Agentic AI and Circular Procurement Performance: An Empirical Study
研究代理型AI在工业采购中的应用如何提升循环采购绩效，发现三个关键前提条件，对采购经理制定政策有参考价值。
ABSTRACT Organizations that practice circular procurement in this rapidly changing world face many uncertainties. However, emerging digital technologies, such as agentic AI, can help manage resources and improve responsiveness to better serve both internal and external customers. Drawing on resource‐orchestration theory, this study aims to understand the impact of adopting agentic AI in industrial purchasing on circular procurement performance. Data for this study were collected from a developing nation, and the analysis was conducted using covariance‐based SEM and a Process analytical method. The results show that firms are most likely to benefit from agentic AI adoption when three prerequisites are present: (i) structured resource scanning and evaluation processes, (ii) integrated cross‐functional procurement systems, and (iii) established supplier collaboration routines. This study is the first to theorize the relationship between organizations' agentic AI adoption and circular procurement performance. The findings will help purchasing and supply managers formulate policies and standard operating procedures to effectively manage circular procurement performance in this rapidly changing world.