Evidence map›Paper›PMID 38601608›Full record

ArticleHeliyon2024

Spatial distribution and influencing factors of rural tourism: A case study of Henan Province.

Jiusheng Du, Beibei Zhao, Yunchao Feng

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Jiusheng DuSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454003, China.
Beibei ZhaoSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454003, China.
Yunchao FengSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rural tourism is a powerful way to revitalize the countryside, and its spatial pattern is crucial for sustainable development. This paper analyzes the spatial distribution of rural tourism characteristic villages in Henan Province by taking 723 villages as the research object and using the nearest neighbor index, kernel density analysis, and spatial autocorrelation. It investigates the influencing factors utilizing the optimal parameters-based geographical detector (OPGD) model. The results show that, firstly, the overall spatial distribution of the rural tourism characteristic villages in Henan Province is characterized by aggregation and unbalanced distribution, and the overall spatial distribution density demonstrates the aggregation characteristics of "four cores and one belt". Secondly, the rural tourism characteristic villages can be divided into four primary categories, agricultural industry, rural culture, and featured villages and towns. The spatial distributions of the four main categories are all clustered. Thirdly, the primary factors affecting the differences in the spatial distribution of the rural tourism characteristic villages are the topographic features, economic development level, tourism market potential, traffic capacity, and relevant policies, among which the critical factor is the number of A-class scenic spots in the tourism market potential. To promote the optimisation of the spatial pattern of rural tourism, it is necessary to strengthen resource integration. Furthermore, it is important to conduct in-depth exploration of more factors in order to provide comprehensive guidance for the sustainable development of rural tourism.

Indexed as

Henan provinceInfluencing factorsOptimal parameters-based geographical detectorRural tourism characteristic villageSpatial distribution

Identifiers

PMID38601608
PMCPMC11004580

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.