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dc.contributor.authorPereira, Luis Nobreen
dc.date.accessioned2018-10-26T05:33:27Zen
dc.date.available2018-10-26T05:33:27Zen
dc.date.issued2016-09en
dc.identifier.urihttp://hdl.handle.net/10919/85525en
dc.description.abstractRevenue management is a key tool for hotel managers’ decision-making process. Cutting-edge revenue management systems have been developed to support managers’ decisions and all have as an essential component an accurate forecasting module. This paper aims to introduce new time series forecasting models to be considered as a tool for forecasting daily hotel occupancies. These models were developed in a state space modeling framework which is capable of tackling seasonal complexities such as multiple seasonal periods and non-integer seasonality.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.publisherVirginia Techen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectComplex seasonal patternsen
dc.subjectForecastingen
dc.subjectForecast accuracyen
dc.subjectHotel demanden
dc.subjectRevenue managementen
dc.titleAn introduction to helpful forecasting methods for hotel revenue management [Summary]en
dc.typeSummaryen
dc.title.serialInternational Journal of Hospitality Managementen
dc.type.dcmitypeTexten


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Creative Commons Attribution 4.0 International
License: Creative Commons Attribution 4.0 International