Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/74797
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dc.contributor.authorYu Guen_US
dc.contributor.authorAnthony Chenen_US
dc.contributor.authorSongyot Kitthamkesornen_US
dc.date.accessioned2022-10-16T06:49:51Z-
dc.date.available2022-10-16T06:49:51Z-
dc.date.issued2022-09-01en_US
dc.identifier.issn17555345en_US
dc.identifier.other2-s2.0-85135943045en_US
dc.identifier.other10.1016/j.jocm.2022.100373en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85135943045&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/74797-
dc.description.abstractThis study presents the properties of the weibit travel choice model (which was newly developed in 2008) and its applications in transportation research. The weibit model uses a Weibull-distributed random error term, relaxing the identically distributed assumption to derive the closed-form choice probability expression. The properties and advantages of the weibit model are graphically illustrated by comparisons with the commonly used logit model. The relationship between the weibit and logit models are discussed in the transportation context. The applications of weibit models to transportation research are exemplified based on the mode choice modeling in various transportation networks incorporating emerging technologies. The study reveals that weibit models have attractive features for evaluating and planning future transportation systems.en_US
dc.subjectDecision Sciencesen_US
dc.subjectMathematicsen_US
dc.titleWeibit choice models: Properties, mode choice application and graphical illustrationsen_US
dc.typeJournalen_US
article.title.sourcetitleJournal of Choice Modellingen_US
article.volume44en_US
article.stream.affiliationsHong Kong Polytechnic Universityen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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