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

Qingfang Liu, Jinping Song, Teqi Dai, Jianhui Xu, Jianmei Li and Enru Wang
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Qingfang Liu: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Jinping Song: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Teqi Dai: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Jianhui Xu: School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239099, China
Jianmei Li: School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239099, China
Enru Wang: Department of Geography & Geographic Information Science, University of North Dakota, Grand Forks, ND 58202, USA

Energies, 2022, vol. 15, issue 4, 1-16

Abstract: 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.

Keywords: low-carbon tourism; tourism eco-efficiency; spatial network correlation; Super-SBM; social network analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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