Artificial Intelligence Empowers Sustainable Supply Chains
人工知能が持続可能なサプライチェーンを強化する (AI 翻訳)
X.F. Wang
🤖 gxceed AI 要約
日本語
持続可能なサプライチェーンにおける「効率性・環境保護・公平性」の課題に対し、AIがどのように貢献できるかを考察。需要予測、物流網最適化、リスク管理、サプライヤー管理、生産最適化、リアルタイム監視、カーボンフットプリント管理などの機能を提唱し、効率向上・コスト削減・レジリエンス強化を実現すると論じる。コンセプト中心のレビュー論文。
English
This paper examines how AI can empower sustainable supply chains, addressing efficiency-environmental protection-equity challenges. It identifies key AI capabilities such as demand forecasting, logistics optimization, risk management, supplier management, production optimization, real-time monitoring, and carbon footprint management. The authors argue AI improves efficiency, reduces costs, and enhances supply chain resilience.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本でもサプライチェーン排出量の算定・開示（Scope 3）やGX推進が課題であり、AIを活用した炭素管理やリスク監視は実務応用の可能性が高い。ただし本稿は概念整理に留まり、日本の制度設計への直接的な示唆は限定的。
In the global GX context
In the global context, this paper aligns with the growing demand for AI-driven tools in Scope 3 carbon disclosure and sustainable supply chain management under frameworks like CSRD and ISSB. It provides a conceptual framework for AI's role in carbon footprint management and emission reduction, though without empirical evidence. It contributes to the discourse on AI-enabled sustainability disclosure infrastructure.
👥 読者別の含意
🔬研究者:Provides a conceptual framework linking AI capabilities to supply chain sustainability, useful for structuring future empirical research on AI-enabled carbon accounting.
🏢実務担当者:Offers a checklist of AI applications (e.g., demand forecasting, carbon footprint management) that corporate sustainability teams can explore for supply chain decarbonization.
🏛政策担当者:Highlights the potential of AI to support supply chain sustainability, suggesting a rationale for policy incentives, though specific recommendations are absent.
📄 Abstract（原文）
With the continuous turbulence in the global market and the rapid development of artificial intelligence (AI), the sustainable development of supply chains has attracted significant attention. Addressing the "efficiency-environmental protection-equity" challenges faced by current sustainable supply chains, this paper attempts to analyze how AI can empower sustainable supply chains and explores AI's ability to handle the dynamic complexity of supply chains, including real-time data monitoring, accurate prediction, intelligent decision-making, risk management, data sharing, and continuous learning. The study finds that AI can empower sustainable supply chains through the following aspects: demand forecasting and inventory optimization, logistics network optimization, supply chain risk management, supplier management, production and manufacturing optimization, real-time monitoring and transparency, as well as carbon footprint management and emission reduction optimization. Through these means, AI helps improve supply chain efficiency, reduce costs, enhance forecasting and demand management capabilities, strengthen risk management and emergency response capabilities, and boost supply chain resilience.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.61453/intij.202555first seen 2026-08-02 18:01:15
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