Risk impact pathway analysis (RIPA): A dynamic risk assessment framework for interdependent critical infrastructures

Abstract Critical Infrastructures (CI) are increasingly interdependent, forming complex dependency networks where disruptions can propagate across sectors and amplify systemic risk. Conventional risk assessment methods are limited by evaluating components in isolation and neglecting how interdependencies shape cascading exposure. This paper introduces the Risk Impact Pathway Analysis (RIPA) framework–a dynamic, dependency-aware risk assessment model that explicitly traces and quantifies risk propagation pathways within interdependent CI systems. RIPA incorporates three key propagation factors: Linkage Intensity (LI), measuring dependency strength; Resilience (RE), acting as a risk shield; and Criticality, functioning as a risk amplifier. Unlike traditional methods focused solely on initial risk (R 0 ), RIPA calculates Total Systemic Risk, revealing hidden high-risk nodes and propagation routes. The framework is validated through a multi-sector case study of the LAMAD-LLC integrated infrastructure system, demonstrating its applicability and effectiveness. Results demonstrate that incorporating interdependency criteria into risk assessment reveals significant hidden vulnerabilities, with certain infrastructure components exhibiting risk increases compared to traditional single-point assessments. This amplification effect illustrates how failures or vulnerabilities propagate through interconnected systems, creating compound risks not captured by conventional methods. Sensitivity analysis reveals that resilience enhancement interventions achieve approximately twice the risk reduction compared to equivalent modifications in either criticality scores or linkage intensity parameters. These findings validate RIPA’s capacity to provide a pathway-centric, topology-aware understanding of systemic exposure, enabling more targeted and effective infrastructure risk management strategies than traditional approaches.