How data science can support industry analysis : the case of smartphones

Detalhes bibliográficos
Autor(a) principal: Foschini, Raffaele
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.5/28043
Resumo: Mestrado Bolonha em Management
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spelling 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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T15:30:16Zoai:repositorio.ulisboa.pt:10400.5/28043Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:45:19.897907Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833601821882449920

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