新デジタルインフラは漁業の低炭素転換を促進するか：中国各省の炭素排出からの証拠
Does new digital infrastructure promote the low-carbon transformation of fisheries: evidence from carbon emissions across Chinese provinces (原題)
Han Zeng, Xiaoyu Chen
🤖 gxceed AI 要約
日本語
中国30省のパネルデータ（2004-2024年）を用い、テキスト分析とダブル機械学習で新デジタルインフラ（NDI）が漁業炭素排出（FCE）に与える影響を評価。NDIはFCEを有意に削減し、技術進歩・産業高度化・エネルギー構造改善を通じて効果を発揮。空間的波及効果も確認され、地域間の排出削減に寄与。
English
Using panel data from 30 Chinese provinces (2004-2024), this study employs textual analysis and double machine learning to assess the impact of new digital infrastructure (NDI) on fishery carbon emissions (FCE). NDI significantly reduces FCE, with effects mediated by technological progress, industrial upgrading, and cleaner energy structure. Spatial spillover analysis shows NDI also reduces emissions in neighboring regions, with indirect effects exceeding direct ones.
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「双炭」目標下でのデジタル基盤と漁業の低炭素化に関する実証研究。日本では水産業の脱炭素化やデジタル化政策に示唆を与えるが、直接的な日本関連性は限定的。日本の漁業関係者には、データ駆動型の排出削減策の参考となる。
In the global GX context
This study provides empirical evidence on how digital infrastructure can drive low-carbon transition in a specific sector (fisheries), relevant to global discussions on sectoral decarbonization and the role of digitalization. It contributes to understanding spatial spillovers of climate policies, which is valuable for designing regional cooperation mechanisms.
👥 読者別の含意
🔬研究者:Provides empirical evidence on the carbon-reduction effects of digital infrastructure in the fishery sector, with methodological insights from double machine learning.
🏢実務担当者:Offers insights for fishery companies and supply chains on leveraging digital infrastructure for emission reductions, potentially informing sustainability strategies.
🏛政策担当者:Highlights the importance of regional digital infrastructure deployment for achieving sectoral emission reduction targets, relevant for policy design.
📄 Abstract（原文）
New digital infrastructure (NDI) provides the technological foundation for integrating data as a factor of production into all stages of fishery production and operations, thereby facilitating the green and low-carbon transformation of fisheries under China’s “dual carbon” goals. Using panel data from 30 provincial-level regions in mainland China over the period 2004–2024, excluding Tibet, this study measures the development level of new digital infrastructure through textual analysis and employs double machine learning to evaluate its effect on fishery carbon emissions. Extended analyses are further conducted from the perspectives of potential transmission pathways, regional and temporal heterogeneity, endogeneity, and spatial spillover effects. The results show that NDI significantly reduces FCE, and this finding remains robust across a range of robustness checks. The potential-pathway analysis shows that NDI is positively associated with technological progress, industrial structure upgrading, and a cleaner energy structure. The spatial spillover analysis shows that NDI not only reduces FCE in the local region but also generates significant emission-reduction effects in spatially connected regions, with the indirect effect exceeding the direct effect. These findings provide empirical evidence for understanding the carbon-reduction effect of NDI in the fishery sector and its potential transmission pathways. They also offer policy implications for optimizing the regional deployment of digital infrastructure and advancing the green and low-carbon transformation of fisheries.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3389/fmars.2026.1932721first seen 2026-09-03 05:08:40
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