<![CDATA[This study develops a new theoretical framework for understanding economic decision-making under conditions of persistent uncertainty. Traditional economic models largely assume rational agents operating in stable environments with predictable risks, thereby limiting their applicability in today’s volatile and complex global economy. Increasing economic turbulence—driven by financial instability, technological disruption, and geopolitical uncertainty—has exposed the limitations of risk-based models and highlighted the need for a broader conceptualization of uncertainty. Adopting a qualitative conceptual approach, this study synthesizes insights from behavioral economics, institutional theory, and complexity economics to construct an integrative framework. The proposed model distinguishes between risk, ambiguity, and deep uncertainty, emphasizing that decision-making processes vary significantly across these conditions. It conceptualizes economic agents as adaptive decision-makers who rely not only on optimization but also on heuristics, learning, and institutional context. The framework identifies three key dimensions influencing decision-making under uncertainty: cognitive adaptation, structural constraints, and institutional guidance. These dimensions interact dynamically, shaping both individual and organizational responses to uncertainty. The study argues that uncertainty is not merely a constraint but also a driver of innovation, strategic flexibility, and systemic transformation. This research contributes to the literature by advancing a unified theory of economic decision-making under uncertainty, moving beyond traditional equilibrium-based models. It provides a foundation for future empirical research and offers policy-relevant insights for managing uncertainty in an increasingly volatile global economy.]]>
