2014
DOI: 10.1016/j.trb.2014.03.001
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Coarse tolling with heterogeneous preferences

Abstract: Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in… Show more

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Cited by 38 publications
(6 citation statements)
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“…The average values were chosen in the following way. The value of time for long distance travellers in the California State Route 91 ranks between 7.09 and 29.42 $/h (Small et al 2005) and the high variability in the results was explained by the kind of survey conducted, i.e. stated preferences or revealed preferences.…”
Section: Case Studymentioning
confidence: 99%
“…The average values were chosen in the following way. The value of time for long distance travellers in the California State Route 91 ranks between 7.09 and 29.42 $/h (Small et al 2005) and the high variability in the results was explained by the kind of survey conducted, i.e. stated preferences or revealed preferences.…”
Section: Case Studymentioning
confidence: 99%
“…Furthermore, Vincent and van den Berg [15] investigated the welfare distribution effects among heterogeneous commuters after the implementation of a single-step toll scheme. This study analyzed and compared three queuing pricing models: the ADL model, the Laih model, and the Breaking model.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Now the authors will evaluate the capability of the proposed tradable credit scheme to maintain the queue length requirement under traveler heterogeneity in scheduling parameters. Although it is desirable to conduct such analysis under a general heterogeneity in which travelers may have any value of α, β, and γ, for tractability the authors have limited their attention to two well-known types of user heterogeneity in the literature (26,27): proportional heterogeneity and γ heterogeneity. The former represents the situation in which all scheduling parameters may vary among travelers but their ratios are assumed to be fixed, whereas the latter casts the situation in which only the consequence of late arrival is different among the travelers (i.e., the travelers have the same α and β but different γ).…”
Section: Evaluation Of Tradable Credit Scheme With User Heterogeneitymentioning
confidence: 99%