Purpose: This study aims to examine and synthesize existing scholarly literature on the impact of big data technology on public decision making within the context of digital governance. It seeks to clarify how big data influences policy processes, administrative performance, and governance outcomes, while also identifying institutional and ethical conditions that shape its effectiveness. Subjects and Methods: The study adopts an integrative qualitative literature review design guided by the PRISMA framework. Academic articles were systematically identified from Scopus, Web of Science, and Google Scholar using predefined keywords related to big data, digital governance, and public decision making. Following identification, screening, and eligibility assessment, nine peer-reviewed studies were selected for in-depth analysis. Data were analyzed using thematic analysis and cross-study synthesis to identify recurring patterns, key themes, and relational mechanisms across studies. Results: The findings indicate that big data technology enhances evidence-based decision making by enabling predictive analytics, real-time analysis, and policy optimization. However, its impact is highly conditional, depending on mediating factors such as data quality, analytical skills, and institutional capacity. The literature also highlights significant challenges related to ethics, accountability, transparency, and unequal access to data and skills. These issues underscore the tension between data-driven efficiency and democratic governance principles. Conclusions: Big data technology functions as an enabling but non-deterministic force in digital governance. Its contribution to public decision making depends on supportive institutions, ethical safeguards, and inclusive governance practices that align technological innovation with public values.
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