A data-driven approach to measure restaurant performance by combining online reviews with historical sales data

Detalhes bibliográficos
Autor(a) principal: Fernandes, E.
Data de Publicação: 2021
Outros Autores: Moro, S., Cortez, P., Batista, F., Ribeiro, R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/21260
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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spelling A data-driven approach to measure restaurant performance by combining online reviews with historical sales dataRestaurant managementBusiness performanceCustomer relationship managementOnline reviewText miningData analyticsRestaurant 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.Elsevier2023-12-26T00:00:00Z2021-01-01T00:00:00Z20212021-01-13T19:03:17Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/21260eng0278-431910.1016/j.ijhm.2020.102830Fernandes, E.Moro, S.Cortez, P.Batista, F.Ribeiro, R.info: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:RCAAP2023-12-31T01:17:29Zoai:repositorio.iscte-iul.pt:10071/21260Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:13:53.012675Repositório 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 by combining online reviews with historical sales data
title A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
spellingShingle A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
Fernandes, E.
Restaurant management
Business performance
Customer relationship management
Online review
Text mining
Data analytics
title_short A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
title_full A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
title_fullStr A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
title_full_unstemmed A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
title_sort A data-driven approach to measure restaurant performance by combining online reviews with historical sales data
author Fernandes, E.
author_facet Fernandes, E.
Moro, S.
Cortez, P.
Batista, F.
Ribeiro, R.
author_role author
author2 Moro, S.
Cortez, P.
Batista, F.
Ribeiro, R.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Fernandes, E.
Moro, S.
Cortez, P.
Batista, F.
Ribeiro, R.
dc.subject.por.fl_str_mv Restaurant management
Business performance
Customer relationship management
Online review
Text mining
Data analytics
topic Restaurant management
Business performance
Customer relationship management
Online review
Text mining
Data analytics
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 2021-01-01T00:00:00Z
2021
2021-01-13T19:03:17Z
2023-12-26T00:00:00Z
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/10071/21260
url http://hdl.handle.net/10071/21260
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0278-4319
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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution 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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