{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T17:52:59Z","timestamp":1769017979512,"version":"3.49.0"},"reference-count":92,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T00:00:00Z","timestamp":1741651200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>In recent years, the rapid advancement of digital technologies and the growing demand for sustainability have driven unprecedented transformations in the automotive industry, particularly toward electric vehicles (EVs) and renewable energy. The EV supply chain, a complex global network, has become increasingly vulnerable to globalization and frequent \u201cblack swan\u201d events. The purpose of this study, grounded in organizational information processing theory, aims to systematically examine the role of digital capability in strengthening supply chain resilience (SCR) through improved risk management effectiveness. Specifically, it explores the multidimensional nature of digital capability, clarifies its distinct impact on SCR, and addresses existing research gaps in this domain. To achieve this, this study develops a theoretical framework and validates it using survey data collected from 249 EV supply chain enterprises in China. Partial Least Squares Structural Equation Modeling (PLS-SEM) is employed to empirically test the proposed relationships. The findings provide valuable theoretical insights and actionable guidance for EV manufacturers seeking to leverage digital transformation to mitigate risks effectively and enhance supply chain resilience. However, as the study focuses on Chinese EV supply chain enterprises, caution is needed when generalizing the findings to other regions. Future research could extend this investigation to different markets, such as to Europe and the United States, to explore potential variations.<\/jats:p>","DOI":"10.3390\/fi17030123","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T10:04:51Z","timestamp":1741687491000},"page":"123","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["How Does Digital Capability Shape Resilient Supply Chains?\u2014Evidence from China\u2019s Electric Vehicle Manufacturing Industry"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3170-9409","authenticated-orcid":false,"given":"Yanxuan","family":"Li","sequence":"first","affiliation":[{"name":"College of Traffic and Transportation, Nanning University, Nanning 530200, China"},{"name":"Faculty of Logistics and Digital Supply Chain, Naresuan University, Phitsanulok 65000, Thailand"}]},{"given":"Vatcharapol","family":"Sukhotu","sequence":"additional","affiliation":[{"name":"Faculty of Logistics and Digital Supply Chain, Naresuan University, Phitsanulok 65000, Thailand"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6205","DOI":"10.1109\/TEM.2023.3254435","article-title":"Result of Digitalization in the Automotive Industry: Total Equipment Effectiveness and Bayesian Analysis","volume":"71","author":"Argun","year":"2024","journal-title":"IEEE Trans. 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