Evidence map›Paper›PMID 37967108›Full record

ArticlePloS one2023

Spatial distribution and influencing factors analysis of national key rural tourism villages in the Yangtze River Delta region based on geographically weighted regression.

Haiyong Zhao, Junnan Zheng, Sihui Ma, Lei Zhao, Pengfei Xu, Jian Li

Abstract read
In one paragraph

Article in PloS one, 2023. 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
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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

6 authors.

Haiyong ZhaoCollege of Landscape Architecture, Zhejiang Agriculture and Forestry University, Hangzhou, China.
Junnan ZhengZhejiang Informatization Development Institute, Hangzhou Dianzi University, Hangzhou, China.
Sihui MaCollege of Landscape Architecture, Zhejiang Agriculture and Forestry University, Hangzhou, China.
Lei ZhaoSchool of Management, Zhejiang University of Technology, Hangzhou, China.
Pengfei XuCollege of Landscape Architecture, Zhejiang Agriculture and Forestry University, Hangzhou, China.
Jian LiCollege of Landscape Architecture, Zhejiang Agriculture and Forestry University, Hangzhou, China.ORCID 0000-0001-6327-1383

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

National key rural tourism villages (NKRTVs) can lead to the high-quality development of rural tourism, and their spatial distribution is influenced by a variety of factors. However, existing studies have neglected the fact that influencing factors can have different directions and effects in different geographic spaces. This study investigates 156 NKRTVs in the Yangtze River Delta region of China as the research object and employs ArcGIS spatial analysis technology to examine their spatial distribution characteristics. Additionally, two new indicators of land and culture are introduced to enhance the index system of influencing factors. A geographically weighted regression model is utilized to identify the spatial heterogeneity of various factors that affect the spatial distribution of NKRTVs. The results of this study indicate the following: (1) The spatial distribution of NKRTVs in the Yangtze River Delta region is characterized by "small clustering and large dispersion." The spatial distribution exhibits strong spatial correlation, with Shanghai serving as the primary spatial clustering core and Huangshan city forming a secondary spatial clustering subcore. The distribution of NKRTVs is relatively scattered in other areas, with obvious differences in the spatial distribution of cold and hot spots. (2) The results of the geographically weighted regression model show that with the change in spatial location, the influence effect of each influencing factor on the spatial distribution of NKRTVs has obvious spatial differences. Based on the spatial heterogeneity of the influencing factors, this study proposes targeted suggestions for the development of rural tourism in different regions.

Indexed as

Spatial RegressionTourismChinaCitiesHumansSpatial Analysis

Identifiers

PMID37967108
PMCPMC10651025

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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.