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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

Janarthanan Balakrishnan, Yogesh Dwivedi, Laurie Hughes, Frederic Boy Orcid Logo

Information Systems Frontiers, Volume: 26, Issue: 3, Pages: 921 - 942

Swansea University Authors: Yogesh Dwivedi, Frederic Boy Orcid Logo

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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...

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Published in: Information Systems Frontiers
ISSN: 1387-3326 1572-9419
Published: Springer Science and Business Media LLC 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa57813
first_indexed 2021-09-08T11:49:06Z
last_indexed 2024-11-14T12:12:32Z
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spelling 2024-08-22T12:08:09.7058424 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 Yogesh Dwivedi Yogesh Dwivedi true false 43e704698d5dbbac3734b7cd0fef60aa 0000-0003-1373-6634 Frederic Boy Frederic Boy true false 2021-09-08 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 26 3 921 942 Springer Science and Business Media LLC 1387-3326 1572-9419 Voice assistants; Artificial intelligence; Dual-factor model; Status quo bias theory; Resistance to change 1 6 2024 2024-06-01 10.1007/s10796-021-10203-y COLLEGE NANME COLLEGE CODE Swansea University SU Library paid the OA fee (TA Institutional Deal) 2024-08-22T12:08:09.7058424 2021-09-08T12:44:47.5682115 Faculty of Humanities and Social Sciences School of Management - Business Management Janarthanan Balakrishnan 1 Yogesh Dwivedi 2 Laurie Hughes 3 Frederic Boy 0000-0003-1373-6634 4 57813__31154__1919b173f92e4ff8aa390dca03a2810d.pdf 57813.VoR.pdf 2024-08-22T12:05:12.1072521 Output 886137 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
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
43e704698d5dbbac3734b7cd0fef60aa
author_id_fullname_str_mv d154596e71b99ad1285563c8fdd373d7_***_Yogesh Dwivedi
43e704698d5dbbac3734b7cd0fef60aa_***_Frederic Boy
author Yogesh Dwivedi
Frederic Boy
author2 Janarthanan Balakrishnan
Yogesh Dwivedi
Laurie Hughes
Frederic Boy
format Journal article
container_title Information Systems Frontiers
container_volume 26
container_issue 3
container_start_page 921
publishDate 2024
institution Swansea University
issn 1387-3326
1572-9419
doi_str_mv 10.1007/s10796-021-10203-y
publisher Springer Science and Business Media LLC
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
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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 2024-06-01T08:04:34Z
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