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Integrating Business Intelligence Frameworks for Enhanced Organizational Decision-Making: Theoretical and Empirical Synthesis
Issue Vol. 2 No. 01 (2025): VOLUME 02 ISSUE 01 --- Section Articles
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Abstract
Business intelligence has evolved from a set of fragmented reporting tools into a comprehensive organizational capability that fundamentally reshapes how decisions are conceived, evaluated, and implemented. Over the past three decades, organizations across industries have increasingly relied on business intelligence systems to cope with escalating data volumes, growing environmental uncertainty, and heightened competitive pressure. This research article provides an extensive, theory-driven and empirically grounded examination of business intelligence as an integrated framework for organizational decision-making. Drawing strictly on the provided body of literature, the article synthesizes classical and contemporary perspectives on business intelligence, analytics, data mining, and artificial intelligence to develop a holistic understanding of how business intelligence contributes to decision quality, strategic alignment, and organizational performance.
The study is grounded in the conceptual foundations of business intelligence frameworks, with particular attention to early integrative models that positioned business intelligence as a bridge between data, information, and managerial action, such as the framework articulated by Kokin and Wang (2013). Building on this foundation, the article critically examines the evolution of business intelligence capabilities, the role of organizational culture and leadership, the integration of advanced analytics and artificial intelligence, and the behavioral and cognitive dimensions of decision-making. The methodological approach is qualitative and interpretive, relying on systematic theoretical analysis rather than statistical modeling, in line with the objective of developing deep conceptual clarity and scholarly integration.
The findings suggest that business intelligence effectiveness is not solely a function of technological sophistication but is deeply embedded in organizational structures, managerial cognition, user participation, and analytical orientation. The discussion elaborates on competing scholarly viewpoints, unresolved debates, and contextual contingencies, including crisis situations such as the COVID-19 pandemic. The article concludes by identifying critical limitations in current research and proposing future research directions that emphasize ethical considerations, organizational learning, and the democratization of analytics. Overall, this research contributes a comprehensive, publication-ready synthesis that advances theoretical understanding and provides a robust foundation for future empirical inquiry into business intelligence and decision-making.
Keywords
References
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