{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T16:05:48Z","timestamp":1779206748645,"version":"3.51.4"},"reference-count":28,"publisher":"Fuji Technology Press Ltd.","issue":"3","funder":[{"DOI":"10.13039\/501100012325","name":"National Office for Philosophy and Social Sciences","doi-asserted-by":"publisher","award":["24XJY013"],"award-info":[{"award-number":["24XJY013"]}],"id":[{"id":"10.13039\/501100012325","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Fujian Provincial Social Science Fund","award":["FJ2023B063"],"award-info":[{"award-number":["FJ2023B063"]}]},{"name":"Fujian Provincial Natural Science Fund","award":["2023J01926"],"award-info":[{"award-number":["2023J01926"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JACIII","J. Adv. Comput. Intell. Intell. Inform."],"published-print":{"date-parts":[[2026,5,20]]},"abstract":"<jats:p>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\u2019s long-term resilience profile of each industry are constructed, and three intelligent clustering algorithms\u2014K-means++, Gaussian mixture model, and spectral clustering\u2014are 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\u2014high resilience and low volatility, low resilience and high volatility, and medium resilience and declining trend.<\/jats:p>","DOI":"10.20965\/jaciii.2026.p0940","type":"journal-article","created":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T15:02:09Z","timestamp":1779202929000},"page":"940-950","source":"Crossref","is-referenced-by-count":0,"title":["Measuring and Characterizing Global Value Chain Resilience in Chinese Industries: Trend Analysis and Intelligent Clustering"],"prefix":"10.20965","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-5152-9395","authenticated-orcid":true,"given":"Linhui","family":"Zhao","sequence":"first","affiliation":[{"name":"Institute of Quantitative Economics and Statistics, Huaqiao University, No.668 Jimei Avenue, Jimei District, Xiamen, Fujian 361021, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanfang","family":"Lyu","sequence":"additional","affiliation":[{"name":"School of Economics, Guangdong University of Technology, No.161 Yinglong Road, Tianhe District, Guangzhou, Guangdong 510520, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Business, Minnan Normal University, No.36 Xianqianzhi Street, Xiangcheng District, Zhangzhou, Fujian 363000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"8550","published-online":{"date-parts":[[2026,5,20]]},"reference":[{"key":"key-10.20965\/jaciii.2026.p0940-1","doi-asserted-by":"crossref","unstructured":"I. 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Martin, \u201cRegional economic resilience, hysteresis and recessionary shocks,\u201d J. of Economic Geography, Vol.12, No.1, pp. 1-32, 2012. https:\/\/doi.org\/10.1093\/jeg\/lbr019","DOI":"10.1093\/jeg\/lbr019"},{"key":"key-10.20965\/jaciii.2026.p0940-8","doi-asserted-by":"crossref","unstructured":"R. Baldwin, R. Freeman, and A. Theodorakopoulos, \u201cHidden exposure: Measuring US supply chain reliance,\u201d National Bureau of Economic Research (NBER) Working Paper, No.31820, 2023. https:\/\/doi.org\/10.3386\/w31820","DOI":"10.3386\/w31820"},{"key":"key-10.20965\/jaciii.2026.p0940-9","doi-asserted-by":"crossref","unstructured":"L. Statsenko, R. S. Jayasinghe, and C. Soosay, \u201cSupply network resilience capabilities: A social-ecological perspective,\u201d Supply Chain Management, Vol.29, No.1, pp. 1-26, 2024. https:\/\/doi.org\/10.1108\/SCM-11-2022-0438","DOI":"10.1108\/SCM-11-2022-0438"},{"key":"key-10.20965\/jaciii.2026.p0940-10","doi-asserted-by":"crossref","unstructured":"M. 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