic Research.

    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:jsusta:v:15:y:2023:i:3:p:2708-:d:1055524. 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.