Improving accuracy and visibility in the supply chain to reduce scope 3 carbon emissions in food sector companies
食品セクター企業におけるスコープ3炭素排出削減のためのサプライチェーンの精度と可視性の向上 (AI 翻訳)
Deó de Urquía, Inés
🤖 gxceed AI 要約
日本語
食品産業のScope3排出量は全体の80%超を占めるが、データ精度・透明性・検証に課題がある。文献レビューで9つの課題を特定し、Fuzzy-TISMとFuzzy MICMACで階層モデルと依存・影響力を分析。最も重要な課題は複雑なサプライチェーンと排出源の特定であり、これらへの優先的対応がScope3算定の精度向上に必要と結論づけた。
English
Scope 3 accounts for over 80% of food sector emissions but faces data accuracy, transparency and verification challenges. Using Fuzzy-TISM and Fuzzy MICMAC, the authors model nine obstacles and identify complex supply chains and emission source identification as the most critical. Effective Scope 3 strategies must prioritize these two challenges.
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SSBJ基準の適用が始まり、Scope3算定の精度と可視性が投資家対応の焦点となっている。食品産業は川上農家から川下小売までサプライチェーンが長く、本分析の階層モデルは経営層の優先順位づけに有用。
In the global GX context
With ISSB S2 and CSRD requiring Scope 3 disclosure, food companies globally struggle with supply chain data. Fuzzy-TISM provides a structured prioritization of barriers useful for disclosure teams and standard-setters.
👥 読者別の含意
🔬研究者:Provides a barrier hierarchy and causal structure for Scope 3 accounting in complex supply chains, useful for further empirical validation.
🏢実務担当者:Helps sustainability teams prioritize supply chain complexity and emission source identification when improving Scope 3 calculation.
🏛政策担当者:Suggests standardization and supplier engagement remain critical barriers needing policy support.
📄 Abstract（原文）
The agricultural industry is an important contributor to global carbon emissions, with Scope 3 emissions comprising more than 80% of the total. The accurate determination of these emissions is extremely difficult due to challenges with data accuracy, transparency, and verification. The objective of this investigation is to improve the transparency and precision of Scope 3 emissions calculations by addressing the primary obstacles that have been identified in the literature. The nine challenges identified in the literature review are as follows: the complex supply chain, emission sources, tool availability, data collection, data quality, the need for standardisation, data divergence, incomplete reporting, and supplier engagement. This research utilises Fuzzy Total Interpretive Structural Modelling (Fuzzy-TISM) to develop a hierarchical model that demonstrates the interconnections of these challenges to support top management in developing effective strategies. Furthermore, the dependence and driving power of these problems are ranked and mapped using Fuzzy MICMAC analysis. The results indicate that the most significant challenges are the intricate supply chain and emission sources. Improving the accuracy and transparency of Scope 3 emissions calculations needs to address these primary challenges. As a result, effective management strategies must prioritise the precise identification of emission sources and the resolution of the supply chain's complexity.
🔗 Provenance — このレコードを発見したソース
- openalex https://hdl.handle.net/2117/439742first seen 2026-08-02 19:08:15
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