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

doi:10.1371/journal.pone.0291614

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

PLoS One. 2023 Nov 15;18(11):e0291614. doi: 10.1371/journal.pone.0291614. eCollection 2023.

Authors

Haiyong Zhao¹, Junnan Zheng², Sihui Ma¹, Lei Zhao³, Pengfei Xu¹, Jian Li^{1

4}

Affiliations

¹ College of Landscape Architecture, Zhejiang Agriculture and Forestry University, Hangzhou, China.
² Zhejiang Informatization Development Institute, Hangzhou Dianzi University, Hangzhou, China.
³ School of Management, Zhejiang University of Technology, Hangzhou, China.
⁴ Zhejiang Province Key Think Tank: Institute of Ecological Civilization, Zhejiang A&F University, Hangzhou, China.

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.

Copyright: © 2023 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

MeSH terms

China
Cities
Humans
Spatial Analysis
Spatial Regression*
Tourism*

Grants and funding

In the process of this research, we were supported by the National Social Science Foundation of China (grant number 22BGL153), the National Social Science Foundation of China (grant number 20BJY125), the Zhejiang Soft Science Research Program (grant number 2022C35090), and the Zhejiang New Seedling Talent Program (grant number 2022R412B045). The funders played an important role in the study. The first grant leader, Jian Li, was responsible for the conceptualization, validation, research, reference provision, writing, and project supervision and management of the research. Junnan Zheng, the leader of the second fund, was responsible for the use of research methods, validation, writing, supervision, etc. in this study. Pengfei Xu, the leader of the third fund, was responsible for the identification of the research framework, defining the research methodology, research, providing references, supervision, and project management in this study. The head of the fourth fund, Haiyong Zhao, is responsible for the conceptualization of the research, the use of research methods, the operation of software, validation, research, paper writing, and project management in the research. A detailed description of this is given in the author contribution section of our paper.