Based on the Bootstrap-DEA model, the tourism efficiency of Chinas provinces from 2009 to 2019 was measured, and then the improved Markov chain was used to test whether the tourism efficiency shows the club convergence distribution, and discuss the characteristics of temporal and spatial convergence, and finally the System-GMM model was combined to explore the important factors that affect the efficiency of Chinas tourism. The results show that Chinas provincial tourism efficiency is “high in the east and low in the west”.The time series evolves drastically, but it shows a significant club convergence effect. In a short period of time, the middle-level tourism efficiency is easier to transfer upwards, while in a long period of time, the efficiency of bipolar tourism is easier to shift downwards. At different neighborhood levels, most provinces and cities have basically the same direction of efficiency transfer with their neighborhoods. Only some eastern and tourist hotspot provinces and cities get rid of the inefficiency of neighborhoods, while a few western provinces and cities have fallen into low efficiency “trap”.Industrial structure, tourism transportation, tourism resource endowment, tourism industry agglomeration, and tourism infrastructure all have a significant positive impact on tourism efficiency, but the influence mechanism shows significant heterogeneity in different regions.

tourism efficiency; club convergence; temporal and spatial characteristics; influencing factors; Markov chain