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ABSTRACT
The network theory is having an important role in tourism research, which provides a useful lens for understanding the structures and interrelations among tourism destinations. This paper analyzes the structure of China’s inbound tourist flow network (ITFN) in a dynamic view, from three levels: the global, the meso, and the individual, meanwhile the correlation between network structure and tourism performance is verified. The interpretation of ITFN structure has been divided into three meanings: the global-level metrics identify the holistic topology, the meso-level metrics are used to understand collaboration, and the individual-level metrics work for competitiveness assessing. China’s case shows the ITFN has a small-world characteristic but gradually becomes weak, the collaboration clusters become more, and the difference of competitiveness among regions has amplified. Moreover, the small-world nature and individual competitiveness have positive impacts on tourism performance, but the correlation between performance and clustering coefficient is significantly negative.
Acknowledgement
The author gratefully acknowledges the financial support of the National Key Research and Development Program of China through the No. 2019YFC0507802, the National Natural Science Foundation of China (NSFC) through the grant No. 41801139, and the Strategic Priority Research Program of CAS through XDA23100302.
Disclosure statement
No potential conflict of interest was reported by the author(s).