How Does Digital Intelligence Transformation Reshape Carbon Emission Efficiency in Resource-Based Cities?
デジタルインテリジェンス変革は資源依存都市の炭素排出効率をどのように再形成するか？ (AI 翻訳)
Qiguo Yi, Guiling Ran, Huiting Chen
🤖 gxceed AI 要約
日本語
本研究は、中国110の資源依存都市のパネルデータ（2013-2022年）を用いて、デジタルインテリジェンス変革（DIT）が炭素排出効率（CEE）に与える影響を分析。DIT指数を構築し、SBM-GML法でCEEを測定した結果、DITはCEEを有意に向上させ、標準偏差1単位の増加でCEEが0.033上昇（サンプル平均の3.96%）。メカニズム分析では、資源配分の改善とグリーン技術革新が媒介。グリーンファイナンスやデジタル基盤が整った都市で効果が大きい。
English
This study analyzes panel data from 110 Chinese resource-based cities (2013-2022) to examine the impact of digital intelligence transformation (DIT) on carbon emission efficiency (CEE). Using a comprehensive DIT index and SBM-GML approach, it finds that DIT significantly improves CEE, with a one-standard-deviation increase raising CEE by 0.033 (3.96% of sample mean). Mechanism analysis reveals that reduced resource misallocation and enhanced green technological innovation are key channels. Heterogeneity analysis shows stronger effects in cities with advanced green finance, better digital infrastructure, and at mature or regenerative stages.
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
日本でもデジタル技術を活用した炭素効率向上が注目される中、本論文は中国の資源依存都市を対象にした実証分析を提供し、日本におけるスマートシティ政策やGX推進への示唆を含む。
In the global GX context
This paper contributes to the growing body of evidence on how digitalization can enhance carbon efficiency, particularly in resource-dependent urban contexts. It offers insights for policymakers worldwide seeking to leverage AI and digital tools for decarbonization.
👥 読者別の含意
🔬研究者:Researchers interested in the intersection of digital transformation and carbon efficiency will find robust empirical evidence and a novel index construction.
🏢実務担当者:Corporate sustainability teams in resource-intensive sectors can use these findings to advocate for digital investments as a means to improve carbon performance.
🏛政策担当者:Policymakers in resource-based cities can consider integrating digital intelligence strategies into their low-carbon transition plans, as the study demonstrates significant efficiency gains.
📄 Abstract（原文）
Resource-based cities face persistent challenges in reconciling economic growth with the transition to low-carbon development. This tension poses significant obstacles to sustainable regional development. Digital intelligence transformation (DIT) refers to the deep integration of digitalization and intelligent technologies. It offers a new pathway to enhance urban sustainability. Using panel data from 110 Chinese resource-based cities from 2013 to 2022, this study examines the impact of DIT on carbon emission efficiency (CEE). A comprehensive DIT index is constructed, and the SBM-GML approach is applied to measure CEE. A two-way fixed-effects model is employed to estimate the impact of DIT on CEE. The results show that DIT significantly improves CEE. A one–standard-deviation increase in DIT is associated with a 0.033 rise in CEE, which equals 3.96% of the sample mean. Mechanism analysis indicates that this effect is closely linked to lower resource misallocation and stronger green technological innovation. Heterogeneity analysis further suggests that DIT has a stronger impact in cities with advanced green finance, better digital infrastructure, and those at mature or regenerative development stages. Overall, the findings provide robust empirical evidence that digital intelligence technologies can serve as an effective driver of sustainable development in resource-based cities.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.3390/su18041918first seen 2026-05-14 21:50:57
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