Abstract

This article investigates the rank–size distribution and spatio-temporal dynamics of domestic and inbound tourist flows in Chinese cities using Zipf’s law and the rank clock method. The results show that Zipf’s law captures key characteristics of the rank–size distribution of tourist flows to China’s cities. There are large differences between the inbound and domestic tourist flows not only for the top 100 but also for all cities. Three types of Zipf’s law are found to apply to China’s subregions. At the individual city level, most rank changes of the top 100 inbound and domestic tourist arrival cities appear in the lower part of the rank. The average rank shift distances of the top 100 inbound and domestic tourist arrival cities are 6.122 and 6.006, respectively. The dynamics of the rank–size distribution of domestic tourist flows to the top 100 cities are more stable than those of inbound tourist flows.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call