This study examines the dynamics of decision-making in complex and unstable organizational systems, where traditional rational-linear approaches are increasingly inadequate in addressing uncertainty, rapid change, and multidimensional interactions. The research aims to develop an integrative decision-making model by incorporating perspectives from complexity theory, system dynamics, management psychology, and digital technologies. A qualitative approach was employed using a systematic literature review and conceptual synthesis of recent scholarly works (2021–2025). Data were collected through document analysis and analyzed using thematic content analysis and systems thinking to identify key dimensions influencing decision-making processes. The findings reveal that decision-making in complex systems is nonlinear, adaptive, and emergent, shaped by the interaction of structural, technological, and human factors. Key dimensions include complex adaptive systems, chaos and nonlinear dynamics, feedback mechanisms, psychological factors, conflict management, and the integration of AI and data-driven systems. The discussion highlights the importance of a hybrid approach that balances technological capabilities with human-centered leadership and organizational learning to enhance decision quality and resilience. In conclusion, this study proposes an integrative framework that provides both theoretical and practical contributions, enabling organizations to navigate uncertainty and improve decision-making effectiveness in unstable environments.
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