<![CDATA[Complex systems increasingly face systemic risks arising not only from individual component failures but also from interactions among multiple components that can generate nonlinear cascading effects. Conventional risk assessment approaches often rely on node-level indicators, such as centrality measures and individual impact assessments, which may overlook hidden vulnerabilities emerging from combinations of seemingly insignificant components. This study aimed to develop and characterize the concept of Joint Chokepoint Amplification (JCA) as a framework for identifying latent systemic vulnerabilities generated through interacting failures within complex networks. The research employed a qualitative conceptual design combined with structured literature analysis and controlled computational experiments. Secondary data from studies on network science, systemic risk, supply chain disruptions, and higher-order interactions were synthesized to formulate the JCA framework, while simulations using Erdos–Renyi, Barabási–Albert, and modular stochastic block model networks were conducted to examine amplification patterns. The results indicated that joint failures among individually low-impact nodes could produce disproportionately large systemic consequences, with amplification effects strongly influenced by network topology and system conditions. Modular networks demonstrated a higher concentration of latent joint chokepoints compared with other network structures. The findings revealed that conventional node-based assessments may fail to capture interaction-driven risks. This study concludes that systemic resilience requires evaluating not only critical nodes but also vulnerable configurations of interacting components, providing a foundation for developing more adaptive risk management strategies in complex systems.]]>
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