IDEAS home Printed from https://ideas.repec.org/a/gam/jtourh/v5y2024i1p5-79d1331093.html
   My bibliography  Save this article

The Spatial Structure and Influencing Factors of the Tourism Economic Network in the Yangtze River Delta Urban Agglomeration

Author

Listed:
  • Xiao Feng

    (Department of Hotel and Tourism, College of Business, Daegu University, Gyeongsan 38453, Republic of Korea)

  • Chang Pan

    (Department of Hotel and Tourism, College of Business, Daegu University, Gyeongsan 38453, Republic of Korea)

  • Fengying Xu

    (Department of Hotel and Tourism, College of Business, Daegu University, Gyeongsan 38453, Republic of Korea)

Abstract

The optimization of a tourism economic network is critical in the promotion of the high-quality development of a regional tourism economy. In order to explore the spatial network structure of the tourism economy of the Yangtze River Delta urban agglomeration and its influencing factors, this study used a modified gravity model and social network analysis methods for evaluation and analysis. The results show the following: (1) the spatial network of the tourism economy in the Yangtze River Delta urban agglomeration in 2016–2021 was characterized by significant non-equilibrium; however, that trend has weakened, and the tourism connections are now stronger in economically developed regions. (2) The density of the network structure was slightly strengthened. The structure of the tourism economy network shows an obvious core–periphery distribution pattern. The external radiation of the center city was enhanced, and the core area of the network expanded. (3) The concept of the “small world” is characterized by a significant evolution from five major associations to four major associations during the study period. (4) The quadratic assignment method (QAP) of regression analysis showed that tourism service reception capacity, tourism information flow, tourism resource endowments and transportation convenience make a significant contribution to the formation of the spatial network of inter-city tourism economic connections. The results of this study can provide a theoretical basis for the optimization of the tourism economic network of urban agglomerations and the scientific decision-making underpinning tourism economic cooperation.

Suggested Citation

  • Xiao Feng & Chang Pan & Fengying Xu, 2024. "The Spatial Structure and Influencing Factors of the Tourism Economic Network in the Yangtze River Delta Urban Agglomeration," Tourism and Hospitality, MDPI, vol. 5(1), pages 1-20, February.
  • Handle: RePEc:gam:jtourh:v:5:y:2024:i:1:p:5-79:d:1331093
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2673-5768/5/1/5/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2673-5768/5/1/5/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sylvain Dejean, 2020. "The role of distance and social networks in the geography of crowdfunding: evidence from France," Regional Studies, Taylor & Francis Journals, vol. 54(3), pages 329-339, March.
    2. Pavlovich, Kathryn, 2014. "A rhizomic approach to tourism destination evolution and transformation," Tourism Management, Elsevier, vol. 41(C), pages 1-8.
    3. Yin, Ping & Lin, Zhibin & Prideaux, Bruce, 2019. "The impact of high-speed railway on tourism spatial structures between two adjoining metropolitan cities in China: Beijing and Tianjin," Journal of Transport Geography, Elsevier, vol. 80(C).
    4. Li, Shuying & Garces, Edwin & Daim, Tugrul, 2019. "Technology forecasting by analogy-based on social network analysis: The case of autonomous vehicles," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    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. 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.
    2. Huanhuan Hua & Amare Wondirad, 2020. "Tourism Network in Urban Agglomerated Destinations: Implications for Sustainable Tourism Destination Development through a Critical Literature Review," Sustainability, MDPI, vol. 13(1), pages 1-16, December.
    3. V. I. Blanutsa, 2022. "Geographic Research of the Platform Economy: Existing and Potential Approaches," Regional Research of Russia, Springer, vol. 12(2), pages 133-142, June.
    4. Ren, Xiaohang & Zeng, Gudian & Dong, Kangyin & Wang, Kun, 2023. "How does high-speed rail affect tourism development? The case of the Sichuan-Chongqing Economic Circle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    5. Gore, Surabhi & Borde, Nilesh & Desai, Purva Hegde & George, Babu, 2022. "A Structured Literature Review of the Tourism Area Life Cycle Concept," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 10(1), pages 1-20.
    6. Saxena, Gunjan, 2015. "Imagined relational capital: An analytical tool in considering small tourism firms' sociality," Tourism Management, Elsevier, vol. 49(C), pages 109-118.
    7. Zavattaro, Staci M. & Daspit, Joshua J. & Adams, Frank G., 2015. "Assessing managerial methods for evaluating place brand equity: A qualitative investigation," Tourism Management, Elsevier, vol. 47(C), pages 11-21.
    8. Yang, Zaoli & Zhang, Weijian & Yuan, Fei & Islam, Nazrul, 2021. "Measuring topic network centrality for identifying technology and technological development in online communities," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    9. Mariano Gallo & Rosa Anna La Rocca, 2022. "The Impact of High-Speed Rail Systems on Tourist Attractiveness in Italy: Regression Models and Numerical Results," Sustainability, MDPI, vol. 14(21), pages 1-33, October.
    10. Kang, Meiling & Li, Yucheng & Zhao, Zhongkuang & Song, Min & Yi, Jun, 2023. "Travel costs and inter-city collaborative innovation: Evidence of high-speed railway in China," Structural Change and Economic Dynamics, Elsevier, vol. 65(C), pages 286-302.
    11. Liu, Bing & Huang, Songshan (Sam) & Fu, Hui, 2017. "An application of network analysis on tourist attractions: The case of Xinjiang, China," Tourism Management, Elsevier, vol. 58(C), pages 132-141.
    12. Sunny Sun & Lina Zhong & Rob Law & Xiaoya Zhang & Liyu Yang & Meiling Li, 2022. "A Proposed DISE Approach for Tourist Destination Crisis Management," Sustainability, MDPI, vol. 14(17), pages 1-16, September.
    13. Raisi, Hossein & Baggio, Rodolfo & Barratt-Pugh, Llandis & Willson, Gregory, 2020. "A network perspective of knowledge transfer in tourism," Annals of Tourism Research, Elsevier, vol. 80(C).
    14. Runbo Zhao & Huiying Zhang & Marina Yue Zhang & Fei Qu & Yunlong Xu, 2023. "Competitor-Weighted Centrality and Small-World Clusters in Competition Networks on Firms’ Innovation Ambidexterity: Evidence from the Wind Energy Industry," IJERPH, MDPI, vol. 20(4), pages 1-18, February.
    15. Francesca Pagliara & Filomena Mauriello & Yin Ping, 2021. "Analyzing the Impact of High-Speed Rail on Tourism with Parametric and Non-Parametric Methods: The Case Study of China," Sustainability, MDPI, vol. 13(6), pages 1-10, March.
    16. Ruggieri, Giovanni & Iannolino, Salvatore & Baggio, Rodolfo, 2022. "Tourism destination brokers: A network analytic approach," Annals of Tourism Research, Elsevier, vol. 97(C).
    17. Douglas S. Noonan & Shiri M. Breznitz & Sana Maqbool, 2021. "Looking for a change in scene: analyzing the mobility of crowdfunding entrepreneurs," Small Business Economics, Springer, vol. 57(2), pages 685-703, August.
    18. Yadav, Jitendra & Yadav, Rambalak & Sahore, Nidhi & Mendiratta, Aparna, 2023. "Digital social engagements and knowledge sharing among sports fans: Role of interaction, identification, and interface," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    19. César Daniel Aguilar-Becerra & Oscar Frausto-Martínez & Hernando Avilés-Pineda & Jair J. Pineda-Pineda & Jennifer Caroline Soares & Maximino Reyes Umaña, 2019. "Path Dependence and Social Network Analysis on Evolutionary Dynamics of Tourism in Coastal Rural Communities," Sustainability, MDPI, vol. 11(18), pages 1-23, September.
    20. 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.

    Corrections

    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:jtourh:v:5:y:2024:i:1:p:5-79:d:1331093. 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: https://www.mdpi.com .

    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.