武陵山片区旅游经济空间网络结构及其效应研究

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

基于武陵山片区71个县(市、区)2010~2018年的面板数据,运用修正引力模型和社会网络分析法,探析武陵山片区旅游经济空间网络结构及其效应。研究结果表明:(1)研究期间内,武陵山片区各县市旅游经济联系强度不断增大,特别是武陵源区、张家界市、黔江区、碧江区等县区间旅游经济联系明显增强,基本实现了由点到线再到面的融合;(2)武陵山片区旅游经济空间网络结构特征明显,网络关联数、网络密度和网络效率呈微小上升态势,而网络等级度逐渐下滑,说明旅游经济有效联系有待增强;(3)武陵山片区节点中心性差值渐趋缩小,旅游经济网络呈现多核心模式;(4)E-I派系结构表明受行政隶属关系影响,武陵山片区旅游经济网络呈明显的“核心—边缘”结构与“行政派系”结构,四大子群(派系)的旅游经济开放程度稳步提振但仍有较大改善空间;(5)网络密度与旅游经济联系强度呈正相关,与旅游经济联系强度差异构成负相关,而网络等级度和网络效率则与之相反,网络中心性各指标的提升均能显著增强旅游经济联系强度。

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.