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Effects of COVID-19 on rail passengers’ crowding perceptions

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  • Aghabayk, Kayvan
  • Esmailpour, Javad
  • Shiwakoti, Nirajan

Abstract

Understanding changes in travel behavior during the spread of pandemic diseases such as COVID-19 is important to develop a resilient transportation system. Since one of the most important ways to prevent the spread of this virus is to keep a safe distance from other people (i.e. social distancing), it has implications for the operations of public transportation as compared to other modes of transportation due to the confinement of a large number of passengers in enclosed space. This study investigated the effect of the spread of COVID-19 on crowding perception and crowding disutility in metro rail system of Tehran. Two surveys were conducted before and during the COVID-19. The stated preference data were analyzed by mixed logit models with the lognormal distribution. Results revealed that the value of crowding increased during the pandemic. Tracking the changes of crowding perception caused by COVID-19 shows that low comfort scores were observed at crowding levels where seats were taken, and the density of standees was high (i.e. not possible to maintain social distancing). During the outbreak of COVID-19, crowding has more disutility for rail passengers and the value of having a seat while traveling increased. Understanding passengers’ perceptions of crowding as examined in this study will assist transport operators, and planners maintain the critical functionality of public transport systems and manage risks of mass transportation during the pandemic and beyond.

Suggested Citation

  • Aghabayk, Kayvan & Esmailpour, Javad & Shiwakoti, Nirajan, 2021. "Effects of COVID-19 on rail passengers’ crowding perceptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 186-202.
    • Handle: RePEc:eee:transa:v:154:y:2021:i:c:p:186-202
    DOI: 10.1016/j.tra.2021.10.011
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    as
    1. Haywood, Luke & Koning, Martin & Monchambert, Guillaume, 2017. "Crowding in public transport: Who cares and why?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 215-227.
    2. Cox, Tom & Houdmont, Jonathan & Griffiths, Amanda, 2006. "Rail passenger crowding, stress, health and safety in Britain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 244-258, March.
    3. Allen, Jaime & Eboli, Laura & Forciniti, Carmen & Mazzulla, Gabriella & Ortúzar, Juan de Dios, 2019. "The role of critical incidents and involvement in transit satisfaction and loyalty," Transport Policy, Elsevier, vol. 75(C), pages 57-69.
    4. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
    5. Allen, Jaime & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2018. "Modelling service-specific and global transit satisfaction under travel and user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 509-528.
    6. Esmailpour, Javad & Aghabayk, Kayvan & Abrari Vajari, Mohammad & De Gruyter, Chris, 2020. "Importance – Performance Analysis (IPA) of bus service attributes: A case study in a developing country," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 129-150.
    7. 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.
    8. Tirachini, Alejandro & Hurtubia, Ricardo & Dekker, Thijs & Daziano, Ricardo A., 2017. "Estimation of crowding discomfort in public transport: Results from Santiago de Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 311-326.
    9. Hörcher, Daniel & Graham, Daniel J. & Anderson, Richard J., 2017. "Crowding cost estimation with large scale smart card and vehicle location data," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 105-125.
    10. Sanmay Shelat & Oded Cats & Sander van Cranenburgh, 2021. "Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands," Papers 2104.10973, arXiv.org, revised Apr 2022.
    11. Mark Wardman & Gerard Whelan, 2011. "Twenty Years of Rail Crowding Valuation Studies: Evidence and Lessons from British Experience," Transport Reviews, Taylor & Francis Journals, vol. 31(3), pages 379-398.
    12. Tirachini, Alejandro & Sun, Lijun & Erath, Alexander & Chakirov, Artem, 2016. "Valuation of sitting and standing in metro trains using revealed preferences," Transport Policy, Elsevier, vol. 47(C), pages 94-104.
    13. Prasanta K. Sahu & Gajanand Sharma & Anirban Guharoy, 2018. "Commuter travel cost estimation at different levels of crowding in a suburban rail system: a case study of Mumbai," Public Transport, Springer, vol. 10(3), pages 379-398, December.
    14. Mackie, P.J. & Jara-Díaz, S. & Fowkes, A.S., 0. "The value of travel time savings in evaluation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(2-3), pages 91-106, April.
    15. Sophia Rabe-Hesketh & Anders Skrondal, 2012. "Multilevel and Longitudinal Modeling Using Stata, 3rd Edition," Stata Press books, StataCorp LP, edition 3, number mimus2, March.
    16. Batarce, Marco & Muñoz, Juan Carlos & Ortúzar, Juan de Dios, 2016. "Valuing crowding in public transport: Implications for cost-benefit analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 358-378.
    17. Amirali Soltanpour & Mahmoud Mesbah & Meeghat Habibian, 2020. "Customer satisfaction in urban rail: a study on transferability of structural equation models," Public Transport, Springer, vol. 12(1), pages 123-146, March.
    18. Haywood, Luke & Koning, Martin, 2015. "The distribution of crowding costs in public transport: New evidence from Paris," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 182-201.
    19. Daly, Andrew & Hess, Stephane & de Jong, Gerard, 2012. "Calculating errors for measures derived from choice modelling estimates," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 333-341.
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