Resilience engineering frames operational continuity as the ability of a socio-technical system to sustain, adapt, and recover performance under disturbance, rather than only preventing failures in a narrow technical sense. Logistics operations are increasingly cyber-physical systems, because transport execution, warehouse automation, port and terminal workflows, and multi-party coordination depend on interconnected information systems, cloud services, and operational technology networks. This interdependence increases exposure to ransomware, malware, denial-of-service disruption, and intrusion events that can propagate across organisations and quickly become service-level agreement breaches, throughput collapse, and multi-node congestion effects. Real-world incidents in maritime logistics and freight forwarding show how cyber events can disrupt booking platforms, corporate and terminal systems, and operational processes at scale, with reported financial impacts reaching hundreds of millions of dollars in some cases. Traditional disaster recovery approaches can remain too IT-centric when they treat restoration as an application recovery problem, and not a system-level problem that joins IT, OT, and operational decision-making under time pressure.
This study develops a resilience engineering framework for disaster recovery and cyber-incident readiness in logistics operations, focused on modelling disruption propagation, quantifying operational impacts, and translating results into logistics-specific recovery playbooks and recovery targets. The research proposes a hybrid modelling approach combining dependency mapping and disruption simulation to examine cascading failure scenarios involving (i) ransomware disruption of coordination platforms, (ii) cloud or shared digital service unavailability, and (iii) compromise of OT or IoT networks that underpin warehouse and port automation. Empirical baselines from port container throughput statistics and sector threat distributions are used to ground scenario parameters and outputs, and a worked simulation illustrates how short-duration disruption can translate into large throughput losses when recovery is constrained by operational bottlenecks. The contribution is a practical cyber-physical resilience architecture for logistics, including measurement metrics, playbook structures, and benchmarks for recovery time and recovery point objectives aligned to operational continuity thresholds.