Spatial mismatch and its formation mechanisms between tourism eco-efficiency and ecotourism attention in China

Scientific understanding of the spatial mismatch between tourism eco-efficiency in physical space and ecotourism attention in virtual space and its formation mechanism is a new initiative to accelerate the formation of a new type of tourism human-land relationship and to promote the modernization of the harmonious coexistence of human beings and nature in high quality under the wave of digital-real integration. Based on the Python platform, we constructed a heterogeneous dataset of network data and statistical data from multiple sources to understand the spatial and temporal characteristics of tourism eco-efficiency and ecotourism network attention in 30 provincial-level areas (hereafter province) in China from 2011 to 2021, and used the gravity trajectory model and spatial mismatch index to investigate the evolution of the center of gravity of the two and the spatial mismatch relationship, and analyzed the formation mechanism of the spatial mismatch relationship with the help of the Random Forest Regression Algorithm. With the help of Random Forest Regression Algorithm, we analyzed the formation mechanism of spatial mismatch relationship. The results showed that: (1) China's tourism eco-efficiency and ecotourism network attention generally showed an increasing trend, and formed a zonal differentiation of "eastern region>central region>western region"; the centers of gravity of them showed a southwesterly shift trend, but the former's shift distance to the west (south) was significantly smaller (larger) than that of the latter. (2) China's tourism eco-efficiency and ecotourism network attention were mainly at positive spatial mismatch level, and form a spatial pattern of "negative spatial mismatch in the provinces of the eastern region of China and positive spatial mismatch in the provinces of the central and western regions". (3) The spatial mismatch between tourism eco-efficiency and ecotourism network attention was influenced by multiple factors; as the level of these factors increased, industrial structure, government regulation, transportation facilities and the digital economy would contribute to the growth of tourism eco-efficiency, while tourism agglomeration, technological innovation and market potential would contribute to the growth of ecotourism network attention.