Measuring and Characterizing Global Value Chain Resilience in Chinese Industries: Trend Analysis and Intelligent Clustering

Against rising global uncertainty, understanding the evolution and structural patterns of global value chain (GVC) resilience is crucial for sustaining stable international production networks. However, existing research often relies on single-indicator or linear measurement approaches that are insufficient to capture the multidimensional and heterogeneous nature of GVC resilience. To address this gap, this study develops a comprehensive GVC resilience framework encompassing resistance, adjustment, and transformative dimensions. Using the OECD inter-country input-output data, we measure the resilience levels of 42 Chinese industries. Feature vectors capturing each industry’s long-term resilience profile of each industry are constructed, and three intelligent clustering algorithms—K-means++, Gaussian mixture model, and spectral clustering—are applied to identify latent grouping structures. The empirical results showed that (1) the evolution of GVC resilience displayed substantial heterogeneity across industries; (2) China exhibited relatively strong resilience in 2000, 2001, 2009, and 2020, but weaker performance in 2004, 2012, and 2017; (3) the integrated clustering outcomes classified industries into three groups—high resilience and low volatility, low resilience and high volatility, and medium resilience and declining trend.