RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2022, Vol. 31 >> Issue (2): 285-295.doi: 10.11870/cjlyzyyhj202202003

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Spatial Network Structure of Tourism Economic and Its Effects in Wuling Mountain Area

WANG Kai1, WANG Meng-han2, YIN Jian-jun3, GAN Chang1    

  1. (1. College of Tourism, Hunan Normal University, Changsha 410081, China;2.School of Environmant and Natural Resources Renmin  University of China,Beijing 100872,China; 3. College of Geography and Tourism, Huanggang Normal University, Huanggang 438000, China)
  • Online:2022-02-20 Published:2022-03-21

Abstract: Based on panel data of 71 counties (cities, districts) in Wuling Mountain Area from 2010 to 2018, the modified gravity model and social network analysis were applied to explore the spatial network structure and its effect of tourism economy. The research results show that: (1) During the research period, the strength of the tourism economic ties between counties and cities in the Wuling Mountain Area has been increasing. Especially, the tourism economic links between Wulingyuan District, Zhangjiajie City, Qianjiang District, Bijiang District and other counties have been significantly strengthened, and the integration from point to line to surface is basically realized. (2) The spatial network structure of the tourism economy in Wuling Mountain Area has obvious characteristics. The number of network connections, network density and network efficiency have shown a slight upward trend, while the level of the network has gradually declined. The effective connection of its tourism economy needs to be strengthened. (3) The difference in node centrality in Wuling Mountain Area is converging significantly. The tourism economic network presents a multi-core model. (4) The analysis of E-I index shows the tourism economic network presents “core-edge” structure and “administrative faction structure”. The tourism economy between the four subgroups (sects) of Hubei Province, Hunan Province, Guizhou Province and Chongqing City has increased steadily, but there is a lot of room for improvement. (5) The density of the network is positively correlated with the strength of tourism economic linkages, and negatively related to the difference in the strength of tourism economic linkages. On the contrary, the degree of network level and network efficiency are opposite. The improvement of various indicators of network centrality can significantly enhance the strength of tourism economic linkages.

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