gxceed
← 論文一覧に戻る

Digitalization and Sustainable Industrial Low-Carbon Transformation: Synergistic Effects, Policy Tools, Technical Pathways, and Financial Innovation

デジタル化と持続可能な産業低炭素転換:相乗効果、政策手段、技術経路、金融イノベーション (AI 翻訳)

Wei Cai, Sufian Jusoh, Xiaoguang Yue

Sustainabilityプレプリント2026-02-01#政策Origin: CN
DOI: 10.3390/su18031433
原典: https://doi.org/10.3390/su18031433

🤖 gxceed AI 要約

日本語

本研究は、中国長江デルタの製造業データを用いて、デジタル化が政策、技術、金融の相乗効果を通じて産業低炭素転換を促進することを実証。排出量取引とグリーンクレジットの組み合わせにより脱炭素コストが18~23%削減され、デジタルツインやIoTなどの技術が業種別に効果を発揮する。また、デジタル化がリアルタイムのMRVを強化し、持続可能性ガバナンスを向上させることを示した。

English

This study empirically demonstrates how digitalization enables industrial low-carbon transformation through synergistic interactions of policy, technology, and finance, using panel data from China's Yangtze River Delta manufacturing firms. Coordinated policy instruments (emissions trading, green credit) reduce decarbonization costs by 18-23%, while digital technologies like digital twins and IoT cut emissions by 12% in steel and 9.7% in textiles. Digitalization also strengthens real-time carbon MRV, improving sustainability governance.

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

中国の事例ではあるが、デジタルMRVや政策連携のフレームワークは、日本のSSBJ対応やグリーン成長戦略にも示唆を与える。特に、複数政策の組み合わせ効果やデジタル技術の活用方法は、日本企業の脱炭素経営に参考となる。

In the global GX context

This paper provides robust empirical evidence on how digitalization can amplify the effectiveness of decarbonization policies and financial instruments, relevant to global frameworks like TCFD and ISSB that emphasize data-driven disclosure and MRV. The quantified synergistic effects offer actionable insights for designing integrated climate policies and scalable digital solutions.

👥 読者別の含意

🔬研究者:Researchers can adopt the mixed-method approach combining econometric analysis and case studies to examine policy-technology-finance synergies in other contexts.

🏢実務担当者:Practitioners can apply identified digital tools (digital twins, IoT) and policy mixes (ETS, green credit) to enhance their decarbonization strategies and reduce costs.

🏛政策担当者:Policymakers should note the quantified cost reductions from coordinated instruments and the role of digital MRV in improving policy precision and enforcement.

📄 Abstract(原文)

In the context of the growing urgency of sustainable industrial transformation under global climate goals, this study examines how digitalization enables and amplifies industrial low-carbon transition through the synergistic interaction of policy tools, technological pathways, and financial innovation. Addressing the challenge of reconciling emissions reduction with industrial efficiency, the study employs a mixed-method approach that combines panel econometric analysis of manufacturing enterprises in China’s Yangtze River Delta with representative case studies. The empirical results demonstrate significant synergistic effects among policy, technology, and finance under digital enablement. Coordinated policy instruments, including emissions trading and green credit, reduce decarbonization costs by 18–23%, while digitally enabled mechanisms such as Zhejiang’s “Carbon Efficiency Code” lower carbon intensity by over 15% for nearly half of participating firms. Technological pathways exhibit sectoral heterogeneity: digital twin optimization reduces emissions by 12% in the steel industry, whereas IoT-based monitoring cuts energy consumption by 9.7% in textiles. Financial innovations further reinforce these outcomes by increasing green R&D intensity and enhancing firms’ climate risk resilience. From a sustainability perspective, the study shows that digitalization strengthens real-time carbon measurement, monitoring, and verification (MRV), thereby improving sustainability performance assessment and governance effectiveness. By integrating digital tools with policy and financial incentives, the findings provide actionable guidance for supporting sustainable industrial operations and designing more precise, scalable, and data-driven sustainability-oriented policy instruments.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。