A Systematic Review of Technology Adoption Models in Cloud Computing Research: A Decade of Evidence (2014–2023)

Abstract

Cloud computing has changed the way individuals and companies’ access, provision and use computing resources, providing scalable, on-demand services with minimal capital outlay. Despite a substantial and expanding body of empirical studies, the literature remains divided across theoretical lenses and application contexts, and there is no consensus on the drivers that promote adoption. This work proposes a systematic literature review (SLR) using the PRISMA 2020 guidelines of the technology adoption models used in cloud computing research published from 2014 to 2023. Mainly based on the Semantic Scholar database, complemented with Web of Science (ISI) and IEEE Xplore, we employed a systematic search and a transparent screening methodology, which resulted in a final corpus of 55 peer-reviewed articles and conference papers. The corpus was coded and examined by frequency analysis and descriptive cross-tabulation by model type, application context, unit of analysis and publication year. The results show that the Technology Acceptance Model (TAM) is the most used lens (36.4%), followed by the Technology-OrganizationEnvironment (TOE) framework (25.5%), the Unified Theory of Acceptance and Use of Technology (UTAUT) (20.0%), Diffusion of Innovation (DOI) (9.1%), mixed/extended models (5.5%), and Theory of Planned Behaviour (TPB) (3.6%). Model selection is highly context-dependent: TAM and UTAUT are favoured for individual-level investigations, but TOE and DOI are favoured for organisational studies. Further analysis of the publishing trend also shows that TOE-, UTAUT-, and integrated-model research have increased in relative proportion since 2020, indicating a slow move from single, user-centric models to multi-level and combined models. The review synthesises findings from business, education, end-user, IT-professional, healthcare and government settings, records the absence of a common determinant set and suggests an integrative route for future study.