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Research on the evolution of spatial network structure of tourism eco-efficiency and its influencing factors in China’s provinces based on carbon emission accounting

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  • Chao Wang
  • Lele Xu
  • Menglan Huang
  • Xiaofeng Su
  • Riwen Lai
  • Anxin Xu

Abstract

In the context of global warming, although the coordinated development of tourism has led to regional economic growth, the high energy consumption-driven effects of such development have also led to environmental degradation. This research combines the undesired output of the Super-SBM model and social network analysis methods to determine the eco-efficiency of provincial tourism in China from 2010–2019 and analyzes its spatial correlation characteristics as well as its influencing factors. The aim of the project is to improve China’s regional tourism eco-efficiency and promote cross-regional tourism correlation. The results show that (1) the mean value of provincial tourism eco-efficiency in China is maintained at 0.405~0.612, with an overall fluctuating upward trend. The tourism eco-efficiency of eastern China is higher than that of central, western and northeastern China, but the latter three regions have not formed a stable spatial distribution pattern. (2) The spatial network of provincial tourism eco-efficiency in China is multithreaded, dense and diversified. Throughout the network, affiliations are becoming closer, and network structure robustness is gradually improving, although the “hierarchical” spatial network structure remains. In individual networks, Jiangsu, Guangdong and Shandong provinces in eastern China have higher centrality degrees, closeness centrality and betweenness centrality than other provinces, which means they are dominant in the network. Hainan Province, also located in eastern China, has not yet built a "bridge" for tourism factor circulation. In the core-periphery model, the core-periphery areas of China’s provincial tourism eco-efficiency are distributed in clusters, and the number of "core members" has increased. (3) The economic development level, information technology development level, and tourism technology level collectively drive the development and evolution of China’s provincial tourism eco-efficiency spatial network.

Suggested Citation

  • Chao Wang & Lele Xu & Menglan Huang & Xiaofeng Su & Riwen Lai & Anxin Xu, 2022. "Research on the evolution of spatial network structure of tourism eco-efficiency and its influencing factors in China’s provinces based on carbon emission accounting," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-20, September.
  • Handle: RePEc:plo:pone00:0272667
    DOI: 10.1371/journal.pone.0272667
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    References listed on IDEAS

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    1. Yiyang Sun & Guolin Hou, 2021. "Analysis on the Spatial-Temporal Evolution Characteristics and Spatial Network Structure of Tourism Eco-Efficiency in the Yangtze River Delta Urban Agglomeration," IJERPH, MDPI, vol. 18(5), pages 1-29, March.
    2. Eyup Dogan & Fahri Seker & Serap Bulbul, 2017. "Investigating the impacts of energy consumption, real GDP, tourism and trade on CO2 emissions by accounting for cross-sectional dependence: A panel study of OECD countries," Current Issues in Tourism, Taylor & Francis Journals, vol. 20(16), pages 1701-1719, December.
    3. Puertas, Rosa & Guaita-Martinez, José M. & Carracedo, Patricia & Ribeiro-Soriano, Domingo, 2022. "Analysis of European environmental policies: Improving decision making through eco-efficiency," Technology in Society, Elsevier, vol. 70(C).
    4. 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.
    5. Zhengju Jiang & Fuyou Guo & Liping Cai & Xiaoxiao Li, 2021. "Eco-Province Construction Performance and Its Influencing Factors of Shandong Province in China: From Regional Eco-Efficiency Perspective," Sustainability, MDPI, vol. 13(21), pages 1-17, November.
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    1. Donghui Peng & Zongzheng Liang & Yapeng Ding & Liuke Liang & Aohui Zhai & Yan Zhang & Xu Gong, 2024. "Spatial and temporal distribution characteristics and influencing factors of tourism eco-efficiency in the Yellow River Basin based on the geographical and temporal weighted regression model," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-27, February.

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