Abstract
Scheduling preferences, derived under the assumption of expected utility maximization, can be used for measuring the value of travel time variability. As an alternative to the expected utility maximization, the rank dependent utility is chosen in this paper. Considering a flexible probability weighting for ranked outcomes, two frequently applied scheduling models are derived and estimated on a data set with specific travel time distributions. Optimistic respondents are observed. Allowing for heterogeneity of scheduling preferences improves the model performance significantly. We also found evidence for valuing excessive travel time, which is not included in the traditional scheduling model specifications.
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