グリーンサプライチェーンにおける在庫最適化研究の進展に関する分析
Analysis of Research Progress on Inventory Optimization in Green Supply Chain (原題)
Zi-Yi Pei, Qian-Zhong Lai
🤖 gxceed AI 要約
日本語
本論文は過去5年間のグリーンサプライチェーン在庫最適化研究を体系的にレビューした。従来の単一コスト最小化から、炭素排出量やサービス水準を含む多目的モデルへと拡張し、数理計画・知能最適化・シミュレーションが広く適用されている。製造業はクローズドループ在庫、EC・日用品はIoT・ビッグデータによる動的補充で低炭素運用を実現するが、炭素会計基準の不統一や社会性能・制度コストの欠如が課題として残る。
English
This paper systematically reviews five years of research on inventory optimization in green supply chains. Models have shifted from single cost minimization to multi-objective frameworks incorporating carbon emissions and service levels, using mathematical programming, intelligent optimization, and simulation. Manufacturing emphasizes closed-loop inventory, while e-commerce and FMCG rely on IoT and big data for dynamic low-carbon replenishment. Key gaps remain: inconsistent carbon accounting standards, neglected social performance and institutional costs, and weak upstream-downstream incentives.
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
日本企業のサプライチェーン排出量（Scope 3）管理やSSBJ開示に向け、在庫最適化と炭素会計を結びつける視点を提供する。特に炭素会計基準の不統一は、日本企業が国際的なScope 3算定・報告を行う上での実務的課題と直結する。
In the global GX context
This review speaks to global efforts to integrate carbon accounting into supply chain operations, relevant to Scope 3 disclosure under ISSB/CSRD and TCFD. It highlights the persistent challenge of inconsistent carbon accounting standards, which complicates comparability across jurisdictions and supply chain tiers.
👥 読者別の含意
🔬研究者:グリーンサプライチェーン在庫最適化の研究動向と未解決課題（炭素会計基準、社会性能、制度コスト）を整理するのに有用。
🏢実務担当者:在庫管理と炭素削減を両立させるモデル設計の参考になるが、実務適用には自社データでの検証が必要。
🏛政策担当者:炭素会計基準の統一やサプライチェーン上流下流のインセンティブ設計を検討する際の論点を提供する。
📄 Abstract（原文）
Against the backdrop of the "dual carbon" strategy and global sustainable development goals, optimizing green supply chain inventory has gradually become an important research topic in both academia and industry. This article provides a systematic review and overview of relevant research in the past five years. Research has found that traditional inventory optimization models have gradually expanded from a single cost minimization objective to simultaneously consider multidimensional objectives such as carbon emissions and service levels. In terms of methodology, mathematical programming, intelligent optimization algorithms, and simulation have been widely applied, and the introduction of uncertainty handling, policies, and financial factors has made the model more practical. In terms of industry applications, the manufacturing industry focuses on closed-loop inventory and recycling strategies, while the e-commerce and fast-moving consumer goods industries rely on the Internet of Things, big data, and dynamic replenishment technology to achieve high turnover and low-carbon operations. Despite some progress, existing research still faces issues such as inconsistent carbon accounting standards, lack of consideration for social performance and institutional implementation costs, and incomplete incentive mechanisms upstream and downstream. Based on this, this article proposes that future research should strengthen interdisciplinary integration and real data verification, explore supply chain collaboration mechanisms, interpretability of deep optimization, and effective integration of policies and practices, in order to promote the further development of green supply chain management theory and practice.
🔗 Provenance — このレコードを発見したソース
- semanticscholar http://tebmr.net/index.php/ojs/article/download/13/12first seen 2026-10-14 05:43:45
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