TY - M-10237
AU - Onomakpo Onomakpo, Henry
TI - AI-Enabled Regenerative Supply Chains: A RSSCM Framework
T2 - Scientific Research Journal of Business, Management and Accounting

PY - 2025
VL - 3
IS - 1
SN - 2584-0592

AB - Addressing a critical gap in sustainable supply chain management (SCM), this study develops and proposes the comprehensive Regenerative Sustainable Supply Chain Management (RSSCM) framework. Synthesized from a systematic literature review and bibliometric analysis of contemporary research, the study identified the essential need to integrate AI-driven optimization, robust resilience strategies, circular economy principles, and ethical governance to achieve actively regenerative outcomes. The resulting RSSCM framework structures these critical components into Optimization, Resilience, and Regeneration pillars, all underpinned by a foundational Governance and Validation layer. This integrated model advocates for strategic digital technology application (AI, IoT) to drive efficiency, resilience, and sustainability, promoting a necessary paradigm shift towards supply chains generating net positive environmental and social impacts. The research provides practitioners with a structured roadmap for transformative change and offers academics a theoretically grounded framework for future inquiry, ultimately advancing progress towards more sustainable and equitable global supply networks.

KW - Supply Chain Management
KW -  Sustainable Supply Chain
KW -  Resilience
KW -  Regenerative Supply Chain
KW -  Circular Economy
KW -  Artificial Intelligence
KW -  Digital Technologies
KW -  Bibliometric Analysis
KW -  Literature Review
KW -  Framework Development.
DO -