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[journal article]

dc.contributor.authorZhang, Yishoude
dc.contributor.authorLi, Gangde
dc.contributor.authorMuskat, Birgitde
dc.contributor.authorVu, Quan Huyde
dc.contributor.authorLaw, Robde
dc.date.accessioned2021-11-03T09:08:07Z
dc.date.available2021-11-03T09:08:07Z
dc.date.issued2021de
dc.identifier.issn0160-7383de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/75518
dc.description.abstractAs tourism researchers continue to search for solutions to determine the best possible forecasting performance, it is important to understand the maximum predictivity achieved by models, as well as how various data characteristics influence the maximum predictivity. Drawing on information theory, the predictivity of tourism demand data is quantitatively evaluated and beneficial for improving the performance of tourism demand forecasting. Empirical results from Hong Kong tourism demand data show that 1) the predictivity could largely help the researchers estimate the best possible forecasting performance and understand the influence of various data characteristics on the forecasting performance.; 2) the predictivity can be used to assess the short effect of external shock - such as SARS over tourism demand forecasting.de
dc.languageende
dc.subject.ddcSozialwissenschaften, Soziologiede
dc.subject.ddcSocial sciences, sociology, anthropologyen
dc.subject.otherData characteristics; Entropy; Predictivity; Tourism demand forecastingde
dc.titlePredictivity of tourism demand datade
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalAnnals of Tourism Research
dc.publisher.countryNLDde
dc.source.issue89de
dc.subject.classozFreizeitforschung, Freizeitsoziologiede
dc.subject.classozLeisure Researchen
dc.subject.thesozTourismusde
dc.subject.thesoztourismen
dc.subject.thesozNachfragede
dc.subject.thesozdemanden
dc.subject.thesozPrognosede
dc.subject.thesozprognosisen
dc.subject.thesozDatengewinnungde
dc.subject.thesozdata captureen
dc.subject.thesozDatenqualitätde
dc.subject.thesozdata qualityen
dc.identifier.urnurn:nbn:de:0168-ssoar-75518-2
dc.rights.licenceCreative Commons - Namensnennung 1.0de
dc.rights.licenceCreative Commons - Attribution 1.0en
internal.statusformal und inhaltlich fertig erschlossende
internal.identifier.thesoz10044305
internal.identifier.thesoz10036309
internal.identifier.thesoz10036432
internal.identifier.thesoz10040547
internal.identifier.thesoz10055811
dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
internal.identifier.classoz20400
internal.identifier.journal2217
internal.identifier.document32
internal.identifier.ddc300
dc.identifier.doihttps://doi.org/10.1016/j.annals.2021.103234de
dc.description.pubstatusPreprintde
dc.description.pubstatusPreprinten
internal.identifier.licence13
internal.identifier.pubstatus3
internal.identifier.review1
dc.subject.classhort20400de
dc.subject.classhort10100de
dc.subject.classhort10900de
internal.pdf.wellformedtrue
internal.pdf.encryptedfalse


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