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アルゴリズム的サステナビリティ:伝統的テキスタイルにおける炭素回避と製品寿命に基づくシルククレジットの数理モデル開発

Algorithmic Sustainability: Developing A Mathematical Model for Silk Credits Based On Carbon Avoidance And Product Longevity In Artisanal Textiles (原題)

Phuong Nguyen Minh, Quan Nguyen Van

Journal of Economics Finance and Management Studies📚 査読済 / ジャーナル2026-10-03#炭素会計Origin: JP経営インパクト: 資金調達対象セクター: textiles
DOI: 10.47191/jefms/v9-i10-01
原典: https://doi.org/10.47191/jefms/v9-i10-01

🤖 gxceed AI 要約

日本語

本論文は、非工業的生産による低炭素な伝統的シルク生産者が炭素金融から排除されている課題に対し、炭素回避(CA)と寿命係数(LF)を統合した「シルククレジット(SC)」の数理モデルを提案する。Entropy-AHPハイブリッド重み付けとTriple Bottom Line理論に基づき、ハノイ近郊3村でのサーベイ設計を通じて運用可能性を示す。SC指数と消費者の支払意欲・アルゴリズム検証への信頼との正の関係を提示し、従来型カーボンクレジットに代わる透明な枠組みを提供する。

English

This paper proposes a mathematical 'Silk Credit' (SC) model integrating carbon avoidance (CA) and a longevity factor (LF) via hybrid Entropy-AHP weighting, grounded in Triple Bottom Line theory. Using a survey design across three artisanal silk-weaving villages near Hanoi, it demonstrates operational feasibility and a plausible positive link between SC scores, consumer willingness to pay, and trust in algorithmic verification. It offers a transparent, survey-grounded alternative to conventional carbon crediting for non-industrialized textile production.

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

日本の伝統産業(西陣織・結城紬等)や中小製造業がScope3・製品寿命評価を通じて炭素金融へ参入する際の方法論的示唆を含む。SSBJ開示やサプライチェーン排出量算定における非工業的生産の扱いを考える上で参考になる。

In the global GX context

Speaks to global debates on baseline integrity in voluntary carbon markets and the operationalization of product longevity within crediting frameworks. Relevant to ISSB/CSRD supply-chain disclosure and emerging methodologies for valuing durability and avoided emissions in artisanal or SME production.

👥 読者別の含意

🔬研究者:炭素クレジットのベースライン設定と製品寿命変数の統合に関する複合指標構築の方法論的参考になる。

🏢実務担当者:伝統産業・中小企業が自社の低炭素性と製品耐久性を定量化し、炭素金融や差別化に活用する枠組みのヒント。

🏛政策担当者:非工業的生産セクターを炭素金融に包摂する際の、透明性ある算定・検証手法設計の論点を提供する。

📄 Abstract(原文)

The global textile industry faces mounting pressure to substantiate its environmental claims, yet artisanal silk producers despite their comparatively low-carbon, non-industrialized production methods, still remain largely excluded from formal carbon finance mechanisms. This gap is compounded by two unresolved methodological problems when voluntary carbon credit markets have been shown to systematically overstate achieved emission reductions due to non-conservative baseline-setting, and product longevity, despite being identified as a major lever for reducing the environmental footprint of textiles, is rarely operationalized as a quantifiable variable within existing crediting frameworks. This paper develops a basic mathematical model termed the Silk Credit (SC) that integrates two components, carbon avoidance (CA) and a longevity factor (LF), combined through a hybrid Entropy-AHP weighting scheme (SC = w1 x CA + w2 x LF), grounded in Triple Bottom Line theory and composite-indicator construction methods. A survey-based research design is proposed to operationalize the model across three artisanal silk-weaving villages in Hanoi (Van Phuc, La Khe, and Phung Xa) collecting primary activity data from producing households and willingness-to-pay data from consumers, with reliability assessed via Cronbach's alpha and hypothesis testing conducted through multiple regression and PLS-SEM. An application of the model demonstrates its operational feasibility, showing differentiated SC scores across villages and a statistically plausible positive relationship between the SC index, consumer willingness to pay, and trust in algorithmic verification. The study contributes a transparent, survey-grounded alternative to conventional carbon crediting approaches and offers a replicable framework for valuing environmental and durability performance in artisanal, non-industrialized textile production. Theoretical, policy, and practical implications are discussed, along with the study's limitations and directions for empirical validation.

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