Akademik Veri Yönetim Sistemi
OPERATIONS MANAGEMENT RESEARCH, cilt.19, sa.1, ss.1-19, 2026 (SSCI, Scopus)
Smart circular agri-food supply chains (SCAFSCs) are critical for sustainable growth and achieving the United Nations Sustainable Development Goals (SDGs). However, their development faces challenges, such as climate change, population growth, rising food demand, rapid technological advances, and labour, cost, and productivity issues. Integrating Artificial Intelligence (AI) into these systems can help address these issues. This study aims to identify and investigate the challenges of AI adoption in SCAFSCs in a developing country. To identify key challenges, this study used the Fermatean fuzzy Delphi (FF Delphi) method, along with a literature review and expert consensus. The relationships among these challenges were analysed using the Fermatean fuzzy decision-making trial and evaluation laboratory (FF DEMATEL) method. The findings were validated through sensitivity and Spearman's correlation analyses. The results indicate that a lack of adequate AI infrastructure, high costs of AI, and a lack of technical skills and expertise are major challenges to implementing AI in SCAFSCs in developing countries. Furthermore, ensuring security and privacy in AI-driven solutions, establishing regulatory frameworks, securing financial resources, and obtaining management support can facilitate AI adoption in SCAFSCs. The study's findings provide valuable insights for policymakers, managers, and practitioners seeking to enhance AI adoption in SCAFSCs.