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The Structure and Evolution of the Tourism Economic Network of the Tibetan Plateau and Its Driving Factors

Author

Listed:
  • Xiaodong Chen

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China
    University of Chinese Academy of Sciences, Beijing 100101, China)

  • Tian Wang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China
    University of Chinese Academy of Sciences, Beijing 100101, China)

  • Xin Zheng

    (University of Chinese Academy of Sciences, Beijing 100101, China
    Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100049, China)

  • Fang Han

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China)

  • Zhaoping Yang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830000, China)

Abstract

Tourism is one of the core industries driving the economy on the Tibetan Plateau towards green development. Adopting the improved gravity model, social network analysis, and quadratic assignment procedure, this paper explores the structure and evolution characteristics of the tourism economic network on the Tibetan Plateau from 2015 to 2019. The results are as follows: (1) the tourism economic strength increased over time, but it was generally higher in Qinghai Province and lower in Tibet. (2) The network density exhibited an upwards trend overall. (3) The structure of the tourism economic network presented a significant core–periphery distribution pattern. Xining, Haixi, and Lhasa acted as a bridge between the spatial network structure of the tourism economy and had a structural hole advantage. However, some remote cities, such as Ali, Naqu, and Guoluo, had low network centricity. (4) The quadratic assignment procedure regression analysis showed that the A-level attractions and star-rated hotels significantly advanced the formation of the spatial association. This study concludes with recommendations for promoting tourism economic associations for policy-makers.

Suggested Citation

  • Xiaodong Chen & Tian Wang & Xin Zheng & Fang Han & Zhaoping Yang, 2022. "The Structure and Evolution of the Tourism Economic Network of the Tibetan Plateau and Its Driving Factors," Land, MDPI, vol. 11(2), pages 1-18, February.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:2:p:241-:d:743021
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    Cited by:

    1. Baitong Li & Jian Li & Chen Liu & Xinyan Yao & Jingxuan Dong & Meijun Xia, 2023. "Provincial Inclusive Green Growth Efficiency in China: Spatial Correlation Network Investigation and Its Influence Factors," Land, MDPI, vol. 12(3), pages 1-24, March.
    2. Ling-Ling Fan & Ya-Lan Shi & Xiao-Yan Wang, 2025. "Spatial Network Structure and Influencing Factors of the Urban Tourism Economy in China: An Empirical Study Based on 284 Prefecture-Level Cities," SAGE Open, , vol. 15(4), pages 21582440251, December.
    3. Shanshan Shi & Menghao Liu & Jianchao Xi, 2022. "Hierarchical Structure and Organizational Model of County Tourism Network of the Tibetan Plateau," Land, MDPI, vol. 11(11), pages 1-18, October.
    4. Kehan Shi & Jinfang Wang & Xiaojin Liu & Xiaoying Zhao, 2022. "Impact of high-speed rail on tourism in China," PLOS ONE, Public Library of Science, vol. 17(12), pages 1-18, December.
    5. Liang Xu & Zhigao Liu, 2022. "The Evolution of the Spatial Patterns of Startup Firms in the Tibet Autonomous Region, China in the 21st Century," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    6. Rui Ding & Jun Fu & Yiling Zhang & Ting Zhang & Jian Yin & Yiming Du & Tao Zhou & Linyu Du, 2022. "Research on the Evolution of the Economic Spatial Pattern of Urban Agglomeration and Its Influencing Factors, Evidence from the Chengdu-Chongqing Urban Agglomeration of China," Sustainability, MDPI, vol. 14(17), pages 1-19, September.
    7. Ziqiang Li & Jianchao Xi & Sui Ye, 2025. "Identifying Suitable Zones for Tourism Activities on the Qinghai–Tibet Plateau Based on Trajectory Data and Machine Learning," Land, MDPI, vol. 14(9), pages 1-18, September.
    8. Yalan Shi & Miaojing Yu & Yongqing Cao & Yanxia Tan & Wenyue Liang, 2025. "Spatial Network Structure of the Global Tourism Economy: Global and Continental Perspectives From 1995 to 2019," SAGE Open, , vol. 15(3), pages 21582440251, July.

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