A methodology to model the evolution of system resilience for Arctic shipping from the perspective of complexity

Resilience theory is introduced in the present study to model the capability of the Arctic shipping system to defend against various risks. For this purpose, a novel methodology integrating a Bayesian network (BN), system dynamics (SD), and dissipative structure is proposed to quantitatively describe the dynamic resilience of the Arctic shipping system. The evolution of the system resilience with time is simulated, based on which the graphical results and discussion are devoted to revealing the dynamic evolution mechanism by integrating the three aspects of triggering conditions, priorities, and driving forces. Overall, the proposed resilience evolution model is suitable for complex systems with uncertainty and nonlinearity, and the results show that the proposed methodology can contribute to formulating future strategies and decisions to guarantee the safety of Arctic shipping.