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Understanding Travel Time Expenditures Around the World: Exploring the Notion of a Travel Time Frontier

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  • Amlan Banerjee
  • Xin Ye
  • Ram Pendyala

Abstract

Travel behavior researchers have been intrigued by the amount of time that people allocate to travel in a day, i.e., the daily travel time expenditure, commonly referred to as a “travel time budget”. Explorations into the notion of a travel time budget have once again resurfaced in the context of activity-based and time use research in travel behavior modeling. This paper revisits the issue by developing the notion of a travel time frontier (TTF) that is distinct from the actual travel time expenditure or budget of an individual. The TTF is defined in this paper as an intrinsic maximum amount of time that people are willing to allocate for travel. It is treated as an unobserved frontier that influences the actual travel time expenditure measured in travel surveys. Using travel survey datasets from around the world (i.e., US, Switzerland and India), this paper sheds new light on daily travel time expenditures by modeling the unobserved TTF and comparing these frontiers across international contexts. The stochastic frontier modeling methodology is employed to model the unobserved TTF as a production frontier. Separate models are estimated for commuter and non-commuter samples to recognize the differing constraints between these market segments. Comparisons across the international contexts show considerable differences in average unobserved TTF values. Copyright Springer Science+Business Media B.V. 2007

Suggested Citation

  • Amlan Banerjee & Xin Ye & Ram Pendyala, 2007. "Understanding Travel Time Expenditures Around the World: Exploring the Notion of a Travel Time Frontier," Transportation, Springer, vol. 34(1), pages 51-65, January.
  • Handle: RePEc:kap:transp:v:34:y:2007:i:1:p:51-65
    DOI: 10.1007/s11116-006-0004-6
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    References listed on IDEAS

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    Cited by:

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    10. Peter R. Stopher & Asif Ahmed & Wen Liu, 2017. "Travel time budgets: new evidence from multi-year, multi-day data," Transportation, Springer, vol. 44(5), pages 1069-1082, September.
    11. Manoj, M. & Verma, Ashish, 2015. "Activity–travel behaviour of non-workers from Bangalore City in India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 400-424.
    12. Choudhury, Charisma F. & Ayaz, Sayeeda Bint, 2015. "Why live far? — Insights from modeling residential location choice in Bangladesh," Journal of Transport Geography, Elsevier, vol. 48(C), pages 1-9.
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    14. Pinjari, Abdul Rawoof & Augustin, Bertho & Sivaraman, Vijayaraghavan & Faghih Imani, Ahmadreza & Eluru, Naveen & Pendyala, Ram M., 2016. "Stochastic frontier estimation of budgets for Kuhn–Tucker demand systems: Application to activity time-use analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 117-133.
    15. Shirgaokar, Manish, 2019. "Operationalizing gendered transportation preferences: A psychological framework incorporating time constraints and risk aversion," Transport Policy, Elsevier, vol. 75(C), pages 10-18.
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