Unveiling Dynamic Resilience on Sustainable Performance in Supply Chain: Artificial Intelligence, System Optimization and Information Transparency

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.