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Effects of proactive and reactive health control measures on public transport preferences of passengers – A stated preference study during the COVID-19 pandemic

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  • Chen, Tiantian
  • Fu, Xiaowen
  • Hensher, David A.
  • Li, Zhi-Chun
  • Sze, N.N.

Abstract

The outbreak of COVID-19 has caused unprecedented disruptions to public transportation services, passengers' mode choice preferences, and their behavioral pattern. Recent studies have updated the systemic shift from shared travel to private mode due to the perceived higher health risk of shared mobility. However, findings from these studies may not be applicable to public transport-oriented cities with very low rate of private car ownership. In the long term when we arrive at a stabilized ‘New Normal’, the need to promote public transport is likely to be re-emphasized with high priority. This study presents insights into the factors affecting public transport (PT) preferences and potential modal shifts within various modes of PT when proactive and reactive health control measures are implemented. An online stated preference survey was conducted in Hong Kong, where public buses, public light buses, MTR, and taxis are the popular modes of public transport. The regret-based panel mixed multinomial logit model was applied in this study, aiming to capture individual’s regret aversion psychology in the context of the COVID-19 pandemic. The results of our random regret model suggest that travelers generally have lower regrets for the chosen mode when having passenger temperature screening, COVID tracing app, and more frequent disinfection, while seem to be unaware of the in-vehicle air quality. Interaction effects between health control measures and personal characteristics (e.g., age and risk attitudes) were also considered. Trip characteristics, including in-vehicle crowding level, fares, in-vehicle travel time, waiting time at a station, walking time, and trip purpose, were found to influence passengers' choices of travel modes. Policy simulations of possible changes in public transport modal preferences in the presence of various health control measures have also been undertaken. The findings suggest that overall health control measures are appreciated by passengers and do align with promotion of a return to public transport use. However, their effects are quite moderate and should be selectively used for different transport modes. Increasing service frequency can be a promising solution, which reduces crowding and waiting time of passengers using public transport modes, and reduces virus transmission risk. This study contributes to a better understanding of public acceptance and preference toward health control measures in public transport, and call for in-depth cost-benefit analysis in the related fields so that better response can be made in possible future public health crisis.

Suggested Citation

  • Chen, Tiantian & Fu, Xiaowen & Hensher, David A. & Li, Zhi-Chun & Sze, N.N., 2024. "Effects of proactive and reactive health control measures on public transport preferences of passengers – A stated preference study during the COVID-19 pandemic," Transport Policy, Elsevier, vol. 146(C), pages 175-192.
    • Handle: RePEc:eee:trapol:v:146:y:2024:i:c:p:175-192
    DOI: 10.1016/j.tranpol.2023.11.011
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    References listed on IDEAS

    as
    1. Beck, Matthew J. & Hensher, David A. & Nelson, John D., 2021. "Public transport trends in Australia during the COVID-19 pandemic: An investigation of the influence of bio-security concerns on trip behaviour," Journal of Transport Geography, Elsevier, vol. 96(C).
    2. Márquez, Luis & Alfonso A, Julieth V. & Poveda, Juan C., 2019. "In-vehicle crowding: Integrating tangible attributes, attitudes, and perceptions in a choice context between BRT and metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 452-465.
    3. Singh, Jyotsna & Homem de Almeida Correia, Gonçalo & van Wee, Bert & Barbour, Natalia, 2023. "Change in departure time for a train trip to avoid crowding during the COVID-19 pandemic: A latent class study in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    4. Li, Hao & Gao, Kun & Tu, Huizhao, 2017. "Variations in mode-specific valuations of travel time reliability and in-vehicle crowding: Implications for demand estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 250-263.
    5. Xingchuan Wang & Enjian Yao & Shasha Liu, 2018. "Travel Choice Analysis under Metro Emergency Context: Utility? Regret? Or Both?," Sustainability, MDPI, vol. 10(11), pages 1-15, October.
    6. Chang, Hung-Hao & Lee, Brian & Yang, Feng-An & Liou, Yu-You, 2021. "Does COVID-19 affect metro use in Taipei?," Journal of Transport Geography, Elsevier, vol. 91(C).
    7. Caspar Chorus & Michel Bierlaire, 2013. "An empirical comparison of travel choice models that capture preferences for compromise alternatives," Transportation, Springer, vol. 40(3), pages 549-562, May.
    8. Tsamboulas, Dimitrios A. & Nikoleris, Anastasios, 2008. "Passengers' willingness to pay for airport ground access time savings," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1274-1282, December.
    9. Zheng, Zuduo & Washington, Simon & Hyland, Paul & Sloan, Keith & Liu, Yulin, 2016. "Preference heterogeneity in mode choice based on a nationwide survey with a focus on urban rail," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 178-194.
    10. Varameth Vichiensan & Yoshitsugu Hayashi & Sudarat Kamnerdsap, 2021. "COVID-19 Countermeasures and Passengers’ Confidence of Urban Rail Travel in Bangkok," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    11. Devarasetty, Prem Chand & Burris, Mark & Douglass Shaw, W., 2012. "The value of travel time and reliability-evidence from a stated preference survey and actual usage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1227-1240.
    12. Salesi, Vinolia Kilinaivoni & Kan Tsui, Wai Hong & Fu, Xiaowen & Gilbey, Andrew, 2022. "Strategies for South Pacific Region to address future pandemics: Implications for the aviation and tourism sectors based on a systematic literature review (2010–2021)," Transport Policy, Elsevier, vol. 125(C), pages 107-126.
    13. Zhang, Junyi & Hayashi, Yoshitsugu & Frank, Lawrence D., 2021. "COVID-19 and transport: Findings from a world-wide expert survey," Transport Policy, Elsevier, vol. 103(C), pages 68-85.
    14. Chen, Tiantian & Fu, Xiaowen & Hensher, David A. & Li, Zhi-Chun & Sze, N.N., 2022. "Air travel choice, online meeting and passenger heterogeneity – An international study on travellers’ preference during a pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 439-453.
    15. Ioannou, Athina & Tussyadiah, Iis & Lu, Yang, 2020. "Privacy concerns and disclosure of biometric and behavioral data for travel," International Journal of Information Management, Elsevier, vol. 54(C).
    16. Qian, Xinwu & Zhang, Wenbo & Ukkusuri, Satish V. & Yang, Chao, 2017. "Optimal assignment and incentive design in the taxi group ride problem," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 208-226.
    17. Li, Zheng & Hensher, David A., 2011. "Crowding and public transport: A review of willingness to pay evidence and its relevance in project appraisal," Transport Policy, Elsevier, vol. 18(6), pages 880-887, November.
    18. Baobao Zhang & Sarah Kreps & Nina McMurry & R Miles McCain, 2020. "Americans’ perceptions of privacy and surveillance in the COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-16, December.
    19. Chen, Tiantian & Fu, Xiaowen & Hensher, David A. & Li, Zhi-Chun & Sze, N.N., 2022. "The effect of online meeting and health screening on business travel: A stated preference case study in Hong Kong," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    20. Eldeeb, Gamal & Mohamed, Moataz, 2020. "Quantifying preference heterogeneity in transit service desired quality using a latent class choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 119-133.
    21. Ho, Chinh Q. & Hensher, David A. & Wang, Shangbo, 2020. "Joint estimation of mode and time of day choice accounting for arrival time flexibility, travel time reliability and crowding on public transport," Journal of Transport Geography, Elsevier, vol. 87(C).
    22. Sun, Xiaoqian & Wandelt, Sebastian & Zhang, Anming, 2021. "Vaccination passports: Challenges for a future of air transportation," Transport Policy, Elsevier, vol. 110(C), pages 394-401.
    23. Zhang, Baobao & Kreps, Sarah E. & McMurry, Nina, 2020. "Americans' perceptions of privacy and surveillance in the COVID-19 Pandemic," OSF Preprints 9wz3y, Center for Open Science.
    24. Kirtonia, Sajeeb & Sun, Yanshuo, 2022. "Evaluating rail transit's comparative advantages in travel cost and time over taxi with open data in two U.S. cities," Transport Policy, Elsevier, vol. 115(C), pages 75-87.
    25. Chorus, Caspar G. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "A Random Regret-Minimization model of travel choice," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 1-18, January.
    26. Wang, Yineng & Lin, Xi & He, Fang & Li, Meng, 2022. "Designing transit-oriented multi-modal transportation systems considering travelers’ choices," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 292-327.
    27. Czerny, Achim I. & Fu, Xiaowen & Lei, Zheng & Oum, Tae H., 2021. "Post pandemic aviation market recovery: Experience and lessons from China," Journal of Air Transport Management, Elsevier, vol. 90(C).
    28. Wong, Stephen D & Chorus, Caspar G & Shaheen, Susan A & Walker, Joan L, 2020. "A Revealed Preference Methodology to Evaluate Regret Minimization with Challenging Choice Sets: A Wildfire Evacuation Case Study," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt2k12q9ph, Institute of Transportation Studies, UC Berkeley.
    29. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, September.
    30. Zhang, Baobao & Kreps, Sarah & McMurry, Nina & McCain, R. Miles, 2020. "Americans’ perceptions of privacy and surveillance in the COVID-19 pandemic," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(12), pages 1-1.
    31. Yang, Linchuan & Ao, Yibin & Ke, Jintao & Lu, Yi & Liang, Yuan, 2021. "To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults," Journal of Transport Geography, Elsevier, vol. 94(C).
    32. Nielsen, Otto Anker & Eltved, Morten & Anderson, Marie Karen & Prato, Carlo Giacomo, 2021. "Relevance of detailed transfer attributes in large-scale multimodal route choice models for metropolitan public transport passengers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 76-92.
    33. Das, Sanhita & Boruah, Alice & Banerjee, Arunabha & Raoniar, Rahul & Nama, Suresh & Maurya, Akhilesh Kumar, 2021. "Impact of COVID-19: A radical modal shift from public to private transport mode," Transport Policy, Elsevier, vol. 109(C), pages 1-11.
    34. Lavieri, Patrícia S. & Bhat, Chandra R., 2019. "Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 242-261.
    35. Ng, Kam To & Fu, Xiaowen & Hanaoka, Shinya & Oum, Tae Hoon, 2022. "Japanese aviation market performance during the COVID-19 pandemic - Analyzing airline yield and competition in the domestic market," Transport Policy, Elsevier, vol. 116(C), pages 237-247.
    36. Kamga, Camille & Eickemeyer, Penny, 2021. "Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada," Transport Policy, Elsevier, vol. 106(C), pages 25-36.
    37. Arentze, Theo A. & Molin, Eric J.E., 2013. "Travelers’ preferences in multimodal networks: Design and results of a comprehensive series of choice experiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 58(C), pages 15-28.
    38. Jin, Fanglei & An, Kun & Yao, Enjian, 2020. "Mode choice analysis in urban transport with shared battery electric vehicles: A stated-preference case study in Beijing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 95-108.
    39. Mulley, Corinne & Ho, Chinh & Ho, Loan & Hensher, David & Rose, John, 2018. "Will bus travellers walk further for a more frequent service? An international study using a stated preference approach," Transport Policy, Elsevier, vol. 69(C), pages 88-97.
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