A Bayesian network and DEMATEL-ISM based approach for evaluating resilience: A case study in inland waterway port

Ports are critical nodes in the global maritime transportation system, as they facilitate a significant portion of the world's trade. However, their central role makes them highly vulnerable to disruptions, which can cascade into severe socio-economic impacts. Despite the recognized importance of resilience, existing models often overlook the comprehensive quantification of interactions between resilience strategies and port disruptions. This paper addresses this gap by proposing a hybrid methodology that combines Bayesian Networks, Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Interpretive Structural Modeling (ISM). The methodology systematically evaluates cause-and-effect relationships within and across resilience strategies categorized into absorptive, adaptive, and restorative capacities. Through the application of this model to a port terminal in northern Colombia, we identified 19 resilience strategies and demonstrated that adaptive and restorative capacities have a more significant impact on port resilience than absorptive capacity. Our findings reveal that interactions among strategies play a crucial role in resilience measurement; neglecting these interdependencies leads to underestimations that can result in misallocated resources and suboptimal preparation. This scalable framework provides decision-makers with a structured tool to prioritize investments in resilience strategies that yield the most significant impact, particularly when resources are limited.