Agile applications of artificial intelligence to apparel industry
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/30906 |
Resumo: | Artificial intelligence systems are increasing its importance in the field of creating value for companies who seek to gain competitive advantage. This is especially true for the online shopping apparel world, in the case of virtual try-on systems. Following this line of thought the theme consumers acceptance of artificial intelligence virtual try-on systems when shopping online apparel came up as a research problem. In this sense this investigation intendeds to study the acceptance by consumers of the virtual try-on artificial systems when buying apparel online according to specific variables previously defined. To assess this, a quantitative approach was used, based on the structural equations model, the partial least squares technique. This research allowed the creation of a new model based on technology acceptance model by including new variables and revealed that the influence of predictive variables on the dependent variable (ATU) is not the same. |
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Agile applications of artificial intelligence to apparel industryConsumer behaviourArtificial intelligenceAgile applicationsVirtual try-onVTOTechnology acceptance modelTAMArtificial intelligence systems are increasing its importance in the field of creating value for companies who seek to gain competitive advantage. This is especially true for the online shopping apparel world, in the case of virtual try-on systems. Following this line of thought the theme consumers acceptance of artificial intelligence virtual try-on systems when shopping online apparel came up as a research problem. In this sense this investigation intendeds to study the acceptance by consumers of the virtual try-on artificial systems when buying apparel online according to specific variables previously defined. To assess this, a quantitative approach was used, based on the structural equations model, the partial least squares technique. This research allowed the creation of a new model based on technology acceptance model by including new variables and revealed that the influence of predictive variables on the dependent variable (ATU) is not the same.Inderscience2024-10-13T00:00:00Z2023-01-01T00:00:00Z20232024-02-07T12:02:39Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/30906eng1741-917410.1504/IJASM.2023.134012Gonçalves, R.Lopes da Costa, R.Pereira, L.Dias, Á.Vinhas da Silva, R.Teixeira, N.info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-11T01:17:54Zoai:repositorio.iscte-iul.pt:10071/30906Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:37:30.011978Repositório 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 |
Agile applications of artificial intelligence to apparel industry |
title |
Agile applications of artificial intelligence to apparel industry |
spellingShingle |
Agile applications of artificial intelligence to apparel industry Gonçalves, R. Consumer behaviour Artificial intelligence Agile applications Virtual try-on VTO Technology acceptance model TAM |
title_short |
Agile applications of artificial intelligence to apparel industry |
title_full |
Agile applications of artificial intelligence to apparel industry |
title_fullStr |
Agile applications of artificial intelligence to apparel industry |
title_full_unstemmed |
Agile applications of artificial intelligence to apparel industry |
title_sort |
Agile applications of artificial intelligence to apparel industry |
author |
Gonçalves, R. |
author_facet |
Gonçalves, R. Lopes da Costa, R. Pereira, L. Dias, Á. Vinhas da Silva, R. Teixeira, N. |
author_role |
author |
author2 |
Lopes da Costa, R. Pereira, L. Dias, Á. Vinhas da Silva, R. Teixeira, N. |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Gonçalves, R. Lopes da Costa, R. Pereira, L. Dias, Á. Vinhas da Silva, R. Teixeira, N. |
dc.subject.por.fl_str_mv |
Consumer behaviour Artificial intelligence Agile applications Virtual try-on VTO Technology acceptance model TAM |
topic |
Consumer behaviour Artificial intelligence Agile applications Virtual try-on VTO Technology acceptance model TAM |
description |
Artificial intelligence systems are increasing its importance in the field of creating value for companies who seek to gain competitive advantage. This is especially true for the online shopping apparel world, in the case of virtual try-on systems. Following this line of thought the theme consumers acceptance of artificial intelligence virtual try-on systems when shopping online apparel came up as a research problem. In this sense this investigation intendeds to study the acceptance by consumers of the virtual try-on artificial systems when buying apparel online according to specific variables previously defined. To assess this, a quantitative approach was used, based on the structural equations model, the partial least squares technique. This research allowed the creation of a new model based on technology acceptance model by including new variables and revealed that the influence of predictive variables on the dependent variable (ATU) is not the same. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-01-01T00:00:00Z 2023 2024-10-13T00:00:00Z 2024-02-07T12:02:39Z |
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/10071/30906 |
url |
http://hdl.handle.net/10071/30906 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1741-9174 10.1504/IJASM.2023.134012 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Inderscience |
publisher.none.fl_str_mv |
Inderscience |
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 |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137426137939968 |