Evidence map›Paper›PMID 41927878›Full record

ArticleScientific reports2026

Sustainable development evaluation of agri-culture-tourism integration in revolutionary old areas: a case study of Tianshui city.

Maomao Luo, Huanyu Zhang, Mengke Xuan, Tingting Liu, Qiancheng Zhou

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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.

Maomao LuoJiujiang Polytechnic University of Science and Technology, Jiujiang, China.
Huanyu ZhangTourism College, Beijing Union University, Beijing, China.
Mengke XuanSchool of Business, Renmin University of China, Beijing, China.
Tingting LiuSchool of Marxism, Central University of Finance and Economics, Beijing, China. lphy1006@163.com.
Qiancheng ZhouSchool of Public Administration, Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a carrier of China's historical and cultural heritage, the sustainable development of the integration of agriculture, culture, and tourism (Agri-Culture-Tourism) in the old revolutionary base areas plays an important role in promoting the protection of cultural heritage and regional economic growth. However, how to achieve sustainable development of Agri-Culture-Tourism integration in old revolutionary base areas and what the key factors influencing such development are still remain important research topics that have not been explored in depth at present. This paper explores the practices and explorations of Tianshui City, a revolutionary old area, in terms of sustainable development in Agri-Culture-Tourism. Through methods such as Python Grey Relational Analysis, Logistic Regression Analysis, and Principal Component Factor Analysis, this study reveals the high correlation between Agri-Culture-Tourism and the tertiary industry in Tianshui City. It identifies key factors influencing tourists' willingness to support, including the "level of infrastructure development for Agri-Culture-Tourism," "richness of Agri-Culture-Tourism resources," and "integration of Agri-Culture-Tourism supporting poverty alleviation." Tianshui city has made remarkable achievements in promoting the sustainable development in Agri-Culture-Tourism, which requires focusing on promoting the development of secondary service industry, basic service industry and improving the efficiency of publicity. This study innovatively reveals effective experiences in the sustainable development of Agri-Culture-Tourism in revolutionary old areas, providing valuable insights for the sustainable development of similar regions in China and other developing countries.

Indexed as

Agri-culture-tourismIntegrated developmentRevolutionary old areasServicesSustainable developmentTianshui city

Identifiers

PMID41927878
PMCPMC13187252

What OpenQuestion holds

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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.