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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...

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Detalles Bibliográficos
Autores principales: Cavalcanti, Diego Rodrigues, Oliveira, Tiago, de Oliveira Santini, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
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.
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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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