ArticleScientific reports2025
The effect of productive capacity changes, income, and clean energy on ecological sustainability in China by novel KRLS approach.
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
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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.
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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.
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Who cites it
1 citing paper in PubMed.
- Machine learning-based analysis of economic efficiency disparities and transition drivers between high- and low-carbon industries in China.Carbon balance and management · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The adverse effects of climatic issues on ecological sustainability have been increasing. Within this context, ensuring a transformation in economic structure into eco-friendly ones has become important. Accordingly, the study investigates how productive capacity changes are marginally effective on ecological sustainability by focusing on the Chinese case, using ecological footprint as the main indicator and load capacity factor as the alternative indicator for robustness, considering productive capacity index (PCI) types as independent variables, controlling economic growth, nuclear energy, and renewable energy, and applying the Kernel-Based Least Squares (KRLS) approach on yearly data from 2000 to 2022. The outcomes reveal that (i) aggregated level PCI and PCI subtypes, except for PCI for institutions (PCI-IN) and private sector (PCI-PS), are inefficient in ensuring ecological sustainability; (ii) PCI-IN has a supporting effect on ecological sustainability, while PCI-PS has an increasing but insignificant effect; (iii) economic growth, as well as nuclear and renewable energy consumption, have a decreasing effect on ecological sustainability; (iv) the outcomes are robust; (v) the KRLS approach presents high prediction outcomes reaching 99.7%. Overall, the study demonstrates the marginal effects of PCI subtypes, where only PCI-IN significantly contributes to ecological sustainability. Accordingly, the study discusses policy implications, such as relying on specific PCI types (i.e., PCI-IN) and trying to make other PCI indicators (e.g., PCI-PS) efficient in supporting ecological sustainability further.
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