The Adoption Analysis of Voice-Based Smart IoT Products
Journal article
Authors/Editors
Strategic Research Themes
Publication Details
Author list: Pal D., Arpnikanondt C., Funilkul S., Chutimaskul W.
Publisher: Institute of Electrical and Electronics Engineers
Publication year: 2020
Volume number: 7
Issue number: 11
Start page: 10852
End page: 10867
Number of pages: 16
ISSN: 23274662
eISSN: 2327-4662
Languages: English-Great Britain (EN-GB)
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Abstract
Rapid enhancements in the Internet of Things (IoT) and other technologies have resulted in the emergence of various types of smart IT products such as the voice assistants (VAs). Accordingly, several attempts have been made through extant research for explaining the acceptance of these devices by using different models related to technology acceptance. In this article, an in-depth comparative analysis is conducted for determining which model best explains the user's acceptance of using VAs. The technology acceptance model (TAM), theory of planned behavior (TPB), unified theory of acceptance and use of technology (UTAUT), and value-based adoption model (VAM) are used for the purpose of comparison using data collected from 436 (275 potential and 161 actual) participants from the Amazon Mechanical Turk (MTurk) platform. A maximum-likelihood structural equation modelling approach is used for the purpose of hypothesis testing on a model-by-model basis, while for the purpose of comparison between the models, Hotelling's T2 test is used as the statistical measure. All the hypotheses across all the models are found to be true, though with varying degrees of adjusted-R2 values. VAM is found to have the greatest predictive power ( adjusted-R2 =0.683 ) and TAM has the least predictive power (adjusted-R2 =0.439) for behavioral intention (BI). Additionally, a multiple regression analysis is conducted for comparing each of the factors considered in the models in terms of their influence on BI. Results show that enjoyment has the greatest influence (31.24%), followed by subjective norms (15.43%). The effect of usefulness is found to be less (11.86%), which suggests the existence of some usability issues with the VAs. Finally, the research implications are discussed and suggestions are provided. © 2014 IEEE.
Keywords
User Acceptance, voice assistants (VAs)
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