IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v193y2025ics1366554524004320.html
   My bibliography  Save this article

Transport behavior and government interventions in pandemics: A hybrid explainable machine learning for road safety

Author

Listed:
  • Abdulrashid, Ismail
  • Zanjirani Farahani, Reza
  • Mammadov, Shamkhal
  • Khalafalla, Mohamed

Abstract

During a pandemic, transportation authorities and policymakers face significant challenges in identifying and validating new travel behavior and how it affects traffic crash patterns to develop effective safety strategies. A timely assessment of an emergency incident’s long-term impact and the development of appropriate response strategies are critical for managing future occurrences. This study investigates to answer these research questions (RQs):

Suggested Citation

  • Abdulrashid, Ismail & Zanjirani Farahani, Reza & Mammadov, Shamkhal & Khalafalla, Mohamed, 2025. "Transport behavior and government interventions in pandemics: A hybrid explainable machine learning for road safety," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:transe:v:193:y:2025:i:c:s1366554524004320
    DOI: 10.1016/j.tre.2024.103841
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554524004320
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2024.103841?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Song, Yuchen & Li, Dawei & Liu, Dongjie & Cao, Qi & Chen, Junlan & Ren, Gang & Tang, Xiaoyong, 2022. "Modeling activity-travel behavior under a dynamic discrete choice framework with unobserved heterogeneity," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    2. Shin Oblander & Daniel Minh McCarthy, 2023. "Frontiers: Estimating the Long-Term Impact of Major Events on Consumption Patterns: Evidence from COVID-19," Marketing Science, INFORMS, vol. 42(5), pages 839-852, September.
    3. Wu, Cheng-Lung & Law, Kristie, 2019. "Modelling the delay propagation effects of multiple resource connections in an airline network using a Bayesian network model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 62-77.
    4. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Zhang, Fangni, 2021. "Impact of entry restriction policies on international air transport connectivity during COVID-19 pandemic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    5. Shirgaokar, Manish & Reynard, Darcy & Collins, Damian, 2021. "Using twitter to investigate responses to street reallocation during COVID-19: Findings from the U.S. and Canada," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 300-312.
    6. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    7. Guo, Liquan & Jiang, Changmin & Hou, Weilu & Ng, Adolf K.Y. & Shi, Qin, 2024. "International multimodal transport connectivity assessment of multimodal transport from mainland China to Europe," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    8. Luca Barbarossa, 2020. "The Post Pandemic City: Challenges and Opportunities for a Non-Motorized Urban Environment. An Overview of Italian Cases," Sustainability, MDPI, vol. 12(17), pages 1-19, September.
    9. Chen, Bi Yu & Chen, Xuan-Yan & Chen, Hui-Ping & Huang, Yan-Bin & Jia, Tao & Lam, William H.K., 2024. "Understanding user equilibrium states of road networks: Evidence from two Chinese mega-cities using taxi trajectory mining," Transportation Research Part A: Policy and Practice, Elsevier, vol. 180(C).
    10. Rafiq, Rezwana & McNally, Michael G. & Sarwar Uddin, Yusuf & Ahmed, Tanjeeb, 2022. "Impact of working from home on activity-travel behavior during the COVID-19 Pandemic: An aggregate structural analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 35-54.
    11. Cankaya, Burak & Topuz, Kazim & Delen, Dursun & Glassman, Aaron, 2023. "Evidence-based managerial decision-making with machine learning: The case of Bayesian inference in aviation incidents," Omega, Elsevier, vol. 120(C).
    12. Melvin Wong & Bilal Farooq, 2019. "ResLogit: A residual neural network logit model for data-driven choice modelling," Papers 1912.10058, arXiv.org, revised Feb 2021.
    13. El Baz, Jamal & Ruel, Salomée & Jebli, Fedwa, 2023. "Harnessing supply chain resilience and social performance through safety and health practices in the COVID-19 era: An investigation of normative pressures and adoption timing's role," International Journal of Production Economics, Elsevier, vol. 264(C).
    14. Abdulrashid, Ismail & Zanjirani Farahani, Reza & Mammadov, Shamkhal & Khalafalla, Mohamed & Chiang, Wen-Chyuan, 2024. "Explainable artificial intelligence in transport Logistics: Risk analysis for road accidents," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    15. Hu, Songhua & Xiong, Chenfeng & Chen, Peng & Schonfeld, Paul, 2023. "Examining nonlinearity in population inflow estimation using big data: An empirical comparison of explainable machine learning models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    16. Borsati, Mattia & Fageda, Xavier, 2024. "Airline price responses in the face of demand shocks: European lessons from the COVID-19 pandemic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    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. Chen, Pengfang & Zhang, Xiaoqiang & Gao, Dongsheng, 2024. "Preference heterogeneity analysis on train choice behaviour of high-speed railway passengers: A case study in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 188(C).
    2. Li, Chi & Mao, Jianfeng & Li, Lingyi & Wu, Jingxuan & Zhang, Lianmin & Zhu, Jianyu & Pan, Zibin, 2024. "Flight delay propagation modeling: Data, Methods, and Future opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    3. 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).
    4. 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.
    5. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: Evidence from a choice experiment," Ecological Economics, Elsevier, vol. 194(C).
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Carlos Barros, 2012. "Sustainable Tourism in Inhambane-Mozambique," CEsA Working Papers 105, CEsA - Centre for African and Development Studies.
    13. 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.
    14. 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.
    15. 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.
    16. Jiang, Meizhi & Lu, Jing, 2020. "The analysis of maritime piracy occurred in Southeast Asia by using Bayesian network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 139(C).
    17. 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.
    18. Bernadeta Gołębiowska & Anna Bartczak & Mikołaj Czajkowski, 2020. "Energy Demand Management and Social Norms," Energies, MDPI, vol. 13(15), pages 1-20, July.
    19. 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.
    20. 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.

    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:eee:transe:v:193:y:2025:i:c:s1366554524004320. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    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.