College of Culture and Tourism, Weifang University, Weifang, China.
Editorial Department of Journal, Weifang University, Weifang, China.
Front Public Health. 2023 Feb 20;11:1127980. doi: 10.3389/fpubh.2023.1127980. eCollection 2023.
Tourism ecosystem health is key to high-quality tourism development. China is now promoting sustainable development and high-quality transformation and upgrading of regional tourism; thus, the research on tourism ecosystem health is of practical significance. Based on the DPSIR model, an evaluation index system of tourism ecosystem health in China was constructed. Then the entropy weight method, spatial autocorrelation analysis, Markov chain analysis, and quantile regression were used to explore the dynamic evolution characteristics and driving factors of tourism ecosystem health in China from 2011 to 2020. The following conclusions were drawn: (1) The tourism ecosystem health in China showed an M-shaped fluctuation process as a whole, with significant spatial correlation and spatial difference. (2) There was a "path-dependent" and "self-locking" effect on the type transfer of tourism ecosystem health, and the type transfer was mainly between adjacent types in successive transfers, with the probability of downward transfer higher than upward transfer, and the geospatial background played a significant role in its dynamic evolution process. (3) In provinces with low tourism ecosystem health type, the negative effect of technological innovation capacity was more significant, and the influence coefficient of the positive effect of tourism environmental regulation and information technology level was larger, while in provinces with high tourism ecosystem health type, the negative effect of tourism industry agglomeration was more significant, and the influence coefficient of the positive effect of tourism industry structure and tourism land-use scale was larger.
旅游生态系统健康是高质量旅游发展的关键。中国目前正在推进区域旅游的可持续发展和高质量转型升级；因此，对旅游生态系统健康的研究具有现实意义。本文基于 DPSIR 模型，构建了中国旅游生态系统健康评价指标体系。然后，运用熵权法、空间自相关分析、马尔可夫链分析和分位数回归方法，探讨了 2011-2020 年中国旅游生态系统健康的动态演变特征及其驱动因素。得到以下结论：（1）中国旅游生态系统健康整体呈“M”型波动过程，具有显著的空间相关性和空间差异。（2）旅游生态系统健康类型的转移存在“路径依赖”和“自我锁定”效应，且类型转移主要在相邻类型之间发生，连续转移中以向下转移为主，向上转移为辅，地理空间背景在其动态演变过程中发挥了重要作用。（3）在旅游生态系统健康水平较低的省份，技术创新能力的负面影响更为显著，旅游环境规制和信息技术水平的积极影响系数较大，而在旅游生态系统健康水平较高的省份，旅游产业集聚的负面影响更为显著，旅游产业结构和旅游土地利用规模的积极影响系数较大。
