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Drivers of Digital Transformation Adoption: A Weight and Meta-Analysis (preprint)
ssrn; 2021.
Preprint
in English
| PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3924304
ABSTRACT
The COVID-19 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, 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 adoption.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-SSRN
Main subject:
Cell Transformation, Viral
/
COVID-19
Language:
English
Year:
2021
Document Type:
Preprint
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