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The Spatial Network Structure of Tourism Efficiency and Its Influencing Factors in China: A Social Network Analysis

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  • Guangming Yang

    (School of Management, Chongqing University of Technology, Chongqing 400054, China
    Rural Revitalization and Regional High-Quality Development Research Center, Chongqing University of Technology, Chongqing 400054, China)

  • Yunrui Yang

    (School of Management, Chongqing University of Technology, Chongqing 400054, China
    Rural Revitalization and Regional High-Quality Development Research Center, Chongqing University of Technology, Chongqing 400054, China)

  • Guofang Gong

    (School of Management, Chongqing University of Technology, Chongqing 400054, China
    Rural Revitalization and Regional High-Quality Development Research Center, Chongqing University of Technology, Chongqing 400054, China)

  • Qingqing Gui

    (School of Management, Chongqing University of Technology, Chongqing 400054, China
    Rural Revitalization and Regional High-Quality Development Research Center, Chongqing University of Technology, Chongqing 400054, China)

Abstract

Although tourism has gradually become a popular form of leisure and entertainment in China, the quality of China’s tourism development remains unclear. Through the panel data of 30 provinces in China, an SBM-DEA model and a social network analysis are used to explore the quality of tourism development, and a spatial econometric regression is used to identify the relevant factors affecting tourism efficiency. The study found that the level of tourism efficiency in Southwest China is high and stable. The northwest region has a low level of tourism efficiency, but a slow growth trend. The rest of the regions show fluctuating trends of tourism efficiencies. The spatial correlation network of provincial tourism efficiency is gradually complicated. Regarding influencing factors, the number of patents granted, traffic levels, financial development, and government macro-control all have positive effects on tourism efficiency. The study uncovered some useful management insights and implications for the travel industry.

Suggested Citation

  • Guangming Yang & Yunrui Yang & Guofang Gong & Qingqing Gui, 2022. "The Spatial Network Structure of Tourism Efficiency and Its Influencing Factors in China: A Social Network Analysis," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:9921-:d:885526
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    References listed on IDEAS

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    2. Dilek Cetin & Emre Aksoy & Yalçın Arslanturk, 2022. "Tourism Location Choice of Local and Foreign Tourist: A Perspective through Spatial Analysis," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 8(2), pages 65-79, December.
    3. Mei Yang & Hongling Zhou & Yali Li & Jinyu Zhang, 2023. "Efficiency Evaluation and Influencing Factors of Sports Industry and Tourism Industry Convergence Based on China’s Provincial Data," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    4. Guangming Yang & Siyi Cheng & Qingqing Gui & Xinlan Chen, 2022. "The Coupling and Coordination Characteristics and Influencing Factors of Green Innovation Efficiency (GIE) and Economic Development Levels in China," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    5. Lin-Hong Zheng & Nor Eeza Zainal Abidin & Mohammad Nazri Mohd Nor & Yue-Yun Xu & Xiao-Wei Feng, 2023. "Sustainable Coupling Coordination and Influencing Factors of Sports Facilities Construction and Social Economy Development in China," Sustainability, MDPI, vol. 15(3), pages 1-17, February.

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