Resilient maritime transportation system from the perspective of FRAM: conceptualization and assessment

The resilience-oriented maritime transportation system (MTS) is prioritized for global maritime transportation in the post-Pandemic. In this study, the resilient MTS is firstly conceptualized and decomposed into 6 aspects from the function perspective. Then, according to the principle of function resonance analysis method (FRAM), 19 functional elements are identified, and the coupling relations among these functional elements are also determined in the form of a directed topological network, in which the functional elements are represented by nodes. The identified functional elements are then mapped into a Bayesian network (BN), and the topological network obtained from FRAM analysis is considered a directed complex network (CN), which is subjective to the improved K-shell decomposition algorithm to determine the prior probability of the root nodes in BN. The conditional probability Tab.s required for simulating the BN model are calculated based on the probability distribution of the root nodes. Finally, the developed BN is simulated with AgenaRisk under the COVID-19 disruption scenario, and functional element importance is also investigated. The results show that the proposed methodology is characterized by the advantages of the FRAM being qualitative and the BN being quantitative with the bridge of CN analysis technique in terms of resilient MTS assessment.