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Drivers of digital transformation adoption: A weight and meta-analysis
The advent of the global pandemic has accelerated the growing need for product and service transformation, highlighting the emerging importance of technology and creating the opportunity to update the digital transformation (DT) domain through empirical-quantitative research. This weight and meta-an...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841366/ https://www.ncbi.nlm.nih.gov/pubmed/35198776 http://dx.doi.org/10.1016/j.heliyon.2022.e08911 |
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author | Cavalcanti, Diego Rodrigues Oliveira, Tiago de Oliveira Santini, Fernando |
author_facet | Cavalcanti, Diego Rodrigues Oliveira, Tiago de Oliveira Santini, Fernando |
author_sort | Cavalcanti, Diego Rodrigues |
collection | PubMed |
description | The advent of the global pandemic has accelerated the growing need for product and service transformation, highlighting the emerging importance of technology and creating the opportunity to update the digital transformation (DT) domain through empirical-quantitative research. This weight and meta-analysis enabled the synthesis and integration of previous literature on the scope of individual DT adoption, evaluating the state of the art and filling a void on the subject. Athwart 88 studies and 99 datasets by international sources, our results demonstrate that attitude and satisfaction are relevant predictors of behavioral intentions and promising outcomes, including compatibility and personal innovativeness. Behavioral intentions, satisfaction, and habit are the best predictors for DT use. Usefulness and ease of use are critical for DT adoption intention and use, being moderated by individualism, as a cultural factor, human capital, and knowledge-technology, as innovation indicators. We present a conceptual model of promising and best predictors for future research on DT individual adoption. |
format | Online Article Text |
id | pubmed-8841366 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88413662022-02-22 Drivers of digital transformation adoption: A weight and meta-analysis Cavalcanti, Diego Rodrigues Oliveira, Tiago de Oliveira Santini, Fernando Heliyon Research Article The advent of the global pandemic has accelerated the growing need for product and service transformation, highlighting the emerging importance of technology and creating the opportunity to update the digital transformation (DT) domain through empirical-quantitative research. This weight and meta-analysis enabled the synthesis and integration of previous literature on the scope of individual DT adoption, evaluating the state of the art and filling a void on the subject. Athwart 88 studies and 99 datasets by international sources, our results demonstrate that attitude and satisfaction are relevant predictors of behavioral intentions and promising outcomes, including compatibility and personal innovativeness. Behavioral intentions, satisfaction, and habit are the best predictors for DT use. Usefulness and ease of use are critical for DT adoption intention and use, being moderated by individualism, as a cultural factor, human capital, and knowledge-technology, as innovation indicators. We present a conceptual model of promising and best predictors for future research on DT individual adoption. Elsevier 2022-02-05 /pmc/articles/PMC8841366/ /pubmed/35198776 http://dx.doi.org/10.1016/j.heliyon.2022.e08911 Text en © 2022 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Cavalcanti, Diego Rodrigues Oliveira, Tiago de Oliveira Santini, Fernando Drivers of digital transformation adoption: A weight and meta-analysis |
title | Drivers of digital transformation adoption: A weight and meta-analysis |
title_full | Drivers of digital transformation adoption: A weight and meta-analysis |
title_fullStr | Drivers of digital transformation adoption: A weight and meta-analysis |
title_full_unstemmed | Drivers of digital transformation adoption: A weight and meta-analysis |
title_short | Drivers of digital transformation adoption: A weight and meta-analysis |
title_sort | drivers of digital transformation adoption: a weight and meta-analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8841366/ https://www.ncbi.nlm.nih.gov/pubmed/35198776 http://dx.doi.org/10.1016/j.heliyon.2022.e08911 |
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