Achieving customer satisfaction is an important goal of the high-quality development (HQD) of the hotel industry. The purpose of this study is to summarize the spatial distribution characteristics and influencing factors of the HQD of the hotel industry to better help improve hotel customer satisfaction and realize the HQD of the hotel industry. Taking Sanya as an example, this study applied kernel density analysis, grid analysis and a geographically weighted regression (GWR) model to reveal the distribution characteristics and influencing factors of the HQD of the hotel industry. The research results show that (1) from 2010 to 2020, both budget hotels and luxury hotels showed an increasing trend year by year and the degree of spatial agglomeration was continuously strengthened. (2) The overall HQD of the hotel industry in Sanya is at a medium to high level, but the development between different regions is unbalanced. The HQD level of the hotel industry in the eastern part of the city is better than that in the western region. (3) There are significant differences in the HQD level and its spatial distribution characteristics of budget hotels and luxury hotels. (4) Hardware facilities, price levels, market popularity and traffic conditions have a positive impact on the HQD level of the hotel industry, while hotel scale and business prosperity have a negative impact on the HQD level of the hotel industry. The public service level does not pass the significance test. The conclusions of this study can provide theoretical reference for the decision-making of HQD of urban tourism.
Family farms, considered the most desirable form of Chinese agriculture, play a pivotal role in promoting rural revitalization and agricultural modernization. The purpose of this study was to summarize the spatiotemporal evolution characteristics and influencing factors of family farms to better promote the development of modern agriculture. Using provincial demonstration family farms in the urban agglomeration in the middle reaches of the Yangtze River (MYR-UA) as the research object, this study applied the nearest neighbor index, kernel density analysis, multiscale spatial clustering analysis (Ripley’s K-function), and geographically weighted regression (GWR) model to reveal the spatiotemporal dynamic evolution and influencing factors of family farms. The results indicate that: 1) from 2013 to 2021, family farms exhibited annual increases, and their development stages could be divided into rapid, stable, and slow growth periods. 2) The spatial agglomeration pattern of family farms was significant, and the intercepted points at different time periods show the distribution characteristics of the entire dispersion and local concentration. The spatial evolution characteristics of different types of family farms are nearly consistent with those of the overall family farms. 3) The overall family farms and various types of family farms show a scale effect, which first strengthens and then weakens with the change in geographical distance. 4) The spatial pattern of family farms in MYR-UA is affected by both natural and social factors, of which, social factors had the greatest influence. Finally, based on the findings of the study, policy recommendations for promoting the high-quality development of family farms are proposed.
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