IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i10p5885-d813912.html
   My bibliography  Save this article

Relationship between Vehicle Safety Ratings and Drivers’ Injury Severity in the Context of Gender Disparity

Author

Listed:
  • Wen Fu

    (School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China)

  • Jaeyoung Lee

    (School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China
    Department of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, FL 32816, USA)

Abstract

Previous studies have analyzed the relationship between vehicle safety ratings from impact tests and actual crash injury severity. Nevertheless, no study has investigated the relationship in the context of gender disparity. The main objective of this paper is to explore the validity of the 5-star ratings of the U.S. National Highway Traffic Safety Administration, which describes vehicles’ protectiveness, using actual traffic crash data by gender. Random parameter models are developed using 2015–2020 two-vehicle crash data from Maryland, United States. According to the data, over 90% of vehicles have 4–5 stars in overall, front-impact, and side-impact 5-star ratings. After controlling other factors, it is shown that woman drivers are more likely to be seriously injured in two-vehicle crashes than men drivers when using vehicles with the same 5-star safety ratings. Moreover, there is significant individual heterogeneity in the effect of vehicles with different 5-star safety ratings on driver injury severity. Using vehicles with more stars can reduce the risk of being seriously injured for most man drivers. However, the probability of woman drivers being seriously injured is reduced by approximately 5% on average by using vehicles with higher star ratings in the overall and front-impact 5-star rating, and individual heterogeneity shows a difference of nearly 50% in positive and negative effects. The overall and front-impact 5-star ratings of vehicles could not provide reasonable information as the safety performance of vehicles in traffic crashes for woman drivers. On the other hand, drivers’ residence, driving characteristics, crash types, and environmental characteristics are significantly associated with the injury severity. It is expected that the results from this study will contribute to guide a better vehicle safety design for both men and women.

Suggested Citation

  • Wen Fu & Jaeyoung Lee, 2022. "Relationship between Vehicle Safety Ratings and Drivers’ Injury Severity in the Context of Gender Disparity," IJERPH, MDPI, vol. 19(10), pages 1-14, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:10:p:5885-:d:813912
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/10/5885/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/10/5885/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    2. Cody R. Philips & Robert C. Garrett & Alan J. Tatro & Thomas J. Fisher, 2021. "An analysis of crash-safety ratings and the true assessment of injuries by vehicle," Computational Statistics, Springer, vol. 36(3), pages 1639-1660, September.
    3. Bose, D. & Segui-Gomez, M. & Crandall, J.R., 2011. "Vulnerability of female drivers involved in motor vehicle crashes: An analysis of US population at risk," American Journal of Public Health, American Public Health Association, vol. 101(12), pages 2368-2373.
    4. Zhu, S. & Layde, P.M. & Guse, C.E. & Laud, P.W. & Pintar, F. & Nirula, R. & Hargarten, S., 2006. "Obesity and risk for death due to motor vehicle crashes," American Journal of Public Health, American Public Health Association, vol. 96(4), pages 734-739.
    5. Tong Zeng, 2016. "Using Halton Sequences in Random Parameters Logit Models," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 5(1), pages 1-4.
    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. Czajkowski, Mikołaj & Zagórska, Katarzyna & Letki, Natalia & Tryjanowski, Piotr & Wąs, Adam, 2021. "Drivers of farmers’ willingness to adopt extensive farming practices in a globally important bird area," Land Use Policy, Elsevier, vol. 107(C).
    2. Venkatesh Shankar & Pablo Azar & Matthew Fuller, 2008. "—: A Multicategory Brand Equity Model and Its Application at Allstate," Marketing Science, INFORMS, vol. 27(4), pages 567-584, 07-08.
    3. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    4. Illichmann, R. & Abdulai, A., 2014. "Analysis of Consumer Preferences and Wilingness-To-Pay for Organic Food Products in Germany," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 49, March.
    5. Toşa, Cristian & Sato, Hitomi & Morikawa, Takayuki & Miwa, Tomio, 2018. "Commuting behavior in emerging urban areas: Findings of a revealed-preferences and stated-intentions survey in Cluj-Napoca, Romania," Journal of Transport Geography, Elsevier, vol. 68(C), pages 78-93.
    6. Scaccia, Luisa & Marcucci, Edoardo & Gatta, Valerio, 2023. "Prediction and confidence intervals of willingness-to-pay for mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 54-78.
    7. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    8. Meredith Fowlie, 2010. "Emissions Trading, Electricity Restructuring, and Investment in Pollution Abatement," American Economic Review, American Economic Association, vol. 100(3), pages 837-869, June.
    9. Ting Li & Robert J. Kauffman & Eric van Heck & Peter Vervest & Benedict G. C. Dellaert, 2014. "Consumer Informedness and Firm Information Strategy," Information Systems Research, INFORMS, vol. 25(2), pages 345-363, June.
    10. Carlos Barros, 2012. "Sustainable Tourism in Inhambane-Mozambique," CEsA Working Papers 105, CEsA - Centre for African and Development Studies.
    11. Lu, Xiao-Yun & Gosling, Geoffrey D. & Shladover, Steven E. & Xiong, Jing & Ceder, Avi, 2006. "Development of a Modeling Framework for Analyzing Improvements in Intermodal Connectivity at California Airports," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt586755r9, Institute of Transportation Studies, UC Berkeley.
    12. van Putten, Marloes & Lijesen, Mark & Özel, Tanju & Vink, Nancy & Wevers, Harm, 2014. "Valuing the preferences for micro-generation of renewables by househoulds," Energy, Elsevier, vol. 71(C), pages 596-604.
    13. Bernard Fortin & Nicolas Jacquemet & Bruce Shearer, 2008. "Policy Analysis in Health-Services Market: Accounting for Quality and Quantity," Annals of Economics and Statistics, GENES, issue 91-92, pages 293-319.
    14. Jürgen Meyerhoff & Ulf Liebe, 2009. "Status Quo Effect in Choice Experiments: Empirical Evidence on Attitudes and Choice Task Complexity," Land Economics, University of Wisconsin Press, vol. 85(3), pages 515-528.
    15. Bernadeta Gołębiowska & Anna Bartczak & Mikołaj Czajkowski, 2020. "Energy Demand Management and Social Norms," Energies, MDPI, vol. 13(15), pages 1-20, July.
    16. Nguyen, Thanh Cong & Le, Hoa Thu & Nguyen, Hang Dieu & Ngo, Mai Thanh & Nguyen, Hong Quang, 2021. "Examining ordering effects and strategic behaviour in a discrete choice experiment," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 394-413.
    17. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    18. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    19. Martin Falk & Eva Hagsten, 2018. "Winter Weather Anomalies and Individual Destination Choice," Sustainability, MDPI, vol. 10(8), pages 1-14, July.
    20. Hamed, Mohammad M. & Mohammed, Ali & Olabi, Abdul Ghani, 2023. "Renewable energy adoption decisions in Jordan's industrial sector: Statistical analysis with unobserved heterogeneity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(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:19:y:2022:i:10:p:5885-:d:813912. 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.