{"title":"Unveiling Dynamic Resilience on Sustainable Performance in Supply Chain: Artificial Intelligence, System Optimization and Information Transparency","authors":"Kuo-Jui Wu, Ming Han, Caiyan Huang, Hailing Qiu, Kanchana Sethanan, Ming-Lang Tseng","doi":"10.1111/jbl.70046","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Supply chain resilience (SCR) enhances the use of artificial intelligence, system optimization, and information transparency to facilitate the dynamics in sustainable supply chain performance improvement. Prior studies neglect system dynamics involvement to identify the dynamic changes. This study proposes a hybrid method for extracting real practices from the globally registered patents and extracts these variables by adopting bidirectional encoder representations of transformers. The results of comparing models based on different environmental data reveal that supply chain resilience does not reliably improve sustainable supply chain performance, especially during crises. Artificial intelligence is able to generate dynamics in the SCR. The resilient systems could be improved through system optimization and information transparency without artificial intelligence in both the before and after dynamic environments.</p>\n </div>","PeriodicalId":48090,"journal":{"name":"Journal of Business Logistics","volume":"46 4","pages":""},"PeriodicalIF":10.7000,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Logistics","FirstCategoryId":"91","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jbl.70046","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
Supply chain resilience (SCR) enhances the use of artificial intelligence, system optimization, and information transparency to facilitate the dynamics in sustainable supply chain performance improvement. Prior studies neglect system dynamics involvement to identify the dynamic changes. This study proposes a hybrid method for extracting real practices from the globally registered patents and extracts these variables by adopting bidirectional encoder representations of transformers. The results of comparing models based on different environmental data reveal that supply chain resilience does not reliably improve sustainable supply chain performance, especially during crises. Artificial intelligence is able to generate dynamics in the SCR. The resilient systems could be improved through system optimization and information transparency without artificial intelligence in both the before and after dynamic environments.
期刊介绍：
Supply chain management and logistics processes play a crucial role in the success of businesses, both in terms of operations, strategy, and finances. To gain a deep understanding of these processes, it is essential to explore academic literature such as The Journal of Business Logistics. This journal serves as a scholarly platform for sharing original ideas, research findings, and effective strategies in the field of logistics and supply chain management. By providing innovative insights and research-driven knowledge, it equips organizations with the necessary tools to navigate the ever-changing business environment.
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