Exploring fish purchasing behaviour using data analytics

Detalhes bibliográficos
Autor(a) principal: Rodrigo Teodoro Passos
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/121388
Resumo: In the last decades there have been significant changes in the retail sector resulting from globalization, the increased competitiveness and transformation on consumer's purchasing behaviour. This paradigm shift also applies to the fish sector, that has been capturing the interest of researchers internationally for political and economic reasons. Taking this competitive environment into account, which values the quality and the service given to the customer based on acceptable costs, it is necessary to adopt customer focused strategies. This thesis is integrated in the ValorMar's project, which was born from the commitment of a broad spectrum of entities, from companies to research centers, positioned by the relevance of the sea economy in the fishery value chain. Thus, this dissertation will try to understand critical relations for the decision making of customers when buying fresh fish.For this, transactional data and data mining techniques appropriate to the problem will be used. The methodology proposed by this thesis aims not only to identify customers using clustering techniques, but also to analyze the market basket of a fresh fish customer. These data analyzis will show that the knowledge extraction from large databases allows to improve the companies strategic decisions and their relationship with customers.
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spelling Exploring fish purchasing behaviour using data analyticsEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringIn the last decades there have been significant changes in the retail sector resulting from globalization, the increased competitiveness and transformation on consumer's purchasing behaviour. This paradigm shift also applies to the fish sector, that has been capturing the interest of researchers internationally for political and economic reasons. Taking this competitive environment into account, which values the quality and the service given to the customer based on acceptable costs, it is necessary to adopt customer focused strategies. This thesis is integrated in the ValorMar's project, which was born from the commitment of a broad spectrum of entities, from companies to research centers, positioned by the relevance of the sea economy in the fishery value chain. Thus, this dissertation will try to understand critical relations for the decision making of customers when buying fresh fish.For this, transactional data and data mining techniques appropriate to the problem will be used. The methodology proposed by this thesis aims not only to identify customers using clustering techniques, but also to analyze the market basket of a fresh fish customer. These data analyzis will show that the knowledge extraction from large databases allows to improve the companies strategic decisions and their relationship with customers.2019-07-112019-07-11T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/121388TID:202397432engRodrigo Teodoro Passosinfo: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:RCAAP2023-11-29T14:46:43Zoai:repositorio-aberto.up.pt:10216/121388Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:08:15.575654Repositório 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 Exploring fish purchasing behaviour using data analytics
title Exploring fish purchasing behaviour using data analytics
spellingShingle Exploring fish purchasing behaviour using data analytics
Rodrigo Teodoro Passos
Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
title_short Exploring fish purchasing behaviour using data analytics
title_full Exploring fish purchasing behaviour using data analytics
title_fullStr Exploring fish purchasing behaviour using data analytics
title_full_unstemmed Exploring fish purchasing behaviour using data analytics
title_sort Exploring fish purchasing behaviour using data analytics
author Rodrigo Teodoro Passos
author_facet Rodrigo Teodoro Passos
author_role author
dc.contributor.author.fl_str_mv Rodrigo Teodoro Passos
dc.subject.por.fl_str_mv Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
description In the last decades there have been significant changes in the retail sector resulting from globalization, the increased competitiveness and transformation on consumer's purchasing behaviour. This paradigm shift also applies to the fish sector, that has been capturing the interest of researchers internationally for political and economic reasons. Taking this competitive environment into account, which values the quality and the service given to the customer based on acceptable costs, it is necessary to adopt customer focused strategies. This thesis is integrated in the ValorMar's project, which was born from the commitment of a broad spectrum of entities, from companies to research centers, positioned by the relevance of the sea economy in the fishery value chain. Thus, this dissertation will try to understand critical relations for the decision making of customers when buying fresh fish.For this, transactional data and data mining techniques appropriate to the problem will be used. The methodology proposed by this thesis aims not only to identify customers using clustering techniques, but also to analyze the market basket of a fresh fish customer. These data analyzis will show that the knowledge extraction from large databases allows to improve the companies strategic decisions and their relationship with customers.
publishDate 2019
dc.date.none.fl_str_mv 2019-07-11
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