Ghadami, Arash, Abdsharafat, Mahdi, Rostamzadeh, Reza, Isavi, Hero. (1404). AI-Powered Supply Chains: Mapping the Future of Resilience and Sustainability. , 18(2), 208-236. doi: 10.22059/imj.2026.410606.1008286
Arash Ghadami; Mahdi Abdsharafat; Reza Rostamzadeh; Hero Isavi. "AI-Powered Supply Chains: Mapping the Future of Resilience and Sustainability". , 18, 2, 1404, 208-236. doi: 10.22059/imj.2026.410606.1008286
Ghadami, Arash, Abdsharafat, Mahdi, Rostamzadeh, Reza, Isavi, Hero. (1404). 'AI-Powered Supply Chains: Mapping the Future of Resilience and Sustainability', , 18(2), pp. 208-236. doi: 10.22059/imj.2026.410606.1008286
Ghadami, Arash, Abdsharafat, Mahdi, Rostamzadeh, Reza, Isavi, Hero. AI-Powered Supply Chains: Mapping the Future of Resilience and Sustainability. , 1404; 18(2): 208-236. doi: 10.22059/imj.2026.410606.1008286

AI-Powered Supply Chains: Mapping the Future of Resilience and Sustainability

Industrial Management Journal
دوره 18، شماره 2، 2026، صفحه 208-236    اصل مقاله (1.53 M)
نوع مقاله: Original Research Article
شناسه دیجیتال (DOI): 10.22059/imj.2026.410606.1008286
نویسندگان
Arash Ghadami1؛ Mahdi Abdsharafat1؛ Reza Rostamzadeh* 2؛ Hero Isavi3
1Ph.D. Candidate, Department of Management, Urmia Branch, Islamic Azad University, Urmia, Iran.
2Associate Prof., Department of Management, Ur. C., Islamic Azad University, Urmia, Iran.
3Assistant Prof., Department of Management, Urmia Branch, Islamic Azad University, Urmia, Iran.
چکیده
Objective: This study aims to present a bibliometric mapping of artificial intelligence applications in supply chain management.
Methodology: Performance analysis and scientific mapping are used based on 805 Scopus-indexed journal articles published between 1996 and 15 March 2025.Three research questions are formulated to guide the analysis concerning disciplinary priorities, thematic structure, and international collaboration.
Results: we document a marked post-2020 acceleration in publications and citations, identify leading sources and authors, and reveal four interconnected thematic clusters: methodological foundations, digital infrastructures, application and resilience foci, and emerging topics. While resilience and sustainability emerge as salient application lenses within the corpus, our contribution is descriptive and explanatory rather than predictive.
Conclusion: The study clarifies conceptual contours, highlights collaboration hubs led by the United States, India, and China, and delineates gaps that motivate future work on data governance, technical integration, and evaluation across sectors.
کلیدواژه‌ها
Artificial intelligence؛ supply chain management؛ bibliometric analysis؛ machine learning؛ digital twins؛ sustainability
مراجع
آمار
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