Evidence map›Paper›PMID 38468960›Full record

ArticleHeliyon2024

Dynamic evolution and obstacle factor analysis of green development in China's agriculture and rural areas based on entropy-based TOPSIS model.

Li Wang, Nan Li, Qian Xie

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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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

3 authors.

Li WangSchool of Economics & Management, Northwest University, Xi'an 710127, China.
Nan LiSchool of Economics & Management, Northwest University, Xi'an 710127, China.
Qian XieSchool of Economics & Management, Northwest University, Xi'an 710127, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Green development of agriculture and rural areas (GDARA) is an essential part of rural revitalization and high-quality development. Based on 2011 to 2020 provincial panel data from China, the entropy-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model is constructed to measure the level of GDARA, finding that the overall level during the sample period was positive. Then the regional differences mainly from intra-regional were revealed by the methods of Dagum Gini coefficient and Kernel density estimation and were shrinking overall. Besides, the results of Markov chain transfer matrix show the dynamic characteristics clearly, which the low-level regions shift to the middle and high levels with a greater probability. The results of the spatial autocorrelation test display that GDARA has a spatial clustering effect. Finally, the industrial upgrading and the business income of leisure agriculture are respectively proven to hinder GDARA at most by the Obstacle degree model empirically. Based on a series of empirical tests, a few relevant policy recommendations are proposed to promote the road to strong agriculture and rural areas in China.

Indexed as

Green development in agriculture and rural areasIndicator systemObstacle factorSpatial and temporal characteristicsSpatial autocorrelation

Identifiers

PMID38468960
PMCPMC10926133

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.