Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/134859
DC FieldValueLanguage
dc.contributor.authorCaballero Sanchez,Eleazaren_US
dc.contributor.authorSánchez Medina, Agustín Jesúsen_US
dc.date.accessioned2024-11-28T19:01:42Z-
dc.date.available2024-11-28T19:01:42Z-
dc.date.issued2024en_US
dc.identifier.issn2673-4591en_US
dc.identifier.urihttp://hdl.handle.net/10553/134859-
dc.description.abstractCancellations play a critical role in the lodging industry. Considering the time horizon, cancellations placed close to check-in have a significant impact on hoteliers, who must respond promptly for effective management. In recent years, the introduction of personal name records (PNR) has brought innovative approaches to this domain, but short-notice cancellation prediction is still underdeveloped. Using real PNR data with more than 10k reservations provided by a four-star hotel, this research aims to combine fuzzy clustering with tree decision techniques and random forest under R software version 4.3.3 to forecast cancellations placed close to the entry day, slightly improving the performance of individual techniques.en_US
dc.languageengen_US
dc.relation.ispartofEngineering Proceedingsen_US
dc.sourceEngineering Proceedings [ISSN 2673-4591], v. 68, n. 1, 43, (Julio 2024)en_US
dc.subject120601 Construcción de algoritmosen_US
dc.subject120304 Inteligencia artificialen_US
dc.subject531290 Economía sectorial: turismoen_US
dc.subject.otherHotel cancellation forecasten_US
dc.subject.otherDecision tree algorithmen_US
dc.subject.otherFuzzy C-means clusteringen_US
dc.subject.otherMachine learningen_US
dc.subject.otherRandom foresten_US
dc.titleDetecting Short-Notice Cancellation in Hotels with Machine Learningen_US
dc.typeinfo:eu-repo/semantics/workingPaperen_US
dc.typeWorking paperen_US
dc.identifier.doi10.3390/engproc2024068043en_US
dc.relation.volume68en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Documento de trabajoen_US
dc.description.numberofpages9en_US
dc.utils.revisionen_US
dc.date.coverdateJulio 2024en_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-TELen_US
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR IUCES: Centro de Innovación para la Empresa, el Turismo, la Internacionalización y la Sostenibilidad-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptGIR IUCES: Centro de Innovación para la Empresa, el Turismo, la Internacionalización y la Sostenibilidad-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Economía y Dirección de Empresas-
crisitem.author.orcid0000-0002-7569-3556-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.fullNameCaballero Sanchez,Eleazar-
crisitem.author.fullNameSánchez Medina, Agustín Jesús-
Appears in Collections:Documento de trabajo
Adobe PDF (254,57 kB)
Show simple item record

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.