2020
DOI: 10.1109/jiot.2020.2991791
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The Adoption Analysis of Voice-Based Smart IoT Products

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Cited by 62 publications
(78 citation statements)
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References 79 publications
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“…Overall, there are several other studies all of which establish the relevance of TAM (particularly PEOU and PU) in the online learning context ( Estriegana et al, 2019 , Gahtani, 2016 , Revythi and Tselios, 2019 , Salloum et al, 2019 , Millat et al, 2018 ). Apart from online learning, TAM has also been used to predict the adoption intention in various other contexts like smart-homes ( Pal et al, 2018 , Park et al, 2018 ), smart products ( Dutot et al, 2019 , Pal et al, 2020 ), smart healthcare ( Bettiga et al, 2020 , Kamal et al, 2020 ), music streaming services ( Pal and Triyason, 2018 , Fernandes and Guerra, 2019 ), and many more.…”
Section: Related Workmentioning
confidence: 99%
“…Overall, there are several other studies all of which establish the relevance of TAM (particularly PEOU and PU) in the online learning context ( Estriegana et al, 2019 , Gahtani, 2016 , Revythi and Tselios, 2019 , Salloum et al, 2019 , Millat et al, 2018 ). Apart from online learning, TAM has also been used to predict the adoption intention in various other contexts like smart-homes ( Pal et al, 2018 , Park et al, 2018 ), smart products ( Dutot et al, 2019 , Pal et al, 2020 ), smart healthcare ( Bettiga et al, 2020 , Kamal et al, 2020 ), music streaming services ( Pal and Triyason, 2018 , Fernandes and Guerra, 2019 ), and many more.…”
Section: Related Workmentioning
confidence: 99%
“…The effect of hedonic benefit is applicable for small households only. Authors in [ 5 ] do an in-depth comparison of three popular adoption models (Theory of Planned Behavior, Technology Adoption Model, and Value-based Adoption Model) with respect to their capabilities of predicting the voice-assistant usage, and find Value-based Adoption Model to have the greatest predictive power. Additionally, a multiple regression analysis shows that the hedonic benefits of using the voice-assistants outweigh the utilitarian benefits.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Although, these statistical properties must be considered while doing a factor analysis, yet the interpretability of the results depends on the judgment of the analyst. In case of VUS items (2, 4, 10, 12, Factor 1), (5,7,9,11,Factor 2), and (1, 8, Factor 3) loaded together with PCA giving the most optimal solution. Factor 1 contains items that bring out the errors and difficulties that users encounter while using the voice-assistants and consequently the frustrations, for example, "I thought the voice-assistant had difficulty in understanding what I asked it to do", "I thought the information provided by the voice-assistant was not relevant to what I asked" and more.…”
Section: Exploratory Factor Analysismentioning
confidence: 99%
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“…Another segment of research focuses on the end user perceptions of IoT services [14][15][16][17][18], especially on the user adoption aspect and the experiences related to the use of the IoT services, rather than the privacy and security concerns. A few recent studies try addressing the security and privacy concerns in an IoT context [19][20][21], however there is no concrete conclusion as to what factors motivate the users to disclose their personal information, despite knowing the privacy risks.…”
Section: Introductionmentioning
confidence: 99%