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

Author

Listed:
  • 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
    Finnish Meteorological Institute, FI-00101 Helsinki, Finland)

  • 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)

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.

Suggested Citation

  • Qingfang Liu & Jinping Song & Teqi Dai & Jianhui Xu & Jianmei Li & Enru Wang, 2022. "Spatial Network Structure of China’s Provincial-Scale Tourism Eco-Efficiency: A Social Network Analysis," Energies, MDPI, vol. 15(4), pages 1-16, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1324-:d:747425
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    References listed on IDEAS

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    1. Gössling, Stefan & Peeters, Paul & Ceron, Jean-Paul & Dubois, Ghislain & Patterson, Trista & Richardson, Robert B., 2005. "The eco-efficiency of tourism," Ecological Economics, Elsevier, vol. 54(4), pages 417-434, September.
    2. Rui Wang & Bing Xia & Suocheng Dong & Yu Li & Zehong Li & Duoxun Ba & Wenbiao Zhang, 2020. "Research on the Spatial Differentiation and Driving Forces of Eco-Efficiency of Regional Tourism in China," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    3. Yiyang Sun & Guolin Hou & Zhenfang Huang & Yi Zhong, 2020. "Spatial-Temporal Differences and Influencing Factors of Tourism Eco-Efficiency in China’s Three Major Urban Agglomerations Based on the Super-EBM Model," Sustainability, MDPI, vol. 12(10), pages 1-21, May.
    4. Castilho, Daniela & Fuinhas, José Alberto & Marques, António Cardoso, 2021. "The impacts of the tourism sector on the eco-efficiency of the Latin American and Caribbean countries," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    5. Zha, Jianping & He, Lamei & Liu, Yang & Shao, Yuhong, 2019. "Evaluation on development efficiency of low-carbon tourism economy: A case study of Hubei Province, China," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 47-57.
    6. Peng, Hongsong & Zhang, Jinhe & Lu, Lin & Tang, Guorong & Yan, Bingjin & Xiao, Xiao & Han, Ya, 2017. "Eco-efficiency and its determinants at a tourism destination: A case study of Huangshan National Park, China," Tourism Management, Elsevier, vol. 60(C), pages 201-211.
    7. Jean-Paul Ceron & John Broderick & Paul Upham & Ghislain Dubois & Paul Peeters & Wolfgang Strasdas, 2007. "Voluntary carbon offsetting schemes for aviation : efficiency and dredibility," Post-Print hal-00527632, HAL.
    8. Xiaoping Qiu & Yiping Fang & Xueting Yang & Fubiao Zhu, 2017. "Tourism Eco-Efficiency Measurement, Characteristics, and Its Influence Factors in China," Sustainability, MDPI, vol. 9(9), pages 1-19, September.
    9. Song, Malin & Li, Hui, 2019. "Estimating the efficiency of a sustainable Chinese tourism industry using bootstrap technology rectification," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 45-54.
    10. Dai, Liang & Derudder, Ben & Liu, Xingjian, 2018. "The evolving structure of the Southeast Asian air transport network through the lens of complex networks, 1979–2012," Journal of Transport Geography, Elsevier, vol. 68(C), pages 67-77.
    11. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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