Evidence map›Paper›PMID 40961064›Full record

ArticlePloS one2025

Spatial attribution and policy design of rural entrepreneurship: Evidence from Anhui Province in China.

Xiaojuan Yang, Weiwei Li, Zhenyu Gao

Abstract read
In one paragraph

Article in PloS one, 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
–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

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

3 authors.

Xiaojuan YangCivil & Architecture Engineering, Xi'an Technological University, Xi'an, China.
Weiwei LiUrban-Rural Construction College, Guangxi Vocational University of Agriculture, Nanning, China.
Zhenyu GaoThe School of Art and Media Design, Nanchang Institute of Science and Technology, Nanchang, China.ORCID https://orcid.org/0009-0002-4322-6117

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rural entrepreneurship is a key way to combat rural decline and promote the revitalization of rural areas and their sustainability, and also a key area of research in agricultural and rural geography, economics, and management. We combined spatial econometrics models such as spatial clustering, cold and hot spot analysis, geographical weighted regression and Geodetector to carry out empirical research on geographical distribution of rural entrepreneurship in Anhui province, in an attempt to provide scientific basis for rural policy design, spatial planning and evidence-based decision-making. The findings showed an increasing trend of the spatial heterogeneity and autocorrelation of rural entrepreneurship in Anhui, with geographic clustering of high, medium and low values as well as cold and hot spots. And the diversification of rural entrepreneurship changes led to a very complex driving mechanism for the generation and evolution of rural entrepreneurship spatial patterns, and the factors showed significant spatial and composite effects. The enlightening value of the analysis results lies in the fact that rural entrepreneurship management not only needs to delineate geographical zones and design differentiated policies, but also needs to jointly build rural entrepreneurship alliances in similar or adjacent areas to integrate regional entrepreneurial resources. In addition, rural entrepreneurship management should be guided according to the situation, and policy design should take into account both quantity and speed control, with establishment of policy combinations based on the spatial and composite effects of different factors.

Indexed as

EntrepreneurshipRural PopulationChinaHumansSpatial Analysis

Identifiers

PMID40961064
PMCPMC12443325

What OpenQuestion holds

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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.