Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104841
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dc.contributorSchool of Professional Education and Executive Development-
dc.contributorSchool of Hotel and Tourism Management-
dc.creatorZhang, Xen_US
dc.creatorSong, Hen_US
dc.date.accessioned2024-03-05T01:26:53Z-
dc.date.available2024-03-05T01:26:53Z-
dc.identifier.issn1099-2340en_US
dc.identifier.urihttp://hdl.handle.net/10397/104841-
dc.language.isoenen_US
dc.publisherJohn Wiley & Sonsen_US
dc.rightsCopyright © 2017 John Wiley & Sons, Ltd.en_US
dc.rightsThis is the peer reviewed version of the following article: Zhang, X, Song, H. An integrative framework for collaborative forecasting in tourism supply chains. Int J Tourism Res. 2018; 20(2): 158–171, which has been published in final form at https://doi.org/10.1002/jtr.2168. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.en_US
dc.subjectCollaborative forecastingen_US
dc.subjectForecastingen_US
dc.subjectForecasting support systemen_US
dc.subjectTourism demanden_US
dc.subjectTourism supply chainen_US
dc.titleAn integrative framework for collaborative forecasting in tourism supply chainsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage158en_US
dc.identifier.epage171en_US
dc.identifier.volume20en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1002/jtr.2168en_US
dcterms.abstractTourism practitioners must often rely on each other in a tourism supply chain (TSC). Demand forecasting plays a key role in shaping the activities of TSC practitioners. In the past 4 decades, researchers have developed many techniques for advanced tourism demand forecasting, but practitioners have had little interest in them. To bridge this gap, we examine the nature of the forecasting tasks of TSC practitioners in Hong Kong and propose a collaborative TSC forecasting framework that not only integrates tourism demand forecasting methods with practitioners' knowledge, but also facilitates information sharing between TSC practitioners to increase industry collaboration and improve forecasting performance.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInternational journal of tourism research, Mar.-Apr. 2018, v. 20, no. 2, p. 158-171en_US
dcterms.isPartOfInternational journal of tourism researchen_US
dcterms.issued2018-03-
dc.identifier.scopus2-s2.0-85035227889-
dc.identifier.eissn1522-1970en_US
dc.description.validate202401 bckw-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberSHTM-0663-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextCollege of Professional and Continuing Education, an affiliate of The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6801673-
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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