Scraping the web for evidence of price discrimination

Detalhes bibliográficos
Autor(a) principal: Mendes, Tomás
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/161392
Resumo: This paper exhibits a study about the practice of price personalisation on e-commerce websites. With this goal, eleven websites were analysed from three different industries: Fashion retail, General Retail and Travel. Moreover, to find evidence of this practice, the differentiated features tested were the device, operating system (OS), browser, and geolocation of the visiting user. Furthermore, two dimensions of price personalisation were conducted in-depth: price discrimination and price steering. Finally, summarised research about the existing laws and their implications is also presented in this report.
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spelling Scraping the web for evidence of price discriminationPrice personalizationPrice discriminationPrice steeringData scienceWeb scrapingData analysisGDPRDomínio/Área Científica::Ciências Sociais::Economia e GestãoThis paper exhibits a study about the practice of price personalisation on e-commerce websites. With this goal, eleven websites were analysed from three different industries: Fashion retail, General Retail and Travel. Moreover, to find evidence of this practice, the differentiated features tested were the device, operating system (OS), browser, and geolocation of the visiting user. Furthermore, two dimensions of price personalisation were conducted in-depth: price discrimination and price steering. Finally, summarised research about the existing laws and their implications is also presented in this report.Han, QiweiEsposito, FabrizioRUNMendes, Tomás2023-12-18T10:08:35Z2022-12-132022-12-132022-12-13T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/161392TID:203317521enginfo: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:RCAAP2024-03-11T05:44:16Zoai:run.unl.pt:10362/161392Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:58:30.463639Repositório 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 Scraping the web for evidence of price discrimination
title Scraping the web for evidence of price discrimination
spellingShingle Scraping the web for evidence of price discrimination
Mendes, Tomás
Price personalization
Price discrimination
Price steering
Data science
Web scraping
Data analysis
GDPR
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Scraping the web for evidence of price discrimination
title_full Scraping the web for evidence of price discrimination
title_fullStr Scraping the web for evidence of price discrimination
title_full_unstemmed Scraping the web for evidence of price discrimination
title_sort Scraping the web for evidence of price discrimination
author Mendes, Tomás
author_facet Mendes, Tomás
author_role author
dc.contributor.none.fl_str_mv Han, Qiwei
Esposito, Fabrizio
RUN
dc.contributor.author.fl_str_mv Mendes, Tomás
dc.subject.por.fl_str_mv Price personalization
Price discrimination
Price steering
Data science
Web scraping
Data analysis
GDPR
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Price personalization
Price discrimination
Price steering
Data science
Web scraping
Data analysis
GDPR
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description This paper exhibits a study about the practice of price personalisation on e-commerce websites. With this goal, eleven websites were analysed from three different industries: Fashion retail, General Retail and Travel. Moreover, to find evidence of this practice, the differentiated features tested were the device, operating system (OS), browser, and geolocation of the visiting user. Furthermore, two dimensions of price personalisation were conducted in-depth: price discrimination and price steering. Finally, summarised research about the existing laws and their implications is also presented in this report.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-13
2022-12-13
2022-12-13T00:00:00Z
2023-12-18T10:08:35Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/161392
TID:203317521
url http://hdl.handle.net/10362/161392
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dc.language.iso.fl_str_mv eng
language eng
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