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Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings

The present study uses the modified Unified Theory of Acceptance and Use of Technology 2 to examine the effect of factors such as performance expectancy (PE), effort expectancy (EE), social influence (SI), and hedonic motivation (HM) that may motivate operators and employees to adopt IVR-based techn...

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Autores principales: Toyoda, Ryo, Russo Abegão, Fernando, Gill, Sue, Glassey, Jarka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer London 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494627/
https://www.ncbi.nlm.nih.gov/pubmed/34642566
http://dx.doi.org/10.1007/s10055-021-00586-3
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author Toyoda, Ryo
Russo Abegão, Fernando
Gill, Sue
Glassey, Jarka
author_facet Toyoda, Ryo
Russo Abegão, Fernando
Gill, Sue
Glassey, Jarka
author_sort Toyoda, Ryo
collection PubMed
description The present study uses the modified Unified Theory of Acceptance and Use of Technology 2 to examine the effect of factors such as performance expectancy (PE), effort expectancy (EE), social influence (SI), and hedonic motivation (HM) that may motivate operators and employees to adopt IVR-based technology into their training. Results of a multi-group analysis based on nationality, prior IVR experience, and/or length of work experience, to analyse the potential similarities and/or differences in perception and acceptance towards using IVR-based technology are also presented. The quantitative research data were gathered using an online questionnaire from 438 chemical operators and/or employees who either speak German, French, or English. Partial least squares structural equation modelling and multi-group analysis based on SmartPLS™ version 3 were used to carry out the path and multi-group analyses. The results show that the behavioural intention (BI) towards adoption of IVR was influenced by PE, EE, and HM for all abovementioned subpopulation. However, the relationship of SI to BI was not supported for respondents with prior IVR experience and for respondents coming from Western region. Although Henseler’s-based multi-group PLS analysis reveals that there was no significant difference between the group comparisons, it is still important to take into account these socio-demographic factors as there are definite group differences in terms of the ranking order of each construct for the IVR adoption intentions among each subpopulation. The implications and future directions were discussed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10055-021-00586-3.
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spelling pubmed-84946272021-10-08 Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings Toyoda, Ryo Russo Abegão, Fernando Gill, Sue Glassey, Jarka Virtual Real S.I. : Covid-19 The present study uses the modified Unified Theory of Acceptance and Use of Technology 2 to examine the effect of factors such as performance expectancy (PE), effort expectancy (EE), social influence (SI), and hedonic motivation (HM) that may motivate operators and employees to adopt IVR-based technology into their training. Results of a multi-group analysis based on nationality, prior IVR experience, and/or length of work experience, to analyse the potential similarities and/or differences in perception and acceptance towards using IVR-based technology are also presented. The quantitative research data were gathered using an online questionnaire from 438 chemical operators and/or employees who either speak German, French, or English. Partial least squares structural equation modelling and multi-group analysis based on SmartPLS™ version 3 were used to carry out the path and multi-group analyses. The results show that the behavioural intention (BI) towards adoption of IVR was influenced by PE, EE, and HM for all abovementioned subpopulation. However, the relationship of SI to BI was not supported for respondents with prior IVR experience and for respondents coming from Western region. Although Henseler’s-based multi-group PLS analysis reveals that there was no significant difference between the group comparisons, it is still important to take into account these socio-demographic factors as there are definite group differences in terms of the ranking order of each construct for the IVR adoption intentions among each subpopulation. The implications and future directions were discussed. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10055-021-00586-3. Springer London 2021-10-07 /pmc/articles/PMC8494627/ /pubmed/34642566 http://dx.doi.org/10.1007/s10055-021-00586-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle S.I. : Covid-19
Toyoda, Ryo
Russo Abegão, Fernando
Gill, Sue
Glassey, Jarka
Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings
title Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings
title_full Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings
title_fullStr Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings
title_full_unstemmed Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings
title_short Drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings
title_sort drivers of immersive virtual reality adoption intention: a multi-group analysis in chemical industry settings
topic S.I. : Covid-19
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494627/
https://www.ncbi.nlm.nih.gov/pubmed/34642566
http://dx.doi.org/10.1007/s10055-021-00586-3
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