<p>Innovation ecosystems are increasingly recognized as strategic infrastructures in the knowledge-based economy, where the creation, transfer, and application of knowledge serve as the primary drivers of growth. Yet, as complex, dynamic, and nonlinear systems, they are highly vulnerable to unpredictable disruptions and chaotic dynamics that may undermine sustainable technological and economic development. This study introduces a conceptual model—grounded in Complexity Theory and Chaos Theory—that identifies and manages critical states in the evolutionary trajectory of innovation ecosystems, particularly when they approach the edge of chaos and risk collapse. Drawing on a systematic literature review, key concepts from Complex Adaptive Systems and Chaos Theory were synthesized into a state-space-based model capable of capturing ecosystem dynamics without reliance on historical datasets or predefined events. The model’s applicability is demonstrated through a case study. The findings show that the model moves beyond traditional event-driven approaches by framing ecosystem dynamics in terms of state transitions, highlighting how short-term disruptions can generate long-term systemic effects and enabling the anticipation of critical thresholds where ecosystems face instability. By linking chaos dynamics with knowledge processes, the model illustrates how chaotic conditions reshape knowledge flows, foster collective learning, and enhance technological productivity, thereby offering a robust perspective on ecosystem resilience under uncertainty. Overall, the state-space model provides an adaptive and forward-looking framework for analyzing and managing innovation ecosystems at local, national, and international levels. From a knowledge economy perspective, it explains the dynamic nature of knowledge creation and utilization as the foundation of competitive advantage, while equipping policymakers, universities, technology firms, and other actors with a predictive tool for designing flexible strategies, managing systemic chaos, and fostering sustainable innovation trajectories.</p>