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Estimating exponential scheduling preferences

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  • Hjorth, Katrine
  • Börjesson, Maria
  • Engelson, Leonid
  • Fosgerau, Mogens

Abstract

Different assumptions about travelers’ scheduling preferences yield different measures of the cost of travel time variability. Only few forms of scheduling preferences provide non-trivial measures which are additive over links in transport networks where link travel times are arbitrarily distributed independent random variables: Assuming smooth preferences, this holds only for specifications with a constant marginal utility of time at the origin and an exponential or affine marginal utility of time at the destination. We apply a generalized version of this model to stated preference data of car drivers’ route and mode choice under uncertain travel times. Our analysis exposes some important methodological issues related to complex non-linear scheduling models: One issue is identifying the point in time where the marginal utility of being at the destination becomes larger than the marginal utility of being at the origin. Another issue is that models with the exponential marginal utility formulation suffer from empirical identification problems. Though our results are not decisive, they partly support the constant-affine specification, in which the value of travel time variability is proportional to the variance of travel time.

Suggested Citation

  • Hjorth, Katrine & Börjesson, Maria & Engelson, Leonid & Fosgerau, Mogens, 2015. "Estimating exponential scheduling preferences," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 230-251.
    • Handle: RePEc:eee:transb:v:81:y:2015:i:p1:p:230-251
    DOI: 10.1016/j.trb.2015.03.014
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    6. Teppei Kato & Kenetsu Uchida & William H. K. Lam & Agachai Sumalee, 2021. "Estimation of the value of travel time and of travel time reliability for heterogeneous drivers in a road network," Transportation, Springer, vol. 48(4), pages 1639-1670, August.
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    11. Abegaz, Dereje & Hjorth, Katrine & Rich, Jeppe, 2017. "Testing the slope model of scheduling preferences on stated preference data," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 409-436.
    12. Engelson, Leonid & Fosgerau, Mogens, 2016. "The cost of travel time variability: Three measures with properties," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 555-564.
    13. Pudāne, Baiba, 2019. "Departure Time Choice and Bottleneck Congestion with Automated Vehicles: Role of On-board Activities," MPRA Paper 96328, University Library of Munich, Germany.
    14. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    15. Li, Chuan-Yao & Huang, Hai-Jun, 2018. "User equilibrium of a single-entry traffic corridor with continuous scheduling preference," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 21-38.
    16. Li, Zhi-Chun & Zhang, Liping, 2020. "The two-mode problem with bottleneck queuing and transit crowding: How should congestion be priced using tolls and fares?," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 46-76.
    17. Jinwon Kim & Jucheol Moon, 2022. "Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data," Working Papers 2201, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
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    19. Li, Chuanyao & Huang, Haijun, 2019. "Analysis of bathtub congestion with continuous scheduling preference," Research in Transportation Economics, Elsevier, vol. 75(C), pages 45-54.

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