Modelling international tourism flows to China: A panel data analysis with the gravity model

Lizhi Xu; Shouyang Wang; Jingjing Li; Ling Tang; Yanmin Shao

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Modelling international tourism flows to China: A panel data analysis with the gravity model

Lizhi Xu ^[2] ; Shouyang Wang ^[3] ; Jingjing Li ^[1] ; Ling Tang ^[1] ; Yanmin Shao ^[4]
1. [1] Beihang University
  
  Beihang University
  
  China
2. [2] Beijing Union University
  
  Beijing Union University
  
  China
3. [3] Graduate University of Chinese Academy of Sciences
  
  Graduate University of Chinese Academy of Sciences
  
  China
4. [4] University of Science and Technology Beijing
  
  University of Science and Technology Beijing
  
  China
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Localización: Tourism economics: the business and finance of tourism and recreation, ISSN 1354-8166, Vol. 25, Nº. 7, 2019, págs. 1047-1069
Idioma: inglés
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Resumen
- Based on the theoretical and empirical foundations of the gravity model, this article systematicallyinvestigates the determinants of international tourist arrivals to China. Various origin–destination(O-D) linked factors accounting for the economic, political and social/culture preferences betweenChina and its tourist origins are particularly explored. Utilizing a panel data set of tourist arrivals toChina from 21 countries from 1995 to 2014, the results suggest that the basic gravity determinantsall have significant effects on tourist arrivals to China. Furthermore, four O-D linked factors arefound to be significant in explaining the number of international tourists and have a greater tourist-enhancing effect. In particular, overseas Chinese, proxying for social/culture-preferential rela-tionships, have caused significant increases in tourism arrivals to China of approximately 120%when the percentage of ethnic Chinese in the origin countries’ population is more than 1%. ForChina to be chosen as a manufacturing and processing centre by international enterprises, variousO-D relationships are important but neglected factors of Chinese tourism patterns, with impor-tant policy implications.