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Valuing Travel Time Variability within a Rank-Dependent Utility Framework and an Investigation of Unobserved Taste Heterogeneity

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  • David A. Hensher
  • Zheng Li

Abstract

Attitude towards risk is important to individual decision making. Rank-dependent utility theory is an appealing framework within which to study decision making under risk. This paper specifies Rank-Dependent Utility (RDU) models in the context of a stated choice experiment of commuter's risky route choice to (a) estimate willingness to pay for travel time, and (b) understand the risk attitudes of sampled respondents and their socioeconomic characteristics. We also allow for unobserved taste heterogeneity within an RDU framework using a mixed multinomial logit model. The findings provide a new set of empirical estimates of the value of travel time savings that allow for travel time variability combined into a single measure, referred to as the value of expected travel time savings. © 2012 LSE and the University of Bath

Suggested Citation

  • David A. Hensher & Zheng Li, 2012. "Valuing Travel Time Variability within a Rank-Dependent Utility Framework and an Investigation of Unobserved Taste Heterogeneity," Journal of Transport Economics and Policy, University of Bath, vol. 46(2), pages 293-312, May.
  • Handle: RePEc:tpe:jtecpo:v:46:y:2012:i:2:p:293-312
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    Cited by:

    1. Xiao, Yu & Fukuda, Daisuke, 2015. "On the cost of misperceived travel time variability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 96-112.
    2. Li, Hao & Tu, Huizhao & Hensher, David A., 2016. "Integrating the mean–variance and scheduling approaches to allow for schedule delay and trip time variability under uncertainty," Transportation Research Part A: Policy and Practice, Elsevier, vol. 89(C), pages 151-163.
    3. Zheng Li & David Hensher, 2013. "Behavioural implications of preferences, risk attitudes and beliefs in modelling risky travel choice with travel time variability," Transportation, Springer, vol. 40(3), pages 505-523, May.
    4. 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.
    5. Balbontin, Camila & Hensher, David A. & Collins, Andrew T., 2017. "Integrating attribute non-attendance and value learning with risk attitudes and perceptual conditioning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 172-191.
    6. Cerroni, Simone & Notaro, Sandra & Raffaelli, Roberta & Shaw, Douglass W., 2013. "The incorporation of subjective risks into choice experiments to test scenario adjustment," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149894, Italian Association of Agricultural and Applied Economics (AIEAA).
    7. Juan de Dios Ortúzar & Elisabetta Cherchi & Luis Ignacio Rizzi, 2014. "Transport research needs," Chapters,in: Handbook of Choice Modelling, chapter 29, pages 688-698 Edward Elgar Publishing.
    8. Wijayaratna, Kasun P. & Dixit, Vinayak V., 2016. "Impact of information on risk attitudes: Implications on valuation of reliability and information," Journal of choice modelling, Elsevier, vol. 20(C), pages 16-34.
    9. Li, Zheng & Hensher, David A. & Rose, John M., 2013. "Accommodating perceptual conditioning in the valuation of expected travel time savings for cars and public transport," Research in Transportation Economics, Elsevier, vol. 39(1), pages 270-276.

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