2022
DOI: 10.3390/su142315953
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Spatial Distribution Characteristics and Influencing Factors of Pro-Poor Tourism Villages in China

Abstract: This paper aims to contribute to the effectiveness of pro-poor tourism in rural areas. We use 5770 pro-poor tourism villages in China as the research objects; the spatial distribution characteristics of pro-poor tourism villages in China are analyzed using a combination of disequilibrium index, kernel density analysis, and spatial autocorrelation; their influencing factors are detected using a geographical detector and overlay analysis. The study results show the following: (1) The distribution of pro-poor tou… Show more

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Cited by 10 publications
(9 citation statements)
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“…The geographical detector is a method to explore the spatial differentiation characteristics of geographical elements and reveal the reasons for spatial differentiation [41][42][43]. It includes four aspects, including factor detection, interaction detection, risk detection, and ecological detection, and is widely used in ecology, society, economics, and other fields.…”
Section: Geographical Detectormentioning
confidence: 99%
“…The geographical detector is a method to explore the spatial differentiation characteristics of geographical elements and reveal the reasons for spatial differentiation [41][42][43]. It includes four aspects, including factor detection, interaction detection, risk detection, and ecological detection, and is widely used in ecology, society, economics, and other fields.…”
Section: Geographical Detectormentioning
confidence: 99%
“…The long axis of the ellipse represents the distribution direction of the data, and the short axis represents the distribution range of the data, and the shorter the short axis means the more obvious centripetal force presented by the data, and the longer the short axis means the greater the degree of dispersion of the data. In other words, the larger the flatness, the more obvious the directivity of the data, while the closer the length and length of the semi-axis, the less obvious the directivity of the data [30].…”
Section: Spatial Density Analysismentioning
confidence: 99%
“…(Akbulaev et al, 2020;Vasanicova et al, 2021). Thus, an imbalance is created for the constant formation and realization of economic interests at all levels of the economic system -from micro (Chang et al, 2022;Zhu et al, 2022) to macro (Ferreira et al, 2020) and mega levels (Ivancsóné et al, 2018). Chang et al (2022) indicate that rainfall and population size have a greater differential effect on rural tourism's spatial distribution than transport, tourism resources, and urban factors.…”
Section: Analysis Of the Territorial Unevenness Of The Tourism Market...mentioning
confidence: 99%
“…Many scientists suggest determining the structure of a tourism market on the basis of spatial polarization by evaluating the ratio of key quantitative parameters that characterize growth rates in employment, wages, and establishments (Yang et al, 2023;Gavurova et al 2023), accommodation base, tourism traffic, tourism-related expenditures and revenues (Roman et al, 2020). In (Zhu et al, 2022), characteristics of the spatial distribution of pro-poor tourism villages in China are described using disequilibrium index, kernel density analysis, and spatial autocorrelation. Selection of a method for studying the uneven development of regions should make it possible to distribute objects not by one parameter, but by a whole set of features (Reznakova et al, 2022).…”
Section: Analysis Of the Territorial Unevenness Of The Tourism Market...mentioning
confidence: 99%