ArticleScientific reports2025
The impact of artificial intelligence on green economy efficiency under integrated governance.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Unpacking the mechanisms and consequences of artificial intelligence in enabling green value co-creation for SMEs.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
This study investigates the impact of Artificial Intelligence (AI) on Green Economic Efficiency (GEE) using panel data from 30 Chinese provinces spanning from 2011 to 2020. The empirical results demonstrate that AI significantly enhances GEE, with its effects varying across regions and governance types. Specifically, AI's impact is stronger in economically advanced and technologically intensive provinces. In terms of policy governance, excessive Market-based Environmental Regulations (MER) diminish AI's effect on GEE, while stronger Administrative-command Environmental Regulations (CER) and Informal Environmental Regulations (IER) amplify it. Technological governance, particularly Substantive Green Technological Innovations (SUG), reduces AI's effectiveness due to high investment thresholds, whereas Symbolic Green Technological Innovations (SYG) increase AI's impact on GEE. In legal governance, both Administrative Intellectual Property Protection (AIP) and Judicial Intellectual Property Protection (JIP) can reduce AI's marginal effect, with AIP showing a stronger threshold effect. These findings empirically support the theoretical models of AI-driven green development, highlighting the varying roles of governance mechanisms in promoting GEE and offering actionable insights for policymakers to optimize governance frameworks for sustainable growth.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.