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

被引:15
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; 英国科研创新办公室;
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
相关论文
共 38 条
[1]   Analysis of the spatial association network structure of China's transportation carbon emissions and its driving factors [J].
Bai, Caiquan ;
Zhou, Lei ;
Xia, Minle ;
Feng, Chen .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2020, 253 (253)
[2]   Eco-efficiency measurement and spatial–temporal evolution of forest tourism [J].
Li B. ;
Ma X. ;
Chen K. .
Arabian Journal of Geosciences, 2021, 14 (7)
[3]   The impacts of the tourism sector on the eco-efficiency of the Latin American and Caribbean countries [J].
Castilho, Daniela ;
Fuinhas, Jose Alberto ;
Marques, Antonio Cardoso .
SOCIO-ECONOMIC PLANNING SCIENCES, 2021, 78
[4]   China's regional tourism efficiency: A two-stage double bootstrap data envelopment analysis [J].
Chaabouni, Sami .
JOURNAL OF DESTINATION MARKETING & MANAGEMENT, 2019, 11 :183-191
[5]   The evolving structure of the Southeast Asian air transport network through it the lens of complex networks, 1979-2012 [J].
Dai, Liang ;
Derudder, Ben ;
Liu, Xingjian .
JOURNAL OF TRANSPORT GEOGRAPHY, 2018, 68 :67-77
[6]   Spatial network structure of the tourism economy in urban agglomeration: A social network analysis [J].
Gan, Chang ;
Voda, Mihai ;
Wang, Kai ;
Chen, Lijun ;
Ye, Jun .
JOURNAL OF HOSPITALITY AND TOURISM MANAGEMENT, 2021, 47 :124-133
[7]  
Gossling S., 2007, Journal of Sustainable Tourism, V15, P223, DOI 10.2167/jost758.0
[8]   The eco-efficiency of tourism [J].
Gössling, S ;
Peeters, P ;
Ceron, JP ;
Dubois, G ;
Patterson, T ;
Richardson, RB .
ECOLOGICAL ECONOMICS, 2005, 54 (04) :417-434
[9]   How to improve tourism energy efficiency to achieve sustainable tourism: evidence from China [J].
He, Lamei ;
Zha, Jianping ;
Loo, Hui Ann .
CURRENT ISSUES IN TOURISM, 2020, 23 (01) :1-16
[10]   Spatial network analysis of carbon emissions from the electricity sector in China [J].
He, Yang-Yang ;
Wei, Zhen-Xiang ;
Liu, Guo-Quan ;
Zhou, P. .
JOURNAL OF CLEANER PRODUCTION, 2020, 262