Research on Resilience Evaluation of Coal Industrial Chain and Supply Chain Based on Interval Type-2F-PT-TOPSIS

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Abstract

As unexpected events such as natural disasters, the COVID-19 pandemic, and overseas containment have caused inevitable shocks to the energy industrial chain and supply chain, the current global energy crisis is intensifying, and different countries and regions have adopted different strategies according to the characteristics of their own national resource endowments in order to cope with energy security. Maintaining the security of the coal industrial chain and supply chain is a prerequisite for energy security to be effectively ensured, considering the main position of coal in China’s energy. Therefore, in the face of multiple uncertain risk factors under today’s momentous changes, this paper constructs an industrial coal chain and supply chain resilience evaluation indicator system from the perspective of resilience, based on four representational capabilities of resilience, namely preparedness, absorptive capacity, recovery capacity, and adaptability, in order to profoundly understand and enhance the resilience of the coal industrial chain and supply chain. An integrated method combining Interval Type-2 Fuzzy Prospect Theory and Technique for Order Preference by Similarity to an Ideal Solution (Interval Type-2F-PT-TOPSIS) is proposed for evaluating the resilience level of the coal industrial chain and supply chain. In the case of Shaanxi Province in China, it was found that the worst level of resilience of the coal industrial chain and supply chain in Shaanxi Province was in 2018, and the best was in 2021. Finally, based on the evaluation results, recommendations are provided to the key nodes of the industrial chain and supply chain in Shaanxi Province with a view to improving their resilience levels to cope with uncertain risks.

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Wu, A., Sun, Y., Zhang, H., Sun, L., Wang, X., & Li, B. (2023). Research on Resilience Evaluation of Coal Industrial Chain and Supply Chain Based on Interval Type-2F-PT-TOPSIS. Processes, 11(2). https://doi.org/10.3390/pr11020566

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