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dc.contributor.authorChiou, Yu-Chiunen_US
dc.contributor.authorHsieh, Chih-Weien_US
dc.date.accessioned2020-03-02T03:23:25Z-
dc.date.available2020-03-02T03:23:25Z-
dc.date.issued2020-01-01en_US
dc.identifier.issn2324-9935en_US
dc.identifier.urihttp://dx.doi.org/10.1080/23249935.2020.1722288en_US
dc.identifier.urihttp://hdl.handle.net/11536/153717-
dc.description.abstractThis paper aimed to investigate contributing factors in length of stay at various types of tourist attractions based on cellular data. Accelerated failure time (AFT) models with three error terms distribution were compared: Weibull, log-normal, and log-logistic. The model with frailty was further used to accommodate unobserved heterogeneity. Potential factors related to attractions and trip characteristics are selected. A case study on Yi-Lan County, Taiwan, where has a variety of sightseeing spots attracting visitors, was conducted. The estimation results show that the Log-normal AFT model with frailty performs best. The key contributing factors in length of stay are city of origin, travel distance, entrance time, travel mode, and sequence of visited spots.en_US
dc.language.isoen_USen_US
dc.subjectLength of stayen_US
dc.subjecttourist attractionsen_US
dc.subjectcellular dataen_US
dc.subjectsurvival analysisen_US
dc.titleDeterminants of tourists' length of stay at various tourist attractions based on cellular dataen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/23249935.2020.1722288en_US
dc.identifier.journalTRANSPORTMETRICA A-TRANSPORT SCIENCEen_US
dc.citation.volume16en_US
dc.citation.issue3en_US
dc.citation.spage716en_US
dc.citation.epage733en_US
dc.contributor.department運輸與物流管理系 註:原交通所+運管所zh_TW
dc.contributor.departmentDepartment of Transportation and Logistics Managementen_US
dc.identifier.wosnumberWOS:000512838100001en_US
dc.citation.woscount0en_US
Appears in Collections:Articles