Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/27879
Author(s): Lopes da Costa, R.
Gupta, V.
Gonçalves, R.
Dias, Á.
Pereira, L.
Gupta, C.
Date: 2022
Title: Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
Journal title: Mathematics
Volume: 10
Number: 22
Reference: Lopes da Costa, R., Gupta, V., Gonçalves, R., Dias, Á., Pereira, L., & Gupta, C. (2022). Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling. Mathematics, 10(22), 4358. http://dx.doi.org/10.3390/math10224358
ISSN: 2227-7390
DOI (Digital Object Identifier): 10.3390/math10224358
Keywords: Artificial intelligence
Cognitive computing
Business management
Intelligent systems
Partial least squares structural equations modelling
Abstract: 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.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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