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Revenue management in Portuguese 4- and 5- star hotels

Bibliographic Details
Main Author: Carvalho, Miguel Coimbra Sandinha de
Publication Date: 2024
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/177699
Summary: This study aims to contribute to the Revenue Management literature, by investigating how it is applied in 4- and 5-star hotels in Portugal. It explores the importance of RM, which practices are most frequently used and regarded as more important, and their impact on hotel efficiency. In addition, it examines AI's expected future role in RM. Following a mixed method approach, the research highlights RM's importance to hotel performance and key practices like market analysis, dynamic pricing, and KPI analysis. It anticipates AI's significant future role in RM. These results offer valuable insights for revenue professionals in the hospitality sector.
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spelling Revenue management in Portuguese 4- and 5- star hotelsRevenue managementUpscaleHotelsPracticesPortugalEfficiencyArtificial intelligenceDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis study aims to contribute to the Revenue Management literature, by investigating how it is applied in 4- and 5-star hotels in Portugal. It explores the importance of RM, which practices are most frequently used and regarded as more important, and their impact on hotel efficiency. In addition, it examines AI's expected future role in RM. Following a mixed method approach, the research highlights RM's importance to hotel performance and key practices like market analysis, dynamic pricing, and KPI analysis. It anticipates AI's significant future role in RM. These results offer valuable insights for revenue professionals in the hospitality sector.Pimentel, DuarteRUNCarvalho, Miguel Coimbra Sandinha de2025-01-21T11:13:48Z2024-06-122024-05-162024-06-12T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/177699TID:203723929enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-01-27T01:37:20Zoai:run.unl.pt:10362/177699Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:41:36.123350Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Revenue management in Portuguese 4- and 5- star hotels
title Revenue management in Portuguese 4- and 5- star hotels
spellingShingle Revenue management in Portuguese 4- and 5- star hotels
Carvalho, Miguel Coimbra Sandinha de
Revenue management
Upscale
Hotels
Practices
Portugal
Efficiency
Artificial intelligence
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Revenue management in Portuguese 4- and 5- star hotels
title_full Revenue management in Portuguese 4- and 5- star hotels
title_fullStr Revenue management in Portuguese 4- and 5- star hotels
title_full_unstemmed Revenue management in Portuguese 4- and 5- star hotels
title_sort Revenue management in Portuguese 4- and 5- star hotels
author Carvalho, Miguel Coimbra Sandinha de
author_facet Carvalho, Miguel Coimbra Sandinha de
author_role author
dc.contributor.none.fl_str_mv Pimentel, Duarte
RUN
dc.contributor.author.fl_str_mv Carvalho, Miguel Coimbra Sandinha de
dc.subject.por.fl_str_mv Revenue management
Upscale
Hotels
Practices
Portugal
Efficiency
Artificial intelligence
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Revenue management
Upscale
Hotels
Practices
Portugal
Efficiency
Artificial intelligence
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This study aims to contribute to the Revenue Management literature, by investigating how it is applied in 4- and 5-star hotels in Portugal. It explores the importance of RM, which practices are most frequently used and regarded as more important, and their impact on hotel efficiency. In addition, it examines AI's expected future role in RM. Following a mixed method approach, the research highlights RM's importance to hotel performance and key practices like market analysis, dynamic pricing, and KPI analysis. It anticipates AI's significant future role in RM. These results offer valuable insights for revenue professionals in the hospitality sector.
publishDate 2024
dc.date.none.fl_str_mv 2024-06-12
2024-05-16
2024-06-12T00:00:00Z
2025-01-21T11:13:48Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/177699
TID:203723929
url http://hdl.handle.net/10362/177699
identifier_str_mv TID:203723929
dc.language.iso.fl_str_mv eng
language eng
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dc.format.none.fl_str_mv application/pdf
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instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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repository.mail.fl_str_mv info@rcaap.pt
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