Developing capabilities for supply chain resilience in a post-COVID world: A machine learning-based thematic analysis
本研究分析了1717篇供应链韧性论文，用机器学习方法将其归为11个主题簇，并识别出后疫情时代企业应重点建设的三种能力：互联性、可转换性和共享性，对管理者和学者均有指导意义。
This study examines the past, present, and future of Supply Chain Resilience (SCR) research in the context of COVID-19. Specifically, a total of 1717 papers in the SCR field are classified into 11 thematic clusters, which are subsequently verified by a supervised machine learning approach. Each cluster is then analyzed within the context of COVID-19, leading to the identification of three associated capabilities (i.e., interconnectedness, transformability, and sharing) on which firms should focus to build a more resilient supply chain in the post-COVID world. The derived insights offer invaluable guidance not only for practicing managers, but also for scholars as they design their future research projects related to SCR for greatest impact.