Cargando…

Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants

Virtual Assistants, also known as conversational artificial intelligence, are transforming the reality around us. These virtual assistants have challenged our daily lives by assisting us in the different dimensions of our lives, such as health, entertainment, home, and education, among others. The m...

Descripción completa

Detalles Bibliográficos
Autores principales: García de Blanes Sebastián, María, Sarmiento Guede, José Ramón, Antonovica, Arta
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9624285/
https://www.ncbi.nlm.nih.gov/pubmed/36329748
http://dx.doi.org/10.3389/fpsyg.2022.993935
_version_ 1784822198601515008
author García de Blanes Sebastián, María
Sarmiento Guede, José Ramón
Antonovica, Arta
author_facet García de Blanes Sebastián, María
Sarmiento Guede, José Ramón
Antonovica, Arta
author_sort García de Blanes Sebastián, María
collection PubMed
description Virtual Assistants, also known as conversational artificial intelligence, are transforming the reality around us. These virtual assistants have challenged our daily lives by assisting us in the different dimensions of our lives, such as health, entertainment, home, and education, among others. The main purpose of this study is to develop and empirically test a model to predict factors that affect users' behavioral intentions when they use intelligent virtual assistants. As a theoretical basis for investigating behavioral intention of using virtual assistants from the consumers' perspective, researchers employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). For this research paper, seven variables were analyzed: performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, habit, and price/value. In order to improve consumer behavior prediction, three additional factors were included in the study: perceived privacy risk, trust, and personal innovativeness. Researchers carried out an online survey with 304 responses. The obtained sample was analyzed with Structural Equation Modeling (SEM) through IBM SPSS V. 27.0 and AMOS V 27.0. The main study results reveal that factors, such as habit, trust, and personal innovation, have a significant impact on the adoption of virtual assistants. However, on the other side, performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, price/value, and perceived privacy risk were not significant factors in the users' intention to adopt this service. This research paper examines the effect of personal innovation, security, and trust variables in relation to the use of virtual assistants. It contributes to a more holistic understanding of the adoption of these intelligent devices and tries to fill the knowledge gap on this topic, as it is an emerging technology. This investigation also provides relevant information on how to successfully implement these technologies.
format Online
Article
Text
id pubmed-9624285
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-96242852022-11-02 Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants García de Blanes Sebastián, María Sarmiento Guede, José Ramón Antonovica, Arta Front Psychol Psychology Virtual Assistants, also known as conversational artificial intelligence, are transforming the reality around us. These virtual assistants have challenged our daily lives by assisting us in the different dimensions of our lives, such as health, entertainment, home, and education, among others. The main purpose of this study is to develop and empirically test a model to predict factors that affect users' behavioral intentions when they use intelligent virtual assistants. As a theoretical basis for investigating behavioral intention of using virtual assistants from the consumers' perspective, researchers employed the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). For this research paper, seven variables were analyzed: performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, habit, and price/value. In order to improve consumer behavior prediction, three additional factors were included in the study: perceived privacy risk, trust, and personal innovativeness. Researchers carried out an online survey with 304 responses. The obtained sample was analyzed with Structural Equation Modeling (SEM) through IBM SPSS V. 27.0 and AMOS V 27.0. The main study results reveal that factors, such as habit, trust, and personal innovation, have a significant impact on the adoption of virtual assistants. However, on the other side, performance expectancy, effort expectancy, facilitating conditions, social influence, hedonic motivation, price/value, and perceived privacy risk were not significant factors in the users' intention to adopt this service. This research paper examines the effect of personal innovation, security, and trust variables in relation to the use of virtual assistants. It contributes to a more holistic understanding of the adoption of these intelligent devices and tries to fill the knowledge gap on this topic, as it is an emerging technology. This investigation also provides relevant information on how to successfully implement these technologies. Frontiers Media S.A. 2022-10-18 /pmc/articles/PMC9624285/ /pubmed/36329748 http://dx.doi.org/10.3389/fpsyg.2022.993935 Text en Copyright © 2022 García de Blanes Sebastián, Sarmiento Guede and Antonovica. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
García de Blanes Sebastián, María
Sarmiento Guede, José Ramón
Antonovica, Arta
Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants
title Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants
title_full Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants
title_fullStr Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants
title_full_unstemmed Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants
title_short Application and extension of the UTAUT2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants
title_sort application and extension of the utaut2 model for determining behavioral intention factors in use of the artificial intelligence virtual assistants
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9624285/
https://www.ncbi.nlm.nih.gov/pubmed/36329748
http://dx.doi.org/10.3389/fpsyg.2022.993935
work_keys_str_mv AT garciadeblanessebastianmaria applicationandextensionoftheutaut2modelfordeterminingbehavioralintentionfactorsinuseoftheartificialintelligencevirtualassistants
AT sarmientoguedejoseramon applicationandextensionoftheutaut2modelfordeterminingbehavioralintentionfactorsinuseoftheartificialintelligencevirtualassistants
AT antonovicaarta applicationandextensionoftheutaut2modelfordeterminingbehavioralintentionfactorsinuseoftheartificialintelligencevirtualassistants