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An introduction to helpful forecasting methods for hotel revenue management

dc.contributor.authorPereira, Luis
dc.date.accessioned2017-04-07T15:56:06Z
dc.date.available2017-04-07T15:56:06Z
dc.date.issued2016-09
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 modelling framework which is capable of tackling seasonal complexities such as multiple seasonal periods and non-integer seasonality. An empirical study was carried out to illustrate how a practitioner may apply and compare the performance of different models when forecasting a hotel's daily occupancy. Results showed that the trigonometric model based on the new modelling framework generally outperformed the majority of the other models. These findings are potentially useful to the entire revenue management community facing the challenge of accurately forecasting a hotel's daily demand. (C) 2016 Elsevier Ltd. All rights reserved.
dc.identifier.doi10.1016/j.ijhm.2016.07.003
dc.identifier.issn0278-4319
dc.identifier.otherAUT: LMP01693;
dc.identifier.urihttp://hdl.handle.net/10400.1/9316
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relation.isbasedonWOS:000383526600002
dc.titleAn introduction to helpful forecasting methods for hotel revenue management
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FSOC%2F04020%2F2013/PT
oaire.citation.endPage23
oaire.citation.startPage13
oaire.citation.titleInternational Journal of Hospitality Management
oaire.citation.volume58
oaire.fundingStream5876
person.familyNameNobre Pereira
person.givenNameLuis
person.identifier.ciencia-id6114-E329-972E
person.identifier.orcid0000-0003-0917-7163
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccess
rcaap.typearticle
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relation.isAuthorOfPublication.latestForDiscovery090a6604-b604-414b-a8d2-c4dc731b7b51
relation.isProjectOfPublicationd929dde6-e7fa-4824-aba6-9f5e14a1e1be
relation.isProjectOfPublication.latestForDiscoveryd929dde6-e7fa-4824-aba6-9f5e14a1e1be

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