Spatial Network Structure of China's Provincial-Scale Tourism Eco-Efficiency: A Social Network Analysis

被引:1
|
作者
Liu, Qingfang [1 ]
Song, Jinping [1 ]
Dai, Teqi [1 ]
Xu, Jianhui [2 ,3 ]
Li, Jianmei [2 ]
Wang, Enru [4 ]
机构
[1] Beijing Normal Univ, Fac Geog Sci, Beijing 100875, Peoples R China
[2] Chuzhou Univ, Sch Geog Informat & Tourism, Chuzhou 239099, Peoples R China
[3] Finnish Meteorol Inst, FI-00101 Helsinki, Finland
[4] Univ North Dakota, Dept Geog & Geog Informat Sci, Grand Forks, ND 58202 USA
基金
中国国家自然科学基金;
关键词
low-carbon tourism; tourism eco-efficiency; spatial network correlation; Super-SBM; social network analysis; SECTOR; ECONOMY;
D O I
10.3390/en15041324
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
While tourism eco-efficiency has been analyzed actively within tourism research, there is an extant dearth of research on the spatial network structure of provincial-scale tourism eco-efficiency. The Super-SBM was used to evaluate the tourism eco-efficiency of 30 provinces (excluding Tibet, Hong Kong, Macao and Taiwan). Then, social network analysis was employed to examine the evolution characteristics regarding the spatial network structure of tourism eco-efficiency. The main results are shown as follows. Firstly, tourism eco-efficiency of more than two thirds' provinces witnessed an increasing trend. Secondly, the spatial network structure of tourism eco-efficiency was still loose and unstable during the sample period. Thirdly, there existed the multidimensional nested and fused spatial factions and condensed subsets in the spatial network structure of tourism eco-efficiency. However, there was still a lack of low-carbon tourism cooperation among second or third sub-groups. These conclusions can provide references for policymakers who expect to reduce carbon emissions from the tourism industry and to achieve sustainable tourism development.
引用
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页数:16
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