Identifying Gaps and Future Research Agenda: Key Success Factors of Digital Transformation Adoption
Amando Jr. Pimentel Singun
Amando Jr. Pimentel Singun, College of Computing and Information Sciences, University of Technology and Applied Sciences, Muscat, Sultanate of Oman.
Manuscript received on 24 July 2026 | First Revised Manuscript received on 05 August 2026 | Second Revised Manuscript received on 09 August 2026 | Manuscript Accepted on 15 August 2026 | Manuscript published on 30 August 2026 | PP: 7-16 | Volume-15 Issue-9, August 2026 | Retrieval Number: 100.1/ijitee.J129915100926 | DOI: 10.35940/ijitee.J1299.15090826
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The purpose of this study is to advance knowledge for managers, policymakers, and researchers regarding the important key factors of successful Digital Transformation (DT) adoption, which can shed light on research gaps and help form a research agenda. A systematic literature review was conducted to analyse 26 peer-reviewed journal articles published between 2020 and 2025 from the Scopus, Emerald, Insight, Google Scholar, and ProQuest databases, following the PRISMA guidelines. Four DT adoption models, such as Diffusion of Innovation (DOI), Technology Acceptance Model (TAM), Task-Technology Fit (TTF), and Theory of Planned Behaviour (TPB), have been analysed to understand why people embrace DT either positively or negatively. According to the literature, the success factors for adopting DT have been identified. In addition, it is found that using only one DT adoption model does not ensure success. It is advisable to use an integrated multi-model or multiple frameworks for the theoretical adoption of DT. Using multiple frameworks makes DT adoption easier to understand. The Input-Process Output (IPO) schema allows consolidating the gaps in the present state and setting out the research agenda. The IPO schema can be considered a helpful tool for identifying research gaps and setting the research agenda, as well as for planning, decision-making, and policymaking.
Keywords: Digital Transformation, Diffusion of Innovation (DOI), Technology Acceptance Model (TAM), Task-Technology Fit (TTF), Theory of Planned Behaviour (TPB).
Scope of the Article: Computer Science and Engineering