A decision support system application module - for PESTLE analysis - competitive intelligence algorithm
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/94985 |
Resumo: | Project Work report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business Intelligence. |
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A decision support system application module - for PESTLE analysis - competitive intelligence algorithmDSSCompetitive IntelligencePESTLEPythonNeural NetworksProject Work report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business Intelligence.In today’s competitive environment, board directors of companies strive to make the right decisions that will put them ahead of their competitors. However due to the volatility of the company’s external environments any decision has its inherent risks. This thesis aims to apply the Python Programming Language to develop a specific module of a Decision Support Tool that intends to predict market movements, trading position and potential, and operations orientation. The module that will be the scope of this thesis will consist in the creation of a predictive model for countries political factors based in public databases with political indexes all over the globe. This module refers to the first factor to consider in a PESTLE analysis.Castelli, MauroMadureira, Luís Alexandre AbrantesRUNSimões, Elson Neves2020-03-25T11:19:07Z2020-03-092020-03-09T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/94985TID:202468429enginfo: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:RCAAP2024-03-11T04:43:00Zoai:run.unl.pt:10362/94985Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:38:10.926970Repositório 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 decision support system application module - for PESTLE analysis - competitive intelligence algorithm |
title |
A decision support system application module - for PESTLE analysis - competitive intelligence algorithm |
spellingShingle |
A decision support system application module - for PESTLE analysis - competitive intelligence algorithm Simões, Elson Neves DSS Competitive Intelligence PESTLE Python Neural Networks |
title_short |
A decision support system application module - for PESTLE analysis - competitive intelligence algorithm |
title_full |
A decision support system application module - for PESTLE analysis - competitive intelligence algorithm |
title_fullStr |
A decision support system application module - for PESTLE analysis - competitive intelligence algorithm |
title_full_unstemmed |
A decision support system application module - for PESTLE analysis - competitive intelligence algorithm |
title_sort |
A decision support system application module - for PESTLE analysis - competitive intelligence algorithm |
author |
Simões, Elson Neves |
author_facet |
Simões, Elson Neves |
author_role |
author |
dc.contributor.none.fl_str_mv |
Castelli, Mauro Madureira, Luís Alexandre Abrantes RUN |
dc.contributor.author.fl_str_mv |
Simões, Elson Neves |
dc.subject.por.fl_str_mv |
DSS Competitive Intelligence PESTLE Python Neural Networks |
topic |
DSS Competitive Intelligence PESTLE Python Neural Networks |
description |
Project Work report presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business Intelligence. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-03-25T11:19:07Z 2020-03-09 2020-03-09T00:00:00Z |
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/10362/94985 TID:202468429 |
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http://hdl.handle.net/10362/94985 |
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TID:202468429 |
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eng |
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eng |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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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 |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137997967327232 |