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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) 
Araújo, C., Gonçalves, R., Lopes da Costa, R., Dias, Á. & Pereira, L. (2022). Artificial intelligence in digital customer journey. International Journal of Electronic Customer Relationship Management . 13 (3), 248-271
Exportar Referência (IEEE) 
C. et al.,  "Artificial intelligence in digital customer journey", in Int. Journal of Electronic Customer Relationship Management , vol. 13, no. 3, pp. 248-271, 2022
Exportar BibTeX 
@article{c.2022_1734880797632,
	author = "Araújo, C. and Gonçalves, R. and Lopes da Costa, R. and Dias, Á. and Pereira, L.",
	title = "Artificial intelligence in digital customer journey",
	journal = "International Journal of Electronic Customer Relationship Management ",
	year = "2022",
	volume = "13",
	number = "3",
	doi = "10.1504/IJECRM.2022.124098",
	pages = "248-271",
	url = "https://www.inderscienceonline.com/doi/abs/10.1504/IJECRM.2022.124098"
}
Exportar RIS 
TY  - JOUR
TI  - Artificial intelligence in digital customer journey
T2  - International Journal of Electronic Customer Relationship Management 
VL  - 13
IS  - 3
AU  - Araújo, C.
AU  - Gonçalves, R.
AU  - Lopes da Costa, R.
AU  - Dias, Á.
AU  - Pereira, L.
PY  - 2022
SP  - 248-271
SN  - 1750-0664
DO  - 10.1504/IJECRM.2022.124098
UR  - https://www.inderscienceonline.com/doi/abs/10.1504/IJECRM.2022.124098
AB  - Artificial intelligence (AI) is present in many business areas, the marketing of the fashion industry being one of them. In this sense, AI becomes relevant for firms, helping to acquire better consumer data and to stand out from the competition by offering personalised, rich, and unique experiences. This study seeks to understand the current state of interaction that consumers have with AI during the digital customer journey (CJ), in the fashion industry. This research focused on the fashion industry and addresses the following AI technologies: recommendation systems, chatbots and virtual testers. These variables were deepened through an online questionnaire and an evaluation of the offerings that various brands have on their websites and apps. The data shows that people who interact with AI are younger and have self-confidence, they are mainly looking for a quick response to their requests, mainly through recommendation systems, chatbots and virtual testers
ER  -