Evidence map›Paper›PMID 41365987›Full record

ArticleScientific reports2025

Research on eco-efficiency of provinces along the Belt and Road in China based on DEA methods and AI prediction algorithms.

Panpan Liu, Fei Zhao, Guoqu Deng, Dandan Dong, Xuke Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Panpan LiuBusiness School, Henan University of Science and Technology, Luoyang, 471023, Henan, China.
Fei ZhaoBusiness School, Henan University of Science and Technology, Luoyang, 471023, Henan, China.
Guoqu DengBusiness School, Henan University of Science and Technology, Luoyang, 471023, Henan, China. dengguoqu@126.com.
Dandan DongBusiness School, Henan University of Science and Technology, Luoyang, 471023, Henan, China.
Xuke LiBusiness School, Henan University of Science and Technology, Luoyang, 471023, Henan, China.

Funding

Major Project of Applied Research in Philosophy and Social Sciences in Universities in Henan Province 2025-YYZD-10
6 · The paper itself

Abstract

Under the strategic goals of promoting ecological civilization and advancing regional coordinated development, China's Belt and Road provinces face dual pressures from economic growth and environmental protection. Therefore, a scientific assessment of eco-efficiency is crucial for achieving regional sustainable development. This study aims to systematically examine eco-efficiency and its spatiotemporal evolution across Belt and Road provinces, while also projecting future development trends. To achieve this, the study employs the super-efficiency Epsilon-Based Measure model to measure static efficiency and integrates the Global Malmquist-Luenberger index to analyze dynamic changes. Utilizing Kernel Density Estimation and Moran index to reveal spatial characteristics. A new information-preferred damped cumulative gray model with artificial intelligence is introduced to provide high-precision predictions. The study finds: (1) The overall eco-efficiency level remains low with a declining trend, exhibiting significant regional variations. (2) The technological progress index is a central driver of eco-efficiency. (3) Spatial heterogeneity in eco-efficiency is particularly pronounced, exhibiting spatial clustering characteristics. (4) The forecast indicates that overall eco-efficiency will show an upward trend in the future. Based on the above conclusions, this study puts forward corresponding policy suggestions. These recommendations are of great significance for promoting the sustainable improvement of eco-efficiency in the provinces along the Belt and Road in China.

Identifiers

PMID41365987
PMCPMC12808772

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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.