Although tourism has gradually become a popular form of leisure and entertainment in China, the quality of China’s tourism development remains unclear. Through the panel data of 30 provinces in China, an SBM-DEA model and a social network analysis are used to explore the quality of tourism development, and a spatial econometric regression is used to identify the relevant factors affecting tourism efficiency. The study found that the level of tourism efficiency in Southwest China is high and stable. The northwest region has a low level of tourism efficiency, but a slow growth trend. The rest of the regions show fluctuating trends of tourism efficiencies. The spatial correlation network of provincial tourism efficiency is gradually complicated. Regarding influencing factors, the number of patents granted, traffic levels, financial development, and government macro-control all have positive effects on tourism efficiency. The study uncovered some useful management insights and implications for the travel industry.

The exploration of the spatial network structure of agricultural water use efficiency (AWUE) and its influencing factors for promoting water saving and improving water use efficiency in regional agricultural production is of great importance. In this paper, the modified gravity model and social network analysis methods were used to study the spatial correlation characteristics and influencing factors of AWUE in China between the years 2008 and 2019. It was found that (1) the overall trend of AWUE in China has been fluctuating and declining, and there are obvious differences in AWUE in each region; (2) the spatial network structure of AWUE in China is complex and relatively stable, with close interprovincial connections and obvious spatial spillover effects; (3) Shanghai, Beijing, Jiangsu, and Zhejiang are at the center of the network; and (4) the differences between geographical adjacency, technological development level, farmers’ income, and natural resource endowment have significant effects on the development of the AWUE network. These results provide a theoretical basis for the government to improve AWUE and promote collaborative regional development.

The tourism, urbanization, technology, and the ecological environment both promote and restrict each other. Coordinating the relationship between the four is of great significance to the realization of high-quality sustainable regional development. Taking the Yunnan–Guizhou–Sichuan region as an example, this paper constructs an uncoordinated coupling model for the tourism–urbanization–technology–ecological environment system. Using exploratory spatial analysis and geographic information systems, this paper reveals the temporal and spatial evolution law affecting the uncoordinated coupling relationship between tourism, urbanization, technology and the ecological environment in the Yunnan–Guizhou–Sichuan region from 2010 to 2020, before establishing a panel Tobit model that is used to explore the factors affecting the four systems. The research shows the following: (1) The level of comprehensive development for tourism, urbanization, technology, and the ecological environment in Yunnan, Guizhou, and Sichuan has increased rapidly. Of all these, the tourism industry was the most affected by COVID-19 in 2020, while the level of urbanization, technology, and ecological environment developments in the three provinces has become similar over time. (2) Uncoordinated development between cities is a prominent problem; while the uncoordinated coupling spatial agglomeration in various regions is relatively stable, the proportion of cities with no significant agglomeration form amounts to more than 70%, with mostly low–low (L–L) and high–high (H–H) agglomeration types. (3) The degree to which uncoordinated coupling exists among the four systems in the Yunnan–Guizhou–Sichuan region is affected by many factors. Only eco-environmental pressure has a significant positive correlation with the degree of uncoordinated coupling, while the tourism scale, economic urbanization, eco-environmental response, and investment in technology have a significant negative correlation. These results provide a theoretical basis and practical references for strengthening the government’s macro-control and promoting collaborative regional development.

Green innovation and the digital economy are the new engine and driving force for Chinese high-quality development and will become the mainstream of China’s high-quality development. Therefore, it is of great significance to explore the interaction between the two for the formulation of economic development policies. This paper constructed an evaluation system of green science and technology innovation efficiency (GSTIE) and digital economy level (DEL) based on 30 provinces in China. Through the corrected coupling coordination degree (CCD) model, this paper measured the coupling coordination degree of green science and technology innovation efficiency and DEL and analyzed its provincial differences and spatial effects. By employing the fuzzy set Qualitative Comparative Analysis (fsQCA) method, this paper further explored the influencing factors configuration affecting the coupling coordination degree of GSTIE and DEL. The research results are as follows. Compared with the development of green science and technology innovation, the development of the digital economy was relatively backward. The coupling coordination degree between China’s provincial GSTIE and DEL showed an overall increasing trend year by year, and there was obvious spatial heterogeneity in which the eastern region was the highest, followed by the western and central regions. A single influencing factor does not constitute a necessary condition for a high coupling coordination degree. There were four paths that improve the coordinated development level between GSTIE and DEL: HC + RD + OP-jointly driven, RD + OP-dual driven, HC + GS-dual driven, and GS-oriented. Finally, based on the research conclusions, this paper proposed corresponding policy suggestions.