An integrated framework for modelling the determinants of big data as a service adoption
Abstract
This study investigates the determinants of Big Data as a Service (BDaaS) adoption among organizations operating in data-intensive industries such as finance, healthcare, retail, and logistics in Europe. Guided by an integrated theoretical lens that combines the Technology-Organization-Environment (TOE) framework with Diffusion of Innovations (DOI), Socio-Technical Systems (STS), and Resource-Based View (RBV), the research employs a quantitative, cross-sectional design. Data were collected through structured questionnaires from 327 IT professionals and decision-makers and analysed using Structural Equation modelling (SEM) and logistic regression. The results indicate that technological readiness, organizational capacity, environmental pressure, and human technology fit, significantly influence BDaaS adoption intention and actual implementation. Moreover, organizational capacity mediates the relationship between technological readiness and adoption, while firm size moderates the effect of environmental pressure. These findings offer theoretical contributions to the literature on digital transformation and provide practical and policy insights for fostering BDaaS uptake across sectors.
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