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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
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)
Exportar Referência (IEEE) 
R. J. Costa et al.,  "Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling", in Mathematics, vol. 10, no. 22, 2022
Exportar BibTeX 
@article{costa2022_1732202161931,
	author = "Lopes da Costa, R. and Gupta, V. and Gonçalves, R. and Dias, Á. and Pereira, L. and Gupta, C.",
	title = "Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling",
	journal = "Mathematics",
	year = "2022",
	volume = "10",
	number = "22",
	doi = "10.3390/math10224358",
	url = "https://www.mdpi.com/2227-7390/10/22/4358"
}
Exportar RIS 
TY  - JOUR
TI  - Artificial intelligence and cognitive computing in companies in Portugal: An outcome of partial least squares—structural equations modeling
T2  - Mathematics
VL  - 10
IS  - 22
AU  - Lopes da Costa, R.
AU  - Gupta, V.
AU  - Gonçalves, R.
AU  - Dias, Á.
AU  - Pereira, L.
AU  - Gupta, C.
PY  - 2022
SN  - 2227-7390
DO  - 10.3390/math10224358
UR  - https://www.mdpi.com/2227-7390/10/22/4358
AB  - 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.
ER  -