デジタルツインによる低炭素ビジネスモデル革新とESG成果：アジア製造業の事例から
Digital Twin-Enabled Low-Carbon Business Model Innovation and ESG Outcomes: Evidence from Asian Manufacturing Cases (原題)
Yuzhang Wang
🤖 gxceed AI 要約
日本語
ハイアール青島工場、シーメンス成都工場、LG昌原スマートパークの3事例を通じ、デジタルツインが低炭素ビジネスモデルとESG成果にどう結びつくかを分析。動的ケイパビリティ理論とNRBVを用い、情報提供・経営判断・業務ルーティン・顧客価値の変化を追跡する。エネルギー・炭素・材料・廃棄物では効果が確認されるが、社会・ガバナンス面は職場慣行やデータ管理に依存し不均一。デジタルツイン単独では不十分で、補完投資・組織変革・信頼できるデータが不可欠と結論づける。
English
Three Asian manufacturing cases (Haier Qingdao, Siemens Chengdu, LG Changwon) show how digital twins translate into low-carbon business model change and ESG outcomes. Using dynamic capabilities and NRBV, the paper traces information flows, managerial routines, and customer value. Energy, carbon, materials and waste show the strongest effects; social and governance outcomes are uneven and depend on work arrangements and data governance. Digital twins alone are insufficient—complementary investment, organizational change, and reliable data are required.
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
日本企業がデジタルツインやスマートファクトリーを導入する際、ESG開示（SSBJ・統合報告書）にどう接続するかの示唆を与える。特にスコープ1・2削減と生産性向上の関係、データガバナンスの重要性は、有報や投資家対応を進める日本製造業に実務的示唆が大きい。
In the global GX context
As global manufacturers adopt digital twins for decarbonization, this paper cautions that digitalization alone does not guarantee ESG outcomes. It adds empirical nuance to ISSB/CSRD disclosure debates by showing which environmental metrics improve and which social/governance metrics remain uneven, relevant for transition finance and climate-risk reporting.
👥 読者別の含意
🔬研究者:デジタルツインとESG成果の因果関係を動的ケイパビリティ理論で説明する実証枠組みを提供する。
🏢実務担当者:デジタルツイン導入時に、補完投資・組織変革・データガバナンスを同時に設計しないとESG成果が確認できない点を実務計画に活かせる。
🏛政策担当者:製造業のデジタル化と脱炭素を結びつける政策設計では、技術導入だけでなく組織・データ基盤への支援が必要であることを示唆する。
📄 Abstract（原文）
Digital twins are now used for more things than before, not only engineering design and maintenance. In many factories, it is being integrated with energy systems, product development tools, and supply chain platforms. However, a factory can be highly digital, yet its business model may remain largely unchanged. This paper examines this problem through three manufacturing cases in Asia: Haier interconnected washing-machine factory in Qingdao, Siemens Chengdu plant, and LG Smart Park in Changwon. Dynamic capabilities theory and natural-resource-based view are used to explain the cases. The analysis mainly looks at what information the twin provides, how managers use this information, what routines are changed, and whether the change affects customer value, delivery activities, or the way economic returns are captured. The three companies do not follow a single path. Haier put digital information into order-driven mass customization. Siemens connects factory and product twins with eco-design and internal testing of solutions. LG first builds flexible production, then some practices are copied to other plants, and later part of this capability is sold to outside customers. The strongest evidence concerns energy, carbon emissions, materials, and waste. Social and governance evidence is more uneven, as it depends heavily on work arrangements, data rules, and management. The cases show that a digital twin alone is not sufficient. It requires complementary investment, organizational change, and sufficiently reliable data; otherwise, low-carbon business model change and ESG outcomes are difficult to confirm. Also, better production efficiency does not always mean better ESG outcomes in the long term.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.68322/ajsid.50first seen 2026-09-22 04:38:13
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