A data-driven approach to measure restaurant performance combining online reviews and historical sales data
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/75121 |
Resumo: | Restaurant management requires customer responsiveness to deal with increasingly higher expectations and market competitiveness. This study proposes an approach to simplify the decision-making process of restaurant managers by combining both live social media customer feedback and historical sales data in a sales forecast model (based on TripAdvisor data and the Bass model). Our approach was validated with internal and external (i.e., online reviews) data gathered from six restaurants. The collected data was processed using data analytics for developing a dashboard that provides value for restauranteurs by taking advantage of online reviews and sales forecast. Such dashboard was evaluated by restaurant management experts, which provided positive feedback, highlighting in particular the time saved in the decision-making process. |
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A data-driven approach to measure restaurant performance combining online reviews and historical sales datarestaurant managementbusiness performancecustomer relationship managementonline reviewtext miningdata analyticsCiências Naturais::Ciências da Computação e da InformaçãoSocial SciencesIndústria, inovação e infraestruturasRestaurant management requires customer responsiveness to deal with increasingly higher expectations and market competitiveness. This study proposes an approach to simplify the decision-making process of restaurant managers by combining both live social media customer feedback and historical sales data in a sales forecast model (based on TripAdvisor data and the Bass model). Our approach was validated with internal and external (i.e., online reviews) data gathered from six restaurants. The collected data was processed using data analytics for developing a dashboard that provides value for restauranteurs by taking advantage of online reviews and sales forecast. Such dashboard was evaluated by restaurant management experts, which provided positive feedback, highlighting in particular the time saved in the decision-making process.This work was supported by the FCT - Fundacao para a Ciencia e Tecnologia, under Projects UIDB/04466/2020, UIDP/04466/2020, UID/CEC/00319/2019, and UIDB/50021/2020.ElsevierUniversidade do MinhoFernandes, ElisabethMoro, SérgioCortez, PauloBaptista, FernandoRibeiro, Ricardo2021-042021-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/75121engFernandes, E., Moro, S., Cortez, P., Batista, F., & Ribeiro, R. (2021). A data-driven approach to measure restaurant performance by combining online reviews with historical sales data. International Journal of Hospitality Management, 94, 102830. doi: https://doi.org/10.1016/j.ijhm.2020.1028300278-431910.1016/j.ijhm.2020.102830102830The original publication is available at https://doi.org/10.1016/j.ijhm.2020.102830info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:01:27Zoai:repositorium.sdum.uminho.pt:1822/75121Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:51:21.281444Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data |
title |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data |
spellingShingle |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data Fernandes, Elisabeth restaurant management business performance customer relationship management online review text mining data analytics Ciências Naturais::Ciências da Computação e da Informação Social Sciences Indústria, inovação e infraestruturas |
title_short |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data |
title_full |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data |
title_fullStr |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data |
title_full_unstemmed |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data |
title_sort |
A data-driven approach to measure restaurant performance combining online reviews and historical sales data |
author |
Fernandes, Elisabeth |
author_facet |
Fernandes, Elisabeth Moro, Sérgio Cortez, Paulo Baptista, Fernando Ribeiro, Ricardo |
author_role |
author |
author2 |
Moro, Sérgio Cortez, Paulo Baptista, Fernando Ribeiro, Ricardo |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Fernandes, Elisabeth Moro, Sérgio Cortez, Paulo Baptista, Fernando Ribeiro, Ricardo |
dc.subject.por.fl_str_mv |
restaurant management business performance customer relationship management online review text mining data analytics Ciências Naturais::Ciências da Computação e da Informação Social Sciences Indústria, inovação e infraestruturas |
topic |
restaurant management business performance customer relationship management online review text mining data analytics Ciências Naturais::Ciências da Computação e da Informação Social Sciences Indústria, inovação e infraestruturas |
description |
Restaurant management requires customer responsiveness to deal with increasingly higher expectations and market competitiveness. This study proposes an approach to simplify the decision-making process of restaurant managers by combining both live social media customer feedback and historical sales data in a sales forecast model (based on TripAdvisor data and the Bass model). Our approach was validated with internal and external (i.e., online reviews) data gathered from six restaurants. The collected data was processed using data analytics for developing a dashboard that provides value for restauranteurs by taking advantage of online reviews and sales forecast. Such dashboard was evaluated by restaurant management experts, which provided positive feedback, highlighting in particular the time saved in the decision-making process. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-04 2021-04-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/75121 |
url |
http://hdl.handle.net/1822/75121 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Fernandes, E., Moro, S., Cortez, P., Batista, F., & Ribeiro, R. (2021). A data-driven approach to measure restaurant performance by combining online reviews with historical sales data. International Journal of Hospitality Management, 94, 102830. doi: https://doi.org/10.1016/j.ijhm.2020.102830 0278-4319 10.1016/j.ijhm.2020.102830 102830 The original publication is available at https://doi.org/10.1016/j.ijhm.2020.102830 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132285128146944 |