Cargando…
An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach
It has been a decade since the first extensive study on the internet's adoption and use was conducted. Circumstances have changed in the last decade internet has become an essential need for every human being. Socio-psychological, economic, and personal factors play a significant role in shapin...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681779/ https://www.ncbi.nlm.nih.gov/pubmed/36414788 http://dx.doi.org/10.1038/s41598-022-24532-8 |
_version_ | 1784834698510336000 |
---|---|
author | Mustafa, Sohaib Zhang, Wen Anwar, Shahzad Jamil, Khalid Rana, Sehrish |
author_facet | Mustafa, Sohaib Zhang, Wen Anwar, Shahzad Jamil, Khalid Rana, Sehrish |
author_sort | Mustafa, Sohaib |
collection | PubMed |
description | It has been a decade since the first extensive study on the internet's adoption and use was conducted. Circumstances have changed in the last decade internet has become an essential need for every human being. Socio-psychological, economic, and personal factors play a significant role in shaping human behaviour. But their role in shaping consumer behaviour toward 5G is still unexplored. In order to determine the impact of socio-psychological elements on 5G technology adoption intention, the study integrated curiosity, perceived value, functional value, and environmental awareness into UTAUT2 and analyzed how they interact. Instead of relying on linear models, this study employed a dual-stage SEM-ANN approach because customers' decision-making process to adopt new technology is complex. Valid responses from 840 respondents were collected, investigated, and ranked using the deep learning ANN approach. All predictors were found statistically significant except social influence. ANN sensitivity analysis revealed that newly integrated predictors (environmental awareness, curiosity) are surprisingly the most important predictors, followed by facilitating conditions and perceived satisfaction. SEM-ANN hybrid two-step deep learning approach explained 83.6% variance higher than the baseline model (UTAUT2). The study improved UTAUT2 by adding new variables and expanding its canvas to predict user technology adoption. This will show how consumers react to 5G services and help telecoms grow into new markets. |
format | Online Article Text |
id | pubmed-9681779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96817792022-11-24 An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach Mustafa, Sohaib Zhang, Wen Anwar, Shahzad Jamil, Khalid Rana, Sehrish Sci Rep Article It has been a decade since the first extensive study on the internet's adoption and use was conducted. Circumstances have changed in the last decade internet has become an essential need for every human being. Socio-psychological, economic, and personal factors play a significant role in shaping human behaviour. But their role in shaping consumer behaviour toward 5G is still unexplored. In order to determine the impact of socio-psychological elements on 5G technology adoption intention, the study integrated curiosity, perceived value, functional value, and environmental awareness into UTAUT2 and analyzed how they interact. Instead of relying on linear models, this study employed a dual-stage SEM-ANN approach because customers' decision-making process to adopt new technology is complex. Valid responses from 840 respondents were collected, investigated, and ranked using the deep learning ANN approach. All predictors were found statistically significant except social influence. ANN sensitivity analysis revealed that newly integrated predictors (environmental awareness, curiosity) are surprisingly the most important predictors, followed by facilitating conditions and perceived satisfaction. SEM-ANN hybrid two-step deep learning approach explained 83.6% variance higher than the baseline model (UTAUT2). The study improved UTAUT2 by adding new variables and expanding its canvas to predict user technology adoption. This will show how consumers react to 5G services and help telecoms grow into new markets. Nature Publishing Group UK 2022-11-21 /pmc/articles/PMC9681779/ /pubmed/36414788 http://dx.doi.org/10.1038/s41598-022-24532-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 | Article Mustafa, Sohaib Zhang, Wen Anwar, Shahzad Jamil, Khalid Rana, Sehrish An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach |
title | An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach |
title_full | An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach |
title_fullStr | An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach |
title_full_unstemmed | An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach |
title_short | An integrated model of UTAUT2 to understand consumers' 5G technology acceptance using SEM-ANN approach |
title_sort | integrated model of utaut2 to understand consumers' 5g technology acceptance using sem-ann approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681779/ https://www.ncbi.nlm.nih.gov/pubmed/36414788 http://dx.doi.org/10.1038/s41598-022-24532-8 |
work_keys_str_mv | AT mustafasohaib anintegratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT zhangwen anintegratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT anwarshahzad anintegratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT jamilkhalid anintegratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT ranasehrish anintegratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT mustafasohaib integratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT zhangwen integratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT anwarshahzad integratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT jamilkhalid integratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach AT ranasehrish integratedmodelofutaut2tounderstandconsumers5gtechnologyacceptanceusingsemannapproach |