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モデルを用いたDEAにより、グリーン技術革新の脱炭素効率を国際比較。R&D支出、再生可能エネルギーパテント、クリーンエネルギー投資を投入、CO2削減量と再生可能エネルギー発電量を産出として分析。多くの国が最適フロンティア未満で、技術ギャップと規模の非効率が原因。投資増加だけでなく効率改善が重要と示唆。
English
This study uses a CCR 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 heterogeneity, with many countries below the optimal frontier due to technological gaps and suboptimal scale. Policy implications emphasize improving innovation efficiency alongside 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GX投資拡大中だが、本論文は投資効率の重要性を指摘。SSBJや有報でのGX指標設計や、グリーン技術の効果検証に示唆を与える。
In the global GX context
This paper provides a cross-country efficiency benchmark for green innovation, relevant to global climate policy discussions. It highlights that simply increasing investment is insufficient; efficiency improvements are critical, aligning with ISSB and transition finance frameworks.
👥 読者別の含意
🔬研究者:Provides a DEA-based methodology to assess green innovation efficiency, useful for comparative climate policy studies.
🏢実務担当者:Offers benchmarking insights for corporate sustainability teams to optimize R&D and clean energy investments.
🏛政策担当者:Highlights the need for policies that improve innovation efficiency, not just increase spending, for effective decarbonization.
📄 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.19442356first seen 2026-05-05 19:11:34
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。