Intelligent Assessment and Empirical Analysis of the Resilience of Shandong Province’s Manufacturing Industry Chain under the Impact of Tariff Policies
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Abstract
This paper develops an intelligent assessment framework for evaluating the resilience of Shandong Province’s manufacturing industry chain under tariff policy shocks by integrating a dynamic CGE model, industrial complex networks, and a random forest algorithm. Against the background of digital manufacturing and intelligent industrial systems, resilient production networks supported by reliable information transmission and sensing infrastructures are essential for stable industrial operation. The proposed framework quantifies the influence of tariff fluctuations on the structural stability and recovery capability of regional manufacturing clusters. Specifically, a dynamic CGE model based on the 2020 input-output table is established to simulate the macroeconomic transmission effects of tariff shocks ranging from 5% to 15%, while a directed weighted complex network identifies critical industrial links through node degree and betweenness centrality. Furthermore, a random forest model incorporating 20 economic and networkrelated variables predicts the dynamic evolution of resilience. The results show that tariff shocks reduce industry output by an average of 3.7%, with import-dependent sectors experiencing the greatest losses, while key hub industries play a dominant role in system stability. The resilience index exhibits a V-shaped recovery, improving from 0.52 to 0.68 within three years through enhanced R&D intensity and digitalization, providing quantitative support for intelligent industrial risk assessment and resilient manufacturing systems.
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