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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 12, 2022.
Abstract: Digital Transformation (DT) is a vital change in the way an organization utilizes processes, people, and technology to provide value to its ever changing customer expectations over products and services. Researchers developed models and frameworks to tackle concerns in this area, and existing literature improved our understanding of digital transformation. However, there are not enough comprehensive systematic literature reviews to picture a clear portrait of the advantages of related works and point out the major gaps for future studies. This study aims to evaluate how these models and frameworks affect business while highlighting their advantages and pointing out their gaps for future improvements and studies. A Systematic Literature Review (SLR) applied and collected and reviewed seven models and nine frameworks over five years between 2017 and 2021 from four databases of IEEE, Web of Science, Scopus, and Science Direct. These models and frameworks were reviewed and their advantages for researchers and practitioners were pointed out while picturing a clear vision of what is done in the Digital Transformation development of models and frameworks. The findings in this SLR indicated that the rising trend of DT studies has increased by 275% solely from 2020 to 2021 with 62% of those studies conducted in Europe.
Seyedali Aghamiri, John Karima and Nadire Cavus, “Advantages of Digital Transformation Models and Frameworks for Business: A Systematic Literature Review” International Journal of Advanced Computer Science and Applications(IJACSA), 13(12), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131206
@article{Aghamiri2022,
title = {Advantages of Digital Transformation Models and Frameworks for Business: A Systematic Literature Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131206},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131206},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {12},
author = {Seyedali Aghamiri and John Karima and Nadire Cavus}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.