Evidence map›Paper›PMID 42528693›Full record

ArticleFrontiers in sociology2026

Spatial differentiation and integrated tourism development of China's traditional heritage villages.

Chaohui Zheng, Heng Wei

Abstract read
In one paragraph

Article in Frontiers in sociology, 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
–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

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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

2 authors.

Chaohui Zheng *Faculty of Science and Engineering, University of Nottingham, Nottingham, United Kingdom.
Heng Wei *College of Urban and Rural Construction, Zhongkai University of Agriculture and Engineering, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Traditional villages in China serve as important carriers of rural cultural heritage but are increasingly threatened by rapid urbanisation and uneven regional development. Understanding their spatial distribution and integration within cultural-tourism networks is essential for developing effective conservation and regional planning strategies. Methods: Using a national dataset of 8,157 officially designated traditional villages, combined with city-level tourism indicators and three categories of cultural heritage carriers (A-level scenic spots, intangible cultural heritage, and protected cultural relics), this study developed an integrated analytical framework based on spatial statistical analysis, spatial correlation analysis, and K-means clustering to evaluate spatial differentiation and cultural-tourism integration patterns. Results: The results reveal a pronounced "south-dense, north-sparse" spatial distribution with persistent regional inequality. Traditional villages exhibit weak correlations with overall tourism performance but strong spatial coupling with A-level scenic spots, moderate associations with protected cultural relics, and limited integration with intangible cultural heritage, indicating a selective and uneven embedding structure. Based on these relationships, Chinese cities can be classified into four development types: comprehensive leading areas, scenic-village integration areas, balanced development areas, and potential development areas, each characterised by distinct cultural-tourism integration pathways. Discussion: The findings demonstrate that traditional villages function as selectively embedded nodes within China's cultural-tourism network rather than uniformly integrated tourism resources. This typology provides a practical basis for differentiated conservation policies, cultural heritage management, and place-based tourism planning while offering new insights into the spatial organisation of cultural heritage systems at the national scale.

Indexed as

K-meansrural cultural heritagerural integrated tourismrural tourism developmenttraditional village

Identifiers

PMID42528693
PMCPMC13414847

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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.