Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling

Detalhes bibliográficos
Autor(a) principal: Lopes da Costa, R.
Data de Publicação: 2022
Outros Autores: Gupta, V., Gonçalves, R., Dias, Á., Pereira, L., Gupta, C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/27879
Resumo: Artificial intelligence (AI) and cognitive computing (CC) are different, which is why each technology has its advantages and disadvantages, depending on the task/operation that a business wants to optimize. Nowadays, it is easy to confuse both by simply associating CC with the widespread theme of AI. This way, companies that want to implement AI know that what they want, in most cases, are the features provided by CC. It is important in these situations to know how to differentiate them, so that it is possible to identify in which circumstance one is more suitable than another, to get more out of the benefits that each has to offer. This project focuses on highlighting the capabilities of both technologies, more specifically in business contexts in which the implementation of intelligent systems and the interest of companies in them is favourable. It also identifies which aspects of these technologies are most interesting for companies. Based on this information, it is evaluated whether these aspects are relevant in decision making. Data analysis is carried out by employing partial least squares structural equations modelling (PLS-SEM) and descriptive statistical techniques.
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spelling Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modelingArtificial intelligenceCognitive computingBusiness managementIntelligent systemsPartial least squares structural equations modellingArtificial intelligence (AI) and cognitive computing (CC) are different, which is why each technology has its advantages and disadvantages, depending on the task/operation that a business wants to optimize. Nowadays, it is easy to confuse both by simply associating CC with the widespread theme of AI. This way, companies that want to implement AI know that what they want, in most cases, are the features provided by CC. It is important in these situations to know how to differentiate them, so that it is possible to identify in which circumstance one is more suitable than another, to get more out of the benefits that each has to offer. This project focuses on highlighting the capabilities of both technologies, more specifically in business contexts in which the implementation of intelligent systems and the interest of companies in them is favourable. It also identifies which aspects of these technologies are most interesting for companies. Based on this information, it is evaluated whether these aspects are relevant in decision making. Data analysis is carried out by employing partial least squares structural equations modelling (PLS-SEM) and descriptive statistical techniques.MDPI2023-02-14T11:45:45Z2022-01-01T00:00:00Z20222023-02-14T11:44:23Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/27879eng2227-739010.3390/math10224358Lopes da Costa, R.Gupta, V.Gonçalves, R.Dias, Á.Pereira, L.Gupta, C.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:RCAAP2023-11-09T17:33:24Zoai:repositorio.iscte-iul.pt:10071/27879Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:15:03.868025Repositório 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 Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
title Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
spellingShingle Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
Lopes da Costa, R.
Artificial intelligence
Cognitive computing
Business management
Intelligent systems
Partial least squares structural equations modelling
title_short Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
title_full Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
title_fullStr Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
title_full_unstemmed Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
title_sort Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
author Lopes da Costa, R.
author_facet Lopes da Costa, R.
Gupta, V.
Gonçalves, R.
Dias, Á.
Pereira, L.
Gupta, C.
author_role author
author2 Gupta, V.
Gonçalves, R.
Dias, Á.
Pereira, L.
Gupta, C.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Lopes da Costa, R.
Gupta, V.
Gonçalves, R.
Dias, Á.
Pereira, L.
Gupta, C.
dc.subject.por.fl_str_mv Artificial intelligence
Cognitive computing
Business management
Intelligent systems
Partial least squares structural equations modelling
topic Artificial intelligence
Cognitive computing
Business management
Intelligent systems
Partial least squares structural equations modelling
description Artificial intelligence (AI) and cognitive computing (CC) are different, which is why each technology has its advantages and disadvantages, depending on the task/operation that a business wants to optimize. Nowadays, it is easy to confuse both by simply associating CC with the widespread theme of AI. This way, companies that want to implement AI know that what they want, in most cases, are the features provided by CC. It is important in these situations to know how to differentiate them, so that it is possible to identify in which circumstance one is more suitable than another, to get more out of the benefits that each has to offer. This project focuses on highlighting the capabilities of both technologies, more specifically in business contexts in which the implementation of intelligent systems and the interest of companies in them is favourable. It also identifies which aspects of these technologies are most interesting for companies. Based on this information, it is evaluated whether these aspects are relevant in decision making. Data analysis is carried out by employing partial least squares structural equations modelling (PLS-SEM) and descriptive statistical techniques.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01T00:00:00Z
2022
2023-02-14T11:45:45Z
2023-02-14T11:44:23Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/27879
url http://hdl.handle.net/10071/27879
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2227-7390
10.3390/math10224358
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