A thorough understanding of the fluctuations of tourist flows provides useful insights concerning the nature of tourist demand. This study aims to investigate the fluctuation patterns and dynamics of inbound tourist flows to China using a complex network approach. Several measures, such as the network topological parameters of degree and degree distribution, betweenness centrality, and shortest path length, are utilized to discover important fluctuation patterns and the transition distance. Based on the empirical results, six important fluctuation patterns of inbound tourist flows to China are recognized. These fluctuation patterns are important intermediaries in the process of transformation of the fluctuation patterns and can be viewed as a prelude to changes in the inbound tourist flows. The value of 3.38 found for the average transition distance suggests that the transformation occurs approximately every three to four quarters. These findings are useful for understanding the inherent laws and transformations governing fluctuations in tourist flows.