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Unleashing the Potential of Artificial Intelligence for Dynamic Supply Chain Optimization and Sustainability

Unleashing the Potential of Artificial Intelligence for Dynamic Supply Chain Optimization and Sustainability
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Author(s): Mirna Ibrahim (Ain Shams University, Egypt)
Copyright: 2024
Pages: 30
Source title: Navigating the Circular Age of a Sustainable Digital Revolution
Source Author(s)/Editor(s): Umair Tanveer (University of Exeter, UK & Ho Chi Minh City University of Economics and Finance, Ho Chi Minh City, Vietnam), Shamaila Ishaq (University of Derby, UK), Truong Quang Huy (RMIT University, Vietnam)and Thinh Gia Hoang (RMIT University, Vietnam)
DOI: 10.4018/979-8-3693-2827-9.ch013

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Abstract

Green supply chain management (GSCM) integrates environmental considerations into supply chain functions from product design to end-of-life management. This chapter examines the emerging applications of artificial intelligence (AI) for advancing sustainability across supply chain operations and decision-making. Specifically, it reviews the use of AI-powered analytics, optimization algorithms, machine learning systems, and distributed ledgers for enabling circular resource flows across global value chains. The chapter also critically evaluates the successes, limitations, risks, and ethical considerations of current AI applications in GSCM. Challenges related to data quality, algorithmic bias, job automation risks, and operational integration complexities are discussed, along with mitigation strategies. Case studies demonstrating AI's impact on solving real-world supply chain sustainability issues are incorporated. The chapter broadens the discussion to encompass economic, social, and environmental dimensions of sustainability, as well as AI's role in enhancing supply chain resilience.

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