Evidence map›Paper›PMID 40820168›Full record

ArticleScientific reports2025

Spatial distribution characteristics and tourism response of intangible cultural heritage in coastal areas of China.

Litao Xie, Tingzuo Feng, Lijun Jiang, Jing Tian

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Litao Xie *School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China.
Tingzuo Feng *School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China.
Lijun Jiang *School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China.
Jing TianSchool of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China. tianjing_sres@whu.edu.cn.

Funding

Undergraduate Training Programs for Innovation and Entrepreneurship of Wuhan University S202510486157
6 · The paper itself

Abstract

The coastal regions of China are abundant in intangible cultural heritage (ICH) resources characterized by distinct maritime features. The comprehensive integration and development of these resources with tourism represent a critical strategy for the scientific protection and sustainable development of coastal ICH. This study examines the spatial distribution of ICH across China's coastal regions. It also establishes an evaluation system to measure tourism response levels toward coastal ICH and employs a GeoDetector model to identify influencing factors. The results indicate that: (1) Different types of ICH resources in coastal areas exhibit distinct spatial distribution patterns, with notable variations in their concentrations. Generally, the spatial distribution of ICH follows a multi-centered structure, exhibiting higher densities in the Yangtze River Delta, Pearl River Delta, and Yellow River Delta. (2) Regional disparities in tourism response levels toward ICH are evident in coastal regions, demonstrating a decreasing gradient from central areas toward the north and south. (3) The tourism response levels of ICH are primarily influenced by factors such as regional GDP, resident population, the tourism environment, and the number of ICH sites, with regional GDP identified as the most influential factor. These findings enhance the understanding of the current developmental status of ICH in China's coastal regions and highlight key distinctions from inland areas.

Indexed as

Coastal areasInfluencing factorsIntangible cultural heritageSpatial distributionTourism response

Identifiers

PMID40820168
PMCPMC12358532

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.