Enterprise Resilience and Trust in Multiscale Logistics Systems

Economic development and industrial networks need coordination among manufacturers, warehouses, transportation assets, embedded controls and sensors, and intelligence automation. Ensuring predictability, security, and trust in these enterprise systems requires methods that capture both the physical pathways supporting operations and the infrastructure sectors that enable them. This study introduces a hybrid sector-asset network framework that captures both highlevel infrastructure interdependencies and asset-level pathways that support freight operations in a sociotechnical system. The approach proceeds across three phases: (1) construction of a multilayer network linking asset-level facilities with critical infrastructure sectors; (2) establishing baseline system structure using centrality-based system order metrics; and (3) stress testing the network by applying structural disruptions and quantifying the effects on the system. The framework is demonstrated on an industrial region of the mid-Atlantic United States by comparing the current logistics systems configuration with an alternative design that integrates two multimodal logistics parks (MMLPs). Disruptions representing weather, operational uncertainty, regulatory changes, and modal loss are applied to both configurations. Sample results show that the MMLP configuration improves resilience across disruptions by enabling intermodal flexibility, redistributing dependencies, and stabilizing critical assets. The method provides a generalizable tool for modelers and owner-operators seeking to evaluate resilience, security, and trust in advanced logistics systems.