Nonlinear driving mechanisms of system adaptability in China's art and cultural tourism industry.

With the transformation of the cultural tourism industry from scale expansion to high-quality development, increasing attention has been paid to the synergistic mechanisms between culture and tourism. However, existing researches have predominantly focused on macro-level coordinated development, while systematic quantitative analyses of art and cultural tourism-centered on artistic creation and expression-remain limited, particularly in terms of factor matching and dynamic adaptation mechanisms. Therefore, this research takes China's art and cultural tourism as the research object and utilizes panel data from 31 provincial administrative regions from 2014 to 2023. From a spatiotemporal perspective, the study examines the evolutionary characteristics of system adaptability and coupling coordination degree. Furthermore, the nonlinear driving mechanisms of system adaptability are explored by integrating the XGBoost model with SHAP (Shapley Additive Explanations). The results indicate that: (1) during the study period, the overall level of system adaptability in China's art and cultural tourism exhibits a fluctuating upward trend, but remains primarily at a low to intermediate stage, with significant regional disparities; (2) system adaptability and coupling coordination degree show consistent evolutionary trends, while system adaptability is more sensitive in capturing the structural and functional matching between art and cultural tourism; (3) based on the XGBoost-SHAP analysis, ecological environment and public service capacity constitute the fundamental constraints of system adaptability, transportation and information infrastructure provide spatial and functional support, whereas cultural education and innovation investment serve as the core endogenous drivers for sustained improvement; (4) the effects of different driving factors on system adaptability exhibit significant nonlinear and stage-specific characteristics, indicating that the evolution of system adaptability is a dynamic process driven by the coordinated interaction of multiple factors.