Rahal, Imene and Khalifa, zayed (2025): AI-EcoSCM: A Lean and Agile Framework for Economic Excellence.
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Abstract
This paper explores the emerging framework of AI-driven Economic Supply Chain Management (EcoSCM), which adapts industrial supply chain optimization and artificial intelligence (AI) principles to the management of economic systems and institutions. EcoSCM emphasizes the systematic coordination of financial, administrative, and technological processes to deliver efficient, adaptive, and data-driven economic ecosystems. The study highlights how Lean principles (waste elimination, continuous improvement) enhance operational efficiency, while Agile principles promote flexibility and responsiveness to rapidly changing market and policy environments. In addition, AI integration—through predictive modeling, data analytics, and intelligent automation—provides real-time insights, informed decision-making, and enhanced economic intelligence. The paper proposes Lean, Agile, and AI Scoring Models to evaluate institutional maturity across efficiency, adaptability, and intelligence dimensions. By aligning Lean efficiency, Agile flexibility, and AI-driven intelligence, EcoSCM establishes a Smart Leagile paradigm capable of sustaining innovation, quality assurance, and digital transformation in the economic sector. Keywords: Economic Supply Chain Management (EcoSCM); Lean–Agile Economy; Artificial Intelligence (AI); Smart Economics; Sustainable Growth.
| Item Type: | MPRA Paper |
|---|---|
| Original Title: | AI-EcoSCM: A Lean and Agile Framework for Economic Excellence |
| Language: | English |
| Keywords: | Economic Supply Chain Management (EcoSCM); Lean–Agile Economy; Artificial Intelligence (AI); Smart Economics; Sustainable Growth. |
| Subjects: | O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights |
| Item ID: | 126740 |
| Depositing User: | I RAHAL Imen RAHAL |
| Date Deposited: | 19 Nov 2025 04:31 |
| Last Modified: | 19 Nov 2025 04:31 |
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| URI: | https://mpra.ub.uni-muenchen.de/id/eprint/126740 |

