Evidence map›Paper›PMID 36834258›Full record

ArticleInternational journal of environmental research and public health2023

Study on the Spatial-Temporal Pattern and Driving Mechanism of Tourism Eco-Security in the Yellow River Basin.

Junyuan Zhao, Shengjie Wang, Jiayue Li

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 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
  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.

Junyuan ZhaoSchool of Business, Xinyang College, West Section of Xinqi Avenue, Shihe District, Xinyang 464000, China.
Shengjie WangCollege of Geography and Environment Science, Northwest Normal University, Lanzhou 730070, China.
Jiayue LiSchool of Business, Central South University of Forestry and Technology, Changsha 410004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tourism eco-security evaluation is an effective tool for facilitating the coordinated and sustainable economic and environmental development of tourist destinations. Based on system theory, this study established a comprehensive evaluation index system for the DPSIR model, applying the entropy-TOPSIS method, spatial autocorrelation, spatial econometric model and geo-detector to investigate the spatial and temporal evolution and drivers of tourism eco-security of the Yellow River basin. The results showed that the tourism eco-security of the Yellow River basin steadily and significantly increased from 2003 to 2020, reaching a peak in 2019, while there was a low level of overall tourism eco-security and improvement possibility. The results show a spatial evolution pattern of expansion from provincial capital cities to nearby prefecture-level cities from the middle and lower reaches to the middle and upper reaches, with significant spatial clustering and spillover effects. Factors affecting the tourism eco-security of the Yellow River basin vary in and between regional basins. Because there are many influencing factors, the key factors were further identified by spatial effect decomposition. The results of this study have important theoretical and practical value in promoting the coordinated and sustainable development of the tourism economy and ecological environment in the Yellow River basin.

Indexed as

Automobile DrivingRiversChinaCitiesEconomic DevelopmentEntropyTourismDPSIR modelinfluencing factorsspatial–temporal evolution modethe Yellow River basintourism eco-security

Identifiers

PMID36834258
PMCPMC9964773

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.