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Network Structure Features and Influencing Factors of Tourism Flow in Rural Areas: Evidence from China

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  • Yuzhen Li

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Guofang Gong

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Fengtai Zhang

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Lei Gao

    (CSIRO, Waite Campus, Urrbrae, Mitcham, SA 5064, Australia)

  • Yuedong Xiao

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Xingyu Yang

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Pengzhen Yu

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

Abstract

Exploring the spatial network structure of tourism flow and its influencing factors is of great significance to the transmission of characteristic culture and the sustainable development of tourism in tourist destinations, especially in backward rural areas. Taking Qiandongnan Miao and Dong Autonomous Prefecture (hereinafter referred to as Qiandongnan Prefecture) as an example, this paper adopts social network analysis and Quadratic Assignment Procedure regression analysis to study the network structural characteristics and influencing factors of tourism flow using online travel blog data. The results show that: (1) There are seasonal changes in tourism flow, but the attractions that tourists pay attention to do not change with the seasons. (2) The tightness of the tourism flow network structure is poor. The core nodes are unevenly distributed, and there are obvious structural holes. (3) The density of the tourism flow network is low. There is a clear core–periphery structure in the network, and the core area has a weak driving effect on the periphery area. There are more cohesive subgroups in the network, but the degree of connectedness between the subgroups varies greatly. (4) Geographical adjacency, transportation accessibility, and tourism resource endowment influence tourism flow network structure. The study found that the influencing factors of tourism flow in rural areas are different from those in urban areas. These results provide useful information for the marketing and development of tourism management departments in rural areas.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9623-:d:880667
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    Cited by:

    1. Zhi Li & Jinsong Liu, 2023. "Evolution Process and Characteristics of Multifactor Flows in Rural Areas: A Case Study of Licheng Village in Hebei, China," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    2. Zhaofeng Wang & Dongchun Huang & Jing Wang, 2023. "Exploring Spatial Correlations of Tourism Ecological Security in China: A Perspective from Social Network Analysis," IJERPH, MDPI, vol. 20(5), pages 1-15, February.
    3. Chen-Hao Xue & Yong-Ping Bai, 2023. "Spatiotemporal Characteristics and Factors Influencing Urban Tourism Market Network in Western China: Taking Chengdu as an Example," Sustainability, MDPI, vol. 15(10), pages 1-21, May.

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