A recommender system for Pingo Doce & Go Nova

Detalhes bibliográficos
Autor(a) principal: Bezerra, Miguel Ângelo Salgueiro
Data de Publicação: 2021
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/123162
Resumo: Using the Design Science framework, and acknowledging the success of recommenders in e-commerce settings, this paper proposes the design and implementation of a recommender in a physical retail store(Pingo Doce & Go Nova). It allows to assess if the recommender can influence customers’ decisions, increase sales, the number of unique products acquired, and understanding the customers. To develop it, the data was collected, curated, recommendation strategies were designed (loyalty, novelty, and related) and the customers were split into groups. The recommender will be deployed in the storeapp and, after, the results from the metrics will be analyzed.
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spelling A recommender system for Pingo Doce & Go NovaData sciencePhysical retailRecommenderDesign science research processDomínio/Área Científica::Ciências Sociais::Economia e GestãoUsing the Design Science framework, and acknowledging the success of recommenders in e-commerce settings, this paper proposes the design and implementation of a recommender in a physical retail store(Pingo Doce & Go Nova). It allows to assess if the recommender can influence customers’ decisions, increase sales, the number of unique products acquired, and understanding the customers. To develop it, the data was collected, curated, recommendation strategies were designed (loyalty, novelty, and related) and the customers were split into groups. The recommender will be deployed in the storeapp and, after, the results from the metrics will be analyzed.Han, QiweiTomás, RuiRUNBezerra, Miguel Ângelo Salgueiro2021-08-26T10:41:50Z2021-01-122021-01-042021-01-12T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/123162TID:202739864enginfo: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:RCAAP2024-03-11T05:04:34Zoai:run.unl.pt:10362/123162Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:44:58.150190Repositório 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 recommender system for Pingo Doce & Go Nova
title A recommender system for Pingo Doce & Go Nova
spellingShingle A recommender system for Pingo Doce & Go Nova
Bezerra, Miguel Ângelo Salgueiro
Data science
Physical retail
Recommender
Design science research process
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short A recommender system for Pingo Doce & Go Nova
title_full A recommender system for Pingo Doce & Go Nova
title_fullStr A recommender system for Pingo Doce & Go Nova
title_full_unstemmed A recommender system for Pingo Doce & Go Nova
title_sort A recommender system for Pingo Doce & Go Nova
author Bezerra, Miguel Ângelo Salgueiro
author_facet Bezerra, Miguel Ângelo Salgueiro
author_role author
dc.contributor.none.fl_str_mv Han, Qiwei
Tomás, Rui
RUN
dc.contributor.author.fl_str_mv Bezerra, Miguel Ângelo Salgueiro
dc.subject.por.fl_str_mv Data science
Physical retail
Recommender
Design science research process
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Data science
Physical retail
Recommender
Design science research process
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description Using the Design Science framework, and acknowledging the success of recommenders in e-commerce settings, this paper proposes the design and implementation of a recommender in a physical retail store(Pingo Doce & Go Nova). It allows to assess if the recommender can influence customers’ decisions, increase sales, the number of unique products acquired, and understanding the customers. To develop it, the data was collected, curated, recommendation strategies were designed (loyalty, novelty, and related) and the customers were split into groups. The recommender will be deployed in the storeapp and, after, the results from the metrics will be analyzed.
publishDate 2021
dc.date.none.fl_str_mv 2021-08-26T10:41:50Z
2021-01-12
2021-01-04
2021-01-12T00:00:00Z
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/10362/123162
TID:202739864
url http://hdl.handle.net/10362/123162
identifier_str_mv TID:202739864
dc.language.iso.fl_str_mv eng
language eng
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.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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