DATA-DRIVEN STRATEGIC MANAGEMENT AND COMPETITIVE ADVANTAGE: A CONCEPTUAL ANALYSIS OF EMERGING ECONOMIES

Data-driven strategic management has become increasingly important as organizations seek to transform data into actionable knowledge and competitive advantage. Although data mining and business intelligence provide opportunities to improve forecasting, resource allocation, and strategic decision-making, their effectiveness depends on organizational capabilities and the institutional environments in which firms operate. These issues are particularly relevant to emerging economies, where firms may experience differences in digital infrastructure, analytical expertise, financial resources, and institutional development. This study develops a conceptual framework explaining the relationship between data mining capabilities and competitive advantage in emerging economies. Drawing on the resource-based view, dynamic capabilities theory, and recent literature on business intelligence, the paper examines the mechanisms through which analytical resources may contribute to strategic agility, organizational learning, and competitive performance. The study adopts a conceptual literature-analysis approach and does not claim to report newly collected empirical data. It proposes that data quality, analytical competence, managerial integration, and organizational learning are important conditions for translating analytical resources into strategic value. The framework also identifies institutional conditions and resource availability as contextual factors that may influence these relationships. The proposed model provides a theoretical foundation for future empirical research and offers practical implications for organizations seeking to strengthen their data-driven strategic management capabilities.