Optimizing Sustainable Electronics Supply Chains Under Carbon Taxation and Fuzzy Demand: A Multi-Goal Programming Approach
炭素課税とファジー需要下における持続可能な電子機器サプライチェーンの最適化：多目標計画アプローチ (AI 翻訳)
Kuang-Yen Chung, Rong-Her Chiu
🤖 gxceed AI 要約
日本語
本研究は、炭素税と需要不確実性を考慮した電子機器サプライチェーンのグリーン計画モデルを提案する。ファジー多目標計画法により、経済性と環境目標のバランスを最適化。実証ケースで、炭素税とグリーン投資が排出削減と収益性維持に有効であることを示した。
English
This study proposes a fuzzy multi-goal optimization model for green supply chain planning under carbon taxation and demand uncertainty. Using a real electronics supply chain case, it demonstrates that carbon taxes and green investments reduce emissions while maintaining profitability, with sensitivity of ±10–20% across policies.
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
日本のGX政策では炭素価格導入が議論されており、本モデルは企業のサプライチェーン計画に実践的示唆を与える。特に電子機器産業は日本が強みを持つため、国内企業の脱炭素戦略策定に活用可能。
In the global GX context
As global carbon pricing expands (EU ETS, CBAM), this model offers a practical tool for supply chain managers to balance cost and emissions. It contributes to the growing literature on integrating green investments and reverse logistics under uncertainty.
👥 読者別の含意
🔬研究者:A multi-objective optimization framework for green supply chains under carbon tax and fuzzy demand, with a real-case validation.
🏢実務担当者:Actionable insights on setting green investment levels and logistics decisions to comply with carbon pricing while controlling costs.
🏛政策担当者:Evidence that well-designed carbon taxes and green investment incentives can reduce emissions without harming profitability.
📄 Abstract（原文）
The sustainable transformation of electronics supply chains (ESCs) increasingly relies on effective green supply chain planning under carbon pricing and demand uncertainty. However, prior studies often lack an integrated framework that jointly considers carbon taxation, green technology investment, and profitability—environment trade-offs in forward and reverse supply chains. To address this gap, this study proposes a fuzzy multi-goal optimization model using linear goal programming under progressive carbon taxation. The model incorporates fuzzy demand (triangular fuzzy numbers), carbon emissions, carbon taxes, and green investment costs and is converted into a solvable linear form via a defuzzification-based procedure to simultaneously achieve multiple aspiration levels for economic and environmental objectives. A real-world ESC case validates the model. The results show that carbon taxation and green investments can reduce emissions while maintaining profitability, with total cost and emission sensitivity of ±10–20% across different policies and demand uncertainty settings. The findings support adaptive, policy-aware planning by guiding green investment intensity and forward–reverse logistics decisions to balance cost efficiency and emissions reduction and provide actionable insights for managers facing progressive carbon pricing regulations.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/su18031686first seen 2026-05-15 17:07:10
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