More and more studies on land transfer prices have been carried out over time. However, the influencing factors of the industrial land transfer price from the perspective of spatial attributes have rarely been explored. Selecting 25 towns as the basic research unit, based on industrial land transfer data, this paper analyzes the influencing factors of the price distribution of industrial land in Dingzhou City, a rural land system reform pilot in China, by using a geographically weighted regression (GWR) model. Eight evaluation factors were selected from five aspects: economy, population, topography, landform, and resource endowment. The results showed that: (1) Compared with the traditional ordinary least squares (OLS) model, the GWR model revealed the spatial differentiation characteristics of the industrial land transfer price in depth. (2) Factors that have a negative correlation with the industrial land transfer price include the proportion of cultivated land area and distance to the city. Factors that have a positive correlation with the industrial land transfer price include the population growth rate, economic growth rate, population density, and number of hospitals per unit area. (3) The results of GWR model analysis showed that the impact of different factors on the various towns of different models had significant spatial differentiation characteristics. This paper will provide a reference for the sustainable use of industrial land in developing countries.
In this era of industrial integration, the synergistic energy given collaborative agglomerations of the culture and tourism industries is crucial for fulfilling the potential of the underlying resources. The cultural grasp of artistic depths when fully supported can transform the cultural experiences for tourists and participants alike. In this study, the theory of spatial economics is used to analyze the spatial coupling degree of the Chinese culture and tourism industries from 2010 to 2019, based on the coupling coordination degree model. A spatial correlation test model was used to analyze the spatial–temporal evolution characteristics of industrial collaborative agglomeration, and a spatial vector autoregression model and impulse response function was used to analyze the economic effects of industrial collaborative agglomeration. The results show: (1) A coupling and coordination relationship exists between Chinese culture and the tourism industries. This collaborative bond is in the initial stage. (2) The overall spatial correlation between these industries can potentially provide significant and positive relationships among several components of the community, tourist, and cultural spectrum. The local spatial correlation of culture and tourism industries in Eastern China is ranked the highest; the central region is in the middle. The western region ranks the lowest. (3) The collaborative synergy of the cultural and tourism industries has a nonlinear economic effect on economic development, while the impacts of different industrial collaborative groups have the potential to strengthen the Chinese economy from a more technological perspective. This study provides theoretical support and recommendations for promoting the coordinated development of Chinese culture and tourism industries, which can also serve as an example for other regions seeking a stronger relationship between their culture, economic growth of the region as a whole, and the tourism industries.
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