How data science can support industry analysis : the case of smartphones
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/28043 |
Resumo: | Mestrado Bolonha em Management |
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How data science can support industry analysis : the case of smartphonesSmartphonesWeb ScrapingClusteringAnsoffPorterMestrado Bolonha em ManagementThe following work presents a comprehensive study of the smartphone industry, with a focus on the development of an automated tool for the monitoring of the market and the recognition of direct competing products. The thesis begins with an overview of the smartphone market. The study then investigates the attractiveness of the market in the framework of Porter's five competitive forces model (Porter, 1979), and different management styles different companies should implement to deal with the high level of environmental Turbulence that characterizes this sector. The Ansoff model for the response to turbulent environments is used to further support this investigation. On the basis of said analysis, it is then presented the development of a Python programmed script that uses web scraping and clustering algorithms to collect the technical specifications of a large number of the smartphone available on the market and proceeds to cluster the devices in order to identify similar and directly competing products. The study will show how the industry is shaped and present the main critical points that small and big firms need to deal with in order to thrive in this industry. The results will present the study of the industry in the framework of the two models and the proof of concept of a practical tool that aims at supporting firms in dealing with the findings given by the application of said models. This thesis contributes to the understanding of the smartphone market by offering a holistic view of its current state and potential trends for the future. The application of such models ultimately points towards the crucial importance of the constant and consistent monitoring of the market as a defense towards the constant evolution and unpredictability of the Smartphone industry.Instituto Superior de Economia e GestãoCosta, CarlosRepositório da Universidade de LisboaFoschini, Raffaele2024-01-24T01:30:40Z2023-032023-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.5/28043engFoschini, Raffaele (2023). “How data science can support industry analysis : the case of smartphones”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestãoinfo: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:RCAAP2024-01-28T01:33:16Zoai:www.repository.utl.pt:10400.5/28043Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:10:11.885255Repositório 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 |
How data science can support industry analysis : the case of smartphones |
title |
How data science can support industry analysis : the case of smartphones |
spellingShingle |
How data science can support industry analysis : the case of smartphones Foschini, Raffaele Smartphones Web Scraping Clustering Ansoff Porter |
title_short |
How data science can support industry analysis : the case of smartphones |
title_full |
How data science can support industry analysis : the case of smartphones |
title_fullStr |
How data science can support industry analysis : the case of smartphones |
title_full_unstemmed |
How data science can support industry analysis : the case of smartphones |
title_sort |
How data science can support industry analysis : the case of smartphones |
author |
Foschini, Raffaele |
author_facet |
Foschini, Raffaele |
author_role |
author |
dc.contributor.none.fl_str_mv |
Costa, Carlos Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Foschini, Raffaele |
dc.subject.por.fl_str_mv |
Smartphones Web Scraping Clustering Ansoff Porter |
topic |
Smartphones Web Scraping Clustering Ansoff Porter |
description |
Mestrado Bolonha em Management |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-03 2023-03-01T00:00:00Z 2024-01-24T01:30:40Z |
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/10400.5/28043 |
url |
http://hdl.handle.net/10400.5/28043 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Foschini, Raffaele (2023). “How data science can support industry analysis : the case of smartphones”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão |
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 |
Instituto Superior de Economia e Gestão |
publisher.none.fl_str_mv |
Instituto Superior de Economia e Gestão |
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 |
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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) |
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 |
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