A Study on the Factors that Influence Wearable Users' Quantified Self Based on UTAUT Model


Hong Jin, Jiayue Yan, Vol. 4, No. 2, pp. 7-10, Jun. 2020
10.22662/IJEMR.2020.4.2.007, Full Text:
Keywords: Distributed network, Machine Learning, Block-chain, Load-Balancing, Performance Improvement

Abstract

The integrated development of artificial intelligence and wearable technology provides technical conditions for users to participate in quantifying themselves. However, in the current, the research on wearable devices and other technical products is very lacking. Based on the existing user acceptance model, this paper proposes a quantitative self-acceptance model for wearable device users, and puts forward relevant assumptions and provide advice on the development of wearable technology.


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Cite this article
[APA Style]
Hong Jin and Jiayue Yan (2020). A Study on the Factors that Influence Wearable Users' Quantified Self Based on UTAUT Model. International Journal of Emerging Multidisciplinary Research, 4(2), 7-10. DOI: 10.22662/IJEMR.2020.4.2.007.

[IEEE Style]
H. Jin and J. Yan, "A Study on the Factors that Influence Wearable Users' Quantified Self Based on UTAUT Model," International Journal of Emerging Multidisciplinary Research, vol. 4, no. 2, pp. 7-10, 2020. DOI: 10.22662/IJEMR.2020.4.2.007.

[ACM Style]
Hong Jin and Jiayue Yan. 2020. A Study on the Factors that Influence Wearable Users' Quantified Self Based on UTAUT Model. International Journal of Emerging Multidisciplinary Research, 4, 2, (2020), 7-10. DOI: 10.22662/IJEMR.2020.4.2.007.