Unveiling the features of successful eBay smartphone sellers

Detalhes bibliográficos
Autor(a) principal: Silva, A. T.
Data de Publicação: 2018
Outros Autores: Moro, S., Rita, P., Cortez, P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/15832
Resumo: The present study adopts a data mining approach based on support vector machines (SVM) for modeling the number of sales of smartphone devices by eBay sellers. The data-based sensitivity analysis was adopted for extracting meaningful knowledge translated into the relevance of each input feature for the model. Such approach allowed unveiling that the number of items the seller also has on auctions, the price and the variety of products the seller offers are the three features that influence most the number of sales, in a total of almost 25%, surpassing the relevance of the features related to customers’ feedback.
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spelling Unveiling the features of successful eBay smartphone sellersOnline salesEBay sellersData miningSensitivity analysisSmartphonesThe present study adopts a data mining approach based on support vector machines (SVM) for modeling the number of sales of smartphone devices by eBay sellers. The data-based sensitivity analysis was adopted for extracting meaningful knowledge translated into the relevance of each input feature for the model. Such approach allowed unveiling that the number of items the seller also has on auctions, the price and the variety of products the seller offers are the three features that influence most the number of sales, in a total of almost 25%, surpassing the relevance of the features related to customers’ feedback.Elsevier2018-05-18T08:56:47Z2019-05-18T00:00:00Z2018-01-01T00:00:00Z20182019-03-08T11:12:52Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/15832eng0969-698910.1016/j.jretconser.2018.05.001Silva, A. T.Moro, S.Rita, P.Cortez, P.info: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:RCAAP2023-07-25T17:30:15ZPortal AgregadorONG
dc.title.none.fl_str_mv Unveiling the features of successful eBay smartphone sellers
title Unveiling the features of successful eBay smartphone sellers
spellingShingle Unveiling the features of successful eBay smartphone sellers
Silva, A. T.
Online sales
EBay sellers
Data mining
Sensitivity analysis
Smartphones
title_short Unveiling the features of successful eBay smartphone sellers
title_full Unveiling the features of successful eBay smartphone sellers
title_fullStr Unveiling the features of successful eBay smartphone sellers
title_full_unstemmed Unveiling the features of successful eBay smartphone sellers
title_sort Unveiling the features of successful eBay smartphone sellers
author Silva, A. T.
author_facet Silva, A. T.
Moro, S.
Rita, P.
Cortez, P.
author_role author
author2 Moro, S.
Rita, P.
Cortez, P.
author2_role author
author
author
dc.contributor.author.fl_str_mv Silva, A. T.
Moro, S.
Rita, P.
Cortez, P.
dc.subject.por.fl_str_mv Online sales
EBay sellers
Data mining
Sensitivity analysis
Smartphones
topic Online sales
EBay sellers
Data mining
Sensitivity analysis
Smartphones
description The present study adopts a data mining approach based on support vector machines (SVM) for modeling the number of sales of smartphone devices by eBay sellers. The data-based sensitivity analysis was adopted for extracting meaningful knowledge translated into the relevance of each input feature for the model. Such approach allowed unveiling that the number of items the seller also has on auctions, the price and the variety of products the seller offers are the three features that influence most the number of sales, in a total of almost 25%, surpassing the relevance of the features related to customers’ feedback.
publishDate 2018
dc.date.none.fl_str_mv 2018-05-18T08:56:47Z
2018-01-01T00:00:00Z
2018
2019-05-18T00:00:00Z
2019-03-08T11:12:52Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/15832
url http://hdl.handle.net/10071/15832
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0969-6989
10.1016/j.jretconser.2018.05.001
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 Elsevier
publisher.none.fl_str_mv Elsevier
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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv
repository.mail.fl_str_mv
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