基于Bootstrap-DEA模型测度2009—2019年中国省域旅游效率，采用改进Markov链检验其是否呈俱乐部趋同分布，并探讨其时空趋同特征，最后结合System-GMM模型探明影响中国旅游效率的重要因素。结果表明：中国省域旅游效率“东高西低”，时序演变剧烈，呈现出显著的俱乐部趋同效应；在短时段下，中间等级旅游效率更容易向上转移，而长时段下，两极等级旅游效率更容易向下转移；在不同邻域水平下，大多数省市与其邻域效率转移方向基本一致，只有部分东部和旅游热点省市摆脱邻域低效率拖累，而少数西部省市跌入低效率“陷阱”；产业结构、旅游交通、旅游资源禀赋、旅游产业集聚、旅游基础设施对旅游效率均具有显著的积极影响，但影响机制在不同地区呈现出显著的异质性。

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.