A commuter departure-time model based on cumulative prospect theory View Full Text


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Article Info

DATE

2018-04

AUTHORS

Guang Yang, Xinwang Liu

ABSTRACT

With a focus on planning of departure times during peak hours for commuters, an optimal arrival-time choice is derived using cumulative prospect theory. The model is able to explain the influence of behavioral characteristics on the choice of departure time. First, optimal solutions are derived explicitly for both early and late-arrival prospects. It is shown that the optimal solution is a function of a subjective measure, namely, the gain–loss ratio (GLR), indicating that the actual arrival time of a commuter depends on his or her attitude to the deviation between gains and losses. Some properties of the optimal solution and the GLR are discussed. These properties suggest that the more that the pleasure of gain exceeds the pain of loss, the greater the correlation between actual and preferred arrival times. Finally, a sensitivity analysis of the results is performed, and the use of the model is illustrated with a numerical example based on a skew-normal distribution. More... »

PAGES

285-307

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00186-017-0619-8

DOI

http://dx.doi.org/10.1007/s00186-017-0619-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092440700


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54 schema:description With a focus on planning of departure times during peak hours for commuters, an optimal arrival-time choice is derived using cumulative prospect theory. The model is able to explain the influence of behavioral characteristics on the choice of departure time. First, optimal solutions are derived explicitly for both early and late-arrival prospects. It is shown that the optimal solution is a function of a subjective measure, namely, the gain–loss ratio (GLR), indicating that the actual arrival time of a commuter depends on his or her attitude to the deviation between gains and losses. Some properties of the optimal solution and the GLR are discussed. These properties suggest that the more that the pleasure of gain exceeds the pain of loss, the greater the correlation between actual and preferred arrival times. Finally, a sensitivity analysis of the results is performed, and the use of the model is illustrated with a numerical example based on a skew-normal distribution.
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