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Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model
Information Systems Frontiers
Swansea University Authors:
Yogesh Dwivedi , Laurie Hughes
, Frederic Boy
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DOI (Published version): 10.1007/s10796-021-10203-y
Abstract
This study investigates the factors that build resistance and attitude towards AI voice assistants (AIVA). A theoretical model is proposed using the dual-factor framework by integrating status quo bias factors (sunk cost, regret avoidance, inertia, perceived value, switching costs, and perceived thr...
Published in: | Information Systems Frontiers |
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ISSN: | 1387-3326 1572-9419 |
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Springer Science and Business Media LLC
2021
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URI: | https://cronfa.swan.ac.uk/Record/cronfa57813 |
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v2 57813 2021-09-08 Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model d154596e71b99ad1285563c8fdd373d7 0000-0002-5547-9990 Yogesh Dwivedi Yogesh Dwivedi true false 7abaa0ecff88cdfd7a208d27a8b62173 0000-0002-0956-0608 Laurie Hughes Laurie Hughes true false 43e704698d5dbbac3734b7cd0fef60aa 0000-0003-1373-6634 Frederic Boy Frederic Boy true false 2021-09-08 BBU This study investigates the factors that build resistance and attitude towards AI voice assistants (AIVA). A theoretical model is proposed using the dual-factor framework by integrating status quo bias factors (sunk cost, regret avoidance, inertia, perceived value, switching costs, and perceived threat) and Technology Acceptance Model (TAM; perceived ease of use and perceived usefulness) variables. The study model investigates the relationship between the status quo factors and resistance towards adoption of AIVA, and the relationship between TAM factors and attitudes towards AIVA. A sample of four hundred and twenty was analysed using structural equation modeling to investigate the proposed hypotheses. The results indicate an insignificant relationship between inertia and resistance to AIVA. Perceived value was found to have a negative but significant relationship with resistance to AIVA. Further, the study also found that inertia significantly differs across gender (male/female) and age groupings. The study's framework and results are posited as adding value to the extant literature and practice, directly related to status quo bias theory, dual-factor model and TAM. Journal Article Information Systems Frontiers 0 Springer Science and Business Media LLC 1387-3326 1572-9419 Voice assistants; Artificial intelligence; Dual-factor model; Status quo bias theory; Resistance to change 15 10 2021 2021-10-15 10.1007/s10796-021-10203-y http://dx.doi.org/10.1007/s10796-021-10203-y COLLEGE NANME Business COLLEGE CODE BBU Swansea University SU Library paid the OA fee (TA Institutional Deal) 2023-09-20T10:54:15.4817615 2021-09-08T12:44:47.5682115 Faculty of Humanities and Social Sciences School of Management - Business Management Janarthanan Balakrishnan 1 Yogesh Dwivedi 0000-0002-5547-9990 2 Laurie Hughes 3 Frederic Boy 4 Laurie Hughes 0000-0002-0956-0608 5 Frederic Boy 0000-0003-1373-6634 6 57813__21364__5539041b11704560ae08a5b6ea4b50d7.pdf 57813.pdf 2021-10-29T11:05:39.3014380 Output 903496 application/pdf Version of Record true © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License true eng http://creativecommons.org/licenses/by/4.0/ |
title |
Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model |
spellingShingle |
Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model Yogesh Dwivedi Laurie Hughes Frederic Boy |
title_short |
Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model |
title_full |
Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model |
title_fullStr |
Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model |
title_full_unstemmed |
Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model |
title_sort |
Enablers and Inhibitors of AI-Powered Voice Assistants: A Dual-Factor Approach by Integrating the Status Quo Bias and Technology Acceptance Model |
author_id_str_mv |
d154596e71b99ad1285563c8fdd373d7 7abaa0ecff88cdfd7a208d27a8b62173 43e704698d5dbbac3734b7cd0fef60aa |
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d154596e71b99ad1285563c8fdd373d7_***_Yogesh Dwivedi 7abaa0ecff88cdfd7a208d27a8b62173_***_Laurie Hughes 43e704698d5dbbac3734b7cd0fef60aa_***_Frederic Boy |
author |
Yogesh Dwivedi Laurie Hughes Frederic Boy |
author2 |
Janarthanan Balakrishnan Yogesh Dwivedi Laurie Hughes Frederic Boy Laurie Hughes Frederic Boy |
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Information Systems Frontiers |
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2021 |
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Swansea University |
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1387-3326 1572-9419 |
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10.1007/s10796-021-10203-y |
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Springer Science and Business Media LLC |
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Faculty of Humanities and Social Sciences |
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url |
http://dx.doi.org/10.1007/s10796-021-10203-y |
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description |
This study investigates the factors that build resistance and attitude towards AI voice assistants (AIVA). A theoretical model is proposed using the dual-factor framework by integrating status quo bias factors (sunk cost, regret avoidance, inertia, perceived value, switching costs, and perceived threat) and Technology Acceptance Model (TAM; perceived ease of use and perceived usefulness) variables. The study model investigates the relationship between the status quo factors and resistance towards adoption of AIVA, and the relationship between TAM factors and attitudes towards AIVA. A sample of four hundred and twenty was analysed using structural equation modeling to investigate the proposed hypotheses. The results indicate an insignificant relationship between inertia and resistance to AIVA. Perceived value was found to have a negative but significant relationship with resistance to AIVA. Further, the study also found that inertia significantly differs across gender (male/female) and age groupings. The study's framework and results are posited as adding value to the extant literature and practice, directly related to status quo bias theory, dual-factor model and TAM. |
published_date |
2021-10-15T10:54:12Z |
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1777549865485598720 |
score |
11.021648 |