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On the other half of the story: allowing for discrete penalties for excessive travel times in scheduling models

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Abstract

In this paper, we introduce a discrete penalty for excessive travel times into scheduling models whose maximal expected utilities have attractive theoretical features of linearity in standard deviation or variance. The extended models maintain the properties of linearity, and its maximal expected utility depends on the shape of the travel time distribution. The value of travel time and its variability could be measured indirectly by the scheduling preferences. The results from empirical data reveal that the extended models, with such a discrete penalty, provide a highly significant better goodness of fit to the data. Furthermore, introducing the penalty for excessive travel time has a strong effect on the estimates of the other scheduling parameters, thus affecting the valuations of travel time. Our findings indicate that, apart from the mean and standard deviation (or variance), individuals value other characteristics of travel time distribution, in particular the probability of excessive travel time.

Suggested Citation

  • Wang, Qian & Sundberg, Marcus & Karlström, Anders, 2013. "On the other half of the story: allowing for discrete penalties for excessive travel times in scheduling models," Working papers in Transport Economics 2013:15, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    • Handle: RePEc:hhs:ctswps:2013_015
    Note: This paper is presented on internal and external seminars, and presented at the annual conference of the International Association of transportation Economics (ITEA Kuhmo Nectar), in Berlin June 2012.
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    References listed on IDEAS

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    More about this item

    Keywords

    Scheduling preferences; Travel time variability; Asymmetric travel time distribution; Excessive travel time;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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