Understanding Big Data Adoption and its Impact on Decision-Making Quality: A Perspective from Public Sector IT Managers in Oman

This study investigates the impact of digital transformation and substantial data generation, commonly referred to as big data, on decision-making quality within Oman's public sector organizations.The widespread use of disruptive digital technologies has led to a significant influx of data, aiming to enhance economic, environmental, and social performance.Recognizing the inherent limitations of data alone, organizations are prioritizing investments in data analytics to facilitate informed decision-making and elevate overall performance.To achieve the study's objectives, a two-stage mixed-methods approach was employed.Initially, a systematic literature review was conducted to identify factors influencing adoption of Big Data Analytics (BDA).Subsequently, in the second stage, a questionnaire was administered to assess the impact of these factors on BDA technology adoption and its role in decision-making making within the IT departments of public organizations in Oman, utilizing a cross-sectional research strategy.Partial Least Squares Structural Equation Modeling was employed to uncover significant factors influencing the adoption of BDA and its subsequent impact on decision-making quality.The findings indicate that relative advantage, complexity, and insecurity significantly predict technological considerations.At the organizational level, top management support and readiness emerge as substantial predictors.Additionally, competitive pressure and government regulations are identified as significant environmental components influencing BDA adoption.In conclusion, the study demonstrates that BDA can effectively enhance decision-making quality in public sector organizations, providing valuable insights for both practitioners and scholars in the ongoing discourse on digital transformation and data-driven decision-making quality.The study employs the Technological Organizational Environment theory to assess the practical impact of selected factors.Data were collected from 332 IT professionals engaged in decision-