SCIENTIA GEOGRAPHICA SINICA ›› 2017, Vol. 37 ›› Issue (11): 1705-1711.doi: 10.13249/j.cnki.sgs.2017.11.012

• Orginal Article • Previous Articles     Next Articles

The Spatial Correlation of Economic Growth of Inbound Tourism in China Based on Social Network Analysis

Lijun Ma(), Yun Long   

  1. Business School of Xiangtan University, Xiangtan 411105, Hunan,China
  • Received:2016-12-06 Revised:2017-02-20 Online:2017-11-20 Published:2017-11-20
  • Supported by:
    National Nature Sciences Foundation of China (41501156), Excellent Youth Foundation of Hunan Educational Committee (15B243) , Sciences Foundation of Hunan Province (14JD56)


This article collects data from 1991 to 2014 to analyze the spatial correlation of economic growth of inbound tourism in China by using the method of Granger Causality Test and Social Network Analysis. Then, we reveal its influencing factors based on QAP correlation and QAP regression. The results show that: 1) Spatial correlation of China’s inbound tourism economical development is highly connected. There is no independent development area. It exists multiple superimposed effects, and spillovers have been greater than benefit. However, the network is not compact entirely, and connections are dispersive generally. 2) The province economy is more developed, the higher the density of individual network, and the more spatial associations with other provinces. Moreover, the correlations of some central and western regions have more connections and stronger mediating effects. 3) The network structure can be divided into four plates. The first plate is “agent plate” that plays a role of bridge and the second plate is “main beneficial plates” that acts as an engine in the integrated network. The third and the fourth plate are both belong to “main beneficial plates”. The transfer mechanism of spatial correlation is that the second plate conveys energy from the first plate to the third and the fourth plate. 4) Number of inbound tourists, distribution of tourism resources, economic development and traffic convenience are important factors of the spatial correlation of economic growth in China’s inbound tourism.

Key words: inbound tourism, economic growth, spatial correlation, social network analysis

CLC Number: 

  • F59