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Agentic AI and Circular Procurement Performance

An Empirical Study

Bibliographic Data

ID22418236
AuthorsSurajit Bag (0000-0002-2344-9551, Excelia Business School), Susmi Routray (0000-0002-9062-599X, Institute of Management Technology Ghaziabad Delhi‐NCR India), Andrea Chiarini (0000-0003-4915-5145, University of Verona Verona Italy, corresponding author), Rasem Qudaih (0009-0008-8988-8312, University of Suffolk Ipswich UK)
Year2026
Publication date2026-06-16
Open AccessYes
TypeARTICLE
VenueBusiness Strategy and the Environment (JOURNAL)
Journal identifiersISSN: 0964-4733 • E-ISSN: 1099-0836
PublisherWiley (PUBLISHER • GB)
DOI10.1002/bse.71149
OpenAlexW7164934445
LanguageEN
References cited75

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.

Empirical evidence · Empirical research · Procurement · Purchasing · Public Procurement and Policy · Supply Chain and Inventory Management · Sustainable Supply Chain Management

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