Systemic risk analysis of complex socio-technical systems from the safety-II perspective

Modern complex socio-technical systems demand systemic risk analysis approaches that can holistically address the interdependencies between human, technological, and organizational components. Traditional models often fall short in capturing the dynamic and emergent nature of these interactions. This study introduces a novel, integrated risk analysis framework grounded in the Safety-II paradigm, which emphasizes understanding how systems succeed under varying conditions rather than focusing solely on failure. The proposed methodology combines the Functional Resonance Analysis Method (FRAM) with Bayesian Networks to overcome FRAM’s qualitative limitations and enable quantitative assessment of performance variability. The framework is further enriched by integrating complementary techniques, including Monte Carlo Simulation and canonical probabilistic models. This holistic toolkit enables a rigorous and scalable approach for modelling uncertainty and systemic variability across complex operational environments. The methodology is demonstrated through a case study of seaport operations, a representative example of a complex socio-technical system. The results show that the integrated Safety-II-informed framework improves the quantification of systemic risk and enhances the capacity to manage complexity and uncertainty in real-world settings.