Relative Efficiency Analysis of Green Technology Innovation in Global Decarbonization: An Application of the CCR Data Envelopment Analysis Model
世界の脱炭素化におけるグリーン技術革新の相対効率分析：CCRデータ包絡分析法の応用 (AI 翻訳)
Dr. D. VIMAL KUMAR
🤖 gxceed AI 要約
日本語
本研究は、CCRモデルに基づくDEAを用いて、グリーン技術革新が脱炭素化に貢献する効率性を国際比較した。R&D支出、再生可能エネルギーの特許、クリーンエネルギー投資を投入要素とし、炭素排出削減量と再生可能エネルギー発電量を産出として分析。結果、多くの国が最適フロンティア未満で非効率であり、技術格差と規模の非効率が原因であることを示した。政策含意として、単なる投資増加ではなく効率改善の重要性を強調。
English
This study uses a CCR-based DEA model to evaluate the efficiency of green technology innovation in global decarbonization across countries. Inputs include R&D expenditure, renewable energy patents, and clean energy investment; outputs are carbon emission reductions and renewable energy generation. Results show substantial inefficiencies, with many countries below the optimal frontier due to technological gaps and suboptimal scale. Policy implications stress that improving innovation efficiency is as critical as increasing investment.
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
日本はグリーンイノベーション投資を拡大しているが、本論文は効率性の視点から政策の最適化を示唆。SSBJや有報での気候関連開示において、技術投資の効率性評価が投資家対話に有用となる可能性がある。
In the global GX context
This paper provides a cross-country efficiency benchmarking framework relevant to global climate policy. It complements TCFD/ISSB disclosure by offering a metric for evaluating the effectiveness of green innovation investments, which can inform transition finance and corporate strategy.
👥 読者別の含意
🔬研究者:Offers a DEA-based methodology for assessing green innovation efficiency across countries, useful for comparative climate policy studies.
🏢実務担当者:Provides a benchmarking tool for companies to evaluate their green R&D efficiency relative to global frontiers.
🏛政策担当者:Highlights that increasing green investment alone is insufficient; efficiency improvements are crucial for decarbonization targets.
📄 Abstract（原文）
The transition toward a low-carbon global economy requires not only increased investment in green technologies but also improvements in the efficiency with which such innovations contribute to decarbonization. This study evaluates the efficiency of green technology innovation in promoting global decarbonization using a Data Envelopment Analysis (DEA) framework based on the Charnes–Cooper–Rhodes (CCR) model, which assumes constant returns to scale. Drawing on cross-country panel data, the study constructs an efficiency model incorporating green innovation inputs—such as research and development (R&D) expenditure, renewable energy patents, and clean energy investment—and desirable outputs including carbon emission reductions and renewable energy generation. The empirical analysis assesses relative efficiency across countries and identifies best-performing frontiers in transforming green technological inputs into decarbonization outcomes. The results reveal substantial heterogeneity in efficiency levels, with several economies operating below the optimal frontier, indicating untapped potential in leveraging green innovation for climate mitigation. Furthermore, scale efficiency decomposition highlights that both technological capability gaps and suboptimal innovation scale contribute to observed inefficiencies. The findings offer important policy implications. First, increasing investment in green innovation alone does not guarantee proportional decarbonization gains; improving innovation efficiency is equally critical. Second, countries can benefit from benchmarking against frontier economies to optimize resource allocation and institutional support mechanisms. Overall, this study contributes to the literature on climate policy and sustainable development by providing an efficiency-based perspective on the role of green technological innovation in achieving global decarbonization targets.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.19442357first seen 2026-05-05 19:11:38
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