Markov transfer probability matrix.

Based on panel data from 18 major tea-producing provinces in China from 2013 to 2022, this study constructs an evaluation index system for tea tourism integration. it employs the entropy method, kernel density estimation, Markov chain, and obstacle model to analyze integration levels, spatiotemporal evolution patterns, and obstacle factors. The results show that: (1) China tea tourism integration shows an upward trend nationally, with four tea regions exhibiting a “Jiangnan> South China> Southwest> Jiangbei” developmental hierarchy, where the Southwest region demonstrates the fastest growth. (2) Interregional development disparities are widening, coupled with intraregional imbalances. Provincial development displays “club convergence” characteristics, with low-level areas exhibiting significant spatial spillover effects from neighboring high-level regions. (3) Common obstacle factors prevail across provinces, particularly industrial economic conversion efficiency, constituting the key constraint for integration development.