A Novel Methodology for Risk Assessment Considering Risk Higher Order Interactions and Propagation Effects

Abstract

Risk assessment is pivotal to effective risk management, yet traditional approaches often overlook the complexity of interactions among multiple risks. Existing methodologies primarily focus on pairwise interactions, neglecting higher order interactions that occur in groups of three or more risks. This oversight can lead to flawed risk assessments and ineffective mitigation strategies. To address this gap, in this article, we present a novel risk assessment framework that incorporates higher order interactions and accounts for the dynamics of risk propagation. Using design structure matrix and logarithmic scale, we construct a comprehensive risk interaction network (RIN). Higher order structures within the RIN are identified by simplicial complex, and a risk propagation model is developed to capture both pairwise interactions and higher order interactions. Validation through real-world projects and experimental scenarios demonstrates that higher order interactions profoundly influence risk dynamics, enabling more accurate and actionable risk rankings. By offering a holistic perspective, this methodology empowers managers to implement targeted, effective risk mitigation strategies.