Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99278
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dc.contributorSchool of Hotel and Tourism Managementen_US
dc.creatorSong, Hen_US
dc.creatorQiu, RTRen_US
dc.creatorPark, Jen_US
dc.date.accessioned2023-07-04T08:30:02Z-
dc.date.available2023-07-04T08:30:02Z-
dc.identifier.issn0160-7383en_US
dc.identifier.urihttp://hdl.handle.net/10397/99278-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2018 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Song, H., Qiu, R. T. R., & Park, J. (2019). A review of research on tourism demand forecasting: Launching the Annals of Tourism Research Curated Collection on tourism demand forecasting. Annals of Tourism Research, 75, 338-362 is available at https://doi.org/10.1016/j.annals.2018.12.001.en_US
dc.subjectArtificial intelligence modelen_US
dc.subjectEconometric modelen_US
dc.subjectForecast combinationen_US
dc.subjectJudgment forecastsen_US
dc.subjectTime seriesen_US
dc.subjectTourism demanden_US
dc.titleA review of research on tourism demand forecasting : launching the Annals of Tourism Research Curated Collection on tourism demand forecastingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage338en_US
dc.identifier.epage362en_US
dc.identifier.volume75en_US
dc.identifier.doi10.1016/j.annals.2018.12.001en_US
dcterms.abstractThis study reviews 211 key papers published between 1968 and 2018, for a better understanding of how the methods of tourism demand forecasting have evolved over time. The key findings, drawn from comparisons of method-performance profiles over time, are that forecasting models have grown more diversified, that these models have been combined, and that the accuracy of forecasting has been improved. Given the complexity of determining tourism demand, there is no single method that performs well for all situations, and the evolution of forecasting methods is still ongoing.en_US
dcterms.abstractThis article also launches the Annals of Tourism Research Curated Collection on tourism demand forecasting, which contains past and hot off the press work on the topic and will continue to grow as new articles on the topic appear in Annals.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAnnals of tourism research, Mar. 2019, v. 75, p. 338-362en_US
dcterms.isPartOfAnnals of tourism researchen_US
dcterms.issued2019-03-
dc.identifier.eissn1873-7722en_US
dc.description.validate202306 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera2156-
dc.identifier.SubFormID46809-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextMr. and Mrs. Chan Chak Fu Endowed Professorship Funden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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