IDEAS home Printed from
   My bibliography  Save this article

Research on the Structural Characteristics and Evolutionary Process of China’s Tourism Investment Spatial Correlation Network


  • Haijian Li

    (School of History Culture and Tourism, Jiangsu Normal University, Xuzhou 221116, China)

  • Wujie Xie

    (School of History Culture and Tourism, Jiangsu Normal University, Xuzhou 221116, China)


The paper uses the revised gravity model to measure the intensity of tourism investment spatial correlation, constructs the spatial correlation matrix of tourism investment, and uses the social network method to analyze the structural characteristics and evolutionary process of tourism investment spatial correlation network based on 31 provinces in China from 2000 to 2016. The findings revealed: (1) The spatial correlation quantity of interprovincial tourism investment continues to grow, with Beijing, Jiangsu, Zhejiang, Shanghai, Shandong, and Guangdong at the top of the list. (2) Overall network density and correlation are rising, and the spatial correlation of interprovincial tourism investment is increasingly close. Network hierarchy and network efficiency are decreasing, and network stability has been enhanced. (3) Degree centrality and closeness centrality of each province have shown a significant increase; Beijing, Shandong, Guangdong, Jiangsu, Zhejiang, and Shanghai are the top six and in the center of the network. Most provinces have improved betweenness centrality, Beijing, Guangdong, Shandong, Liaoning, Shaanxi, and Hunan have a strong betweenness centrality with strong intermediary capacity. (4) The core area mainly includes eastern and central provinces, and the periphery areas mainly include western and northeastern provinces. The network connection density of the core and periphery areas shows an increasing trend, while the network linkage density between the core and periphery areas shows a downward trend.

Suggested Citation

  • Haijian Li & Wujie Xie, 2022. "Research on the Structural Characteristics and Evolutionary Process of China’s Tourism Investment Spatial Correlation Network," IJERPH, MDPI, vol. 19(23), pages 1-20, November.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15661-:d:983636

    Download full text from publisher

    File URL:
    Download Restriction: no

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Li, Hengyun & Chen, Jason Li & Li, Gang & Goh, Carey, 2016. "Tourism and regional income inequality: Evidence from China," Annals of Tourism Research, Elsevier, vol. 58(C), pages 81-99.
    2. Piervito Bianchi & Giulio Mario Cappelletti & Elisabetta Mafrolla & Edgardo Sica & Roberta Sisto, 2020. "Accessible Tourism in Natural Park Areas: A Social Network Analysis to Discard Barriers and Provide Information for People with Disabilities," Sustainability, MDPI, vol. 12(23), pages 1-14, November.
    3. Hwayoon Seok & George A. Barnett & Yoonjae Nam, 2021. "A social network analysis of international tourism flow," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 419-439, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenming Shi & Meifeng Luo & Mengjie Jin & Seu Keow Cheng & Kevin X. Li, 2020. "Urban–rural income disparity and inbound tourism: Spatial evidence from China," Tourism Economics, , vol. 26(7), pages 1231-1247, November.
    2. Gabriela Carmen Pascariu & Bogdan-Constantin Ibanescu, 2018. "Determinants and Implications of the Tourism Multiplier Effect in EU Economies. Towards a Core-Periphery Pattern?," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 20(S12), pages 982-982, November.
    3. Wu, Hanjun & Hong Tsui, Kan Wai & Ngo, Thanh & Lin, Yi-Hsin, 2020. "Impacts of aviation subsidies on regional wellbeing: Systematic review, meta-analysis and future research directions," Transport Policy, Elsevier, vol. 99(C), pages 215-239.
    4. Edgardo Sica & Roberta Sisto & Piervito Bianchi & Giulio Cappelletti, 2020. "Inclusivity and Responsible Tourism: Designing a Trademark for a National Park Area," Sustainability, MDPI, vol. 13(1), pages 1-11, December.
    5. Zhixin Zeng & Xiaojun Wang, 2021. "Effects of Domestic Tourism on Urban-Rural Income Inequality: Evidence from China," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
    6. Natalia Porto & Natalia Espinola & Laura Carella, 2020. "Income inequality, tourism and resources endowment in Uruguay: a spatial and distributional approach," Asociación Argentina de Economía Política: Working Papers 4393, Asociación Argentina de Economía Política.
    7. Arunava Bandyopadhyay & Soumen Rej & Kashif Raza Abbasi & Ashar Awan, 2023. "Nexus between tourism, hydropower, and CO2 emissions in India: fresh insights from ARDL and cumulative fourier frequency domain causality," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 10903-10927, October.
    8. Zhixin Zeng & Xiaojun Wang, 2021. "Spatial Effects of Domestic Tourism on Urban-Rural Income Inequality," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    9. Maria Giovina Pasca & Grazia Chiara Elmo & Gabriella Arcese & Giulio Mario Cappelletti & Olimpia Martucci, 2022. "Accessible Tourism in Protected Natural Areas: An Empirical Study in the Lazio Region," Sustainability, MDPI, vol. 14(3), pages 1-12, February.
    10. Bowen Xiang & Rushuang Chen & Gaofeng Xu, 2022. "Uncovering Network Heterogeneity of China’s Three Major Urban Agglomerations from Hybrid Space Perspective-Based on TikTok Check-In Records," Land, MDPI, vol. 12(1), pages 1-21, December.
    11. Lv, Zhike, 2020. "Does tourism affect the informal sector?," Annals of Tourism Research, Elsevier, vol. 80(C).
    12. Yuzhen Li & Guofang Gong & Fengtai Zhang & Lei Gao & Yuedong Xiao & Xingyu Yang & Pengzhen Yu, 2022. "Network Structure Features and Influencing Factors of Tourism Flow in Rural Areas: Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    13. Daxin Dong & Xiaowei Xu & Hong Yu & Yanfang Zhao, 2019. "The Impact of Air Pollution on Domestic Tourism in China: A Spatial Econometric Analysis," Sustainability, MDPI, vol. 11(15), pages 1-16, August.
    14. Christian Myles Rogerson, 2017. "The Economic Geography of South Africa’s International Tourism Industry," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 13(2), pages 66-80, April.
    15. Mohd Nor, Norma Azuli & Mohd Salleh, Norlida Hanim & Falatehan, A Faroby, 2021. "The Effect of Tourism Expenditure on the Economy: A New Evidence," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 55(3), pages 23-34.
    16. Jie Yu & Fei You & Jian Wang & Zishan Wang, 2023. "Evolution Modes of Chili Pepper Industry Clusters under the Perspective of Social Network—An Example from Xinfu District, Xinzhou, Shanxi Province," Sustainability, MDPI, vol. 15(6), pages 1-14, March.
    17. Yuewei Wang & Mengmeng Xi & Hang Chen & Cong Lu, 2022. "Evolution and Driving Mechanism of Tourism Flow Networks in the Yangtze River Delta Urban Agglomeration Based on Social Network Analysis and Geographic Information System: A Double-Network Perspective," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    18. Andrzej Tucki & Korneliusz Pylak, 2021. "Collective or Individual? What Types of Tourism Reduce Economic Inequality in Peripheral Regions?," Sustainability, MDPI, vol. 13(9), pages 1-16, April.
    19. Kosztyán, Zsolt Tibor & Király, Ferenc & Kurbucz, Marcell Tamás, 2024. "Európai cégek tulajdonosi szerkezetének dinamikus hálózatelemzése [Investigating the ownership structure of European companies using dynamic network analysis methods]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(1), pages 57-85.
    20. Jiao, Xiaoying & Chen, Jason Li & Li, Gang, 2021. "Forecasting tourism demand: Developing a general nesting spatiotemporal model," Annals of Tourism Research, Elsevier, vol. 90(C).


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15661-:d:983636. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.