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Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands

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  • Stephane Hess
  • John Polak
  • Andrew Daly
  • Geoffrey Hyman

Abstract

Modelling the temporal response of travellers to transport policy interventions has rapidly emerged as a major issue in many practical transport planning studies and is recognised to hold particular challenges. The importance of congestion and its variation over the day, together with the emergence of time-dependent road user charging as a policy tool, emphasise the need to understand whether and how travellers will change the timing of their journeys. For practical planning studies, analysts face a major issue of relating temporal changes to other behavioural changes that are likely to result from policy or exogenous changes. In particular, the relative sensitivity of time and mode switching has been difficult to resolve. This paper describes a study undertaken to determine the relative sensitivity of mode and time of day choice to changes in travel times and costs and to investigate whether evidence exists of varying magnitudes of unobservable influences in time of day switching. The study draws on data from three related stated preference studies undertaken over the past decade in the United Kingdom and the Netherlands and uses error components logit models to investigate the patterns of substitution between mode and time of day alternatives. It is concluded that the magnitude of unobserved influences on time switching depends significantly on the magnitudes of the time switches considered. With time periods of the magnitude generally represented in practical modelling, i.e. peak periods of 2–3 hours, time switching is generally more sensitive in these data than mode switching. However, the context of the modelling and the extent to which relevant variables can be measured will strongly influence these results. Copyright Springer Science+Business Media B.V. 2007

Suggested Citation

  • Stephane Hess & John Polak & Andrew Daly & Geoffrey Hyman, 2007. "Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands," Transportation, Springer, vol. 34(2), pages 213-238, March.
  • Handle: RePEc:kap:transp:v:34:y:2007:i:2:p:213-238
    DOI: 10.1007/s11116-006-0011-7
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    References listed on IDEAS

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    Cited by:

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    4. Zannat, Khatun E. & Choudhury, Charisma F. & Hess, Stephane, 2024. "Modelling time-of-travel preferences capturing correlations between departure times and activity durations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).
    5. de Jong, Gerard & Kouwenhoven, Marco & Ruijs, Kim & van Houwe, Pieter & Borremans, Dana, 2016. "A time-period choice model for road freight transport in Flanders based on stated preference data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 20-31.
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    7. Thorhauge, Mikkel & Cherchi, Elisabetta & Rich, Jeppe, 2016. "How flexible is flexible? Accounting for the effect of rescheduling possibilities in choice of departure time for work trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 177-193.
    8. Richard Batley & J. Nicolás Ibá-ez, 2013. "Applied welfare economics with discrete choice models: implications of theory for empirical specification," Chapters, in: Stephane Hess & Andrew Daly (ed.), Choice Modelling, chapter 7, pages 144-171, Edward Elgar Publishing.
    9. Hess, Stephane & Daly, Andrew & Rohr, Charlene & Hyman, Geoff, 2007. "On the development of time period and mode choice models for use in large scale modelling forecasting systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 802-826, November.
    10. Kato, Hironori & Kaneko, Yuichiro & Soyama, Yoshihiko, 2014. "Economic benefits of urban rail projects that improve travel-time reliability: Evidence from Tokyo, Japan," Transport Policy, Elsevier, vol. 35(C), pages 202-210.
    11. Haustein, Sonja & Kroesen, Maarten, 2022. "Shifting to more sustainable mobility styles: A latent transition approach," Journal of Transport Geography, Elsevier, vol. 103(C).
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    13. Khan, Mubassira & Machemehl, Randy, 2017. "Commercial vehicles time of day choice behavior in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 68-83.
    14. Ghader, Sepehr & Carrion, Carlos & Zhang, Lei, 2019. "Autoregressive continuous logit: Formulation and application to time-of-day choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 240-257.
    15. 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).
    16. Badiola, Nicolás & Raveau, Sebastián & Galilea, Patricia, 2019. "Modelling preferences towards activities and their effect on departure time choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 39-51.
    17. Haiyan Zhu & Hongzhi Guan & Yan Han & Wanying Li, 2019. "A Study of Tourists’ Holiday Rush-Hour Avoidance Travel Behavior Considering Psychographic Segmentation," Sustainability, MDPI, vol. 11(13), pages 1-20, July.
    18. Bhatta, Bharat P. & Larsen, Odd I., 2011. "Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice," Transport Policy, Elsevier, vol. 18(2), pages 326-335, March.
    19. Xie, Litian & Olszewski, Piotr, 2011. "Modelling the effects of road pricing on traffic using ERP traffic data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(6), pages 512-522, July.
    20. Thorhauge, Mikkel & Kassahun, Habtamu Tilahun & Cherchi, Elisabetta & Haustein, Sonja, 2020. "Mobility needs, activity patterns and activity flexibility: How subjective and objective constraints influence mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 255-272.
    21. Yi-Shih Chung & Szu-Yu Tu, 2021. "Tri-reference-point hypothesis development for airport ground access behaviors," Transportation, Springer, vol. 48(5), pages 2159-2185, October.
    22. Thorhauge, Mikkel & Swait, Joffre & Cherchi, Elisabetta, 2020. "The habit-driven life: Accounting for inertia in departure time choices for commuting trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 272-289.
    23. Lemp, Jason D. & Kockelman, Kara M. & Damien, Paul, 2010. "The continuous cross-nested logit model: Formulation and application for departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 646-661, June.
    24. Bwambale, Andrew & Choudhury, Charisma F. & Hess, Stephane, 2019. "Modelling departure time choice using mobile phone data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 424-439.

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