[Objective] The paper aimed to reflect the spatial pattern and temporal and spatial evolution characteristics, the differences between inter-regional tourism economy was measured from the quality aspect, which provide...[Objective] The paper aimed to reflect the spatial pattern and temporal and spatial evolution characteristics, the differences between inter-regional tourism economy was measured from the quality aspect, which provided a reference for the local governments in the future tourism development. [Method] Using the location entropy methods, three time periods side of tourism-related date of 2000, 2005, 2007 were selected, from the angle of the spatial pattern and the evolution of the differences within the different scales, the spatial and temporal evolution characteristics of the economic development level of Jiangsu were analysed. [Result] The results showed that from the aspect of spatial evolution pattern, as time goes on, the economic development of Jiangsu tourism has experienced morphological evolution of concentration- dispersion decrease-stability; when it comes to the development of the tourism economy, in recent years, the overall gap between the tourism economy in Jiangsu did not widen, the gap mainly led by the region one after another. According to their volatility, it will be divided into four categories: A Stable type (Wuxi, Xuzhou, Lianyungang and Taizhou), B Increasing type (Huai’an), C Fluctuations type (Nanjing, Changzhou, Suzhou and Yangzhou) and D Depression type (Nantong, Yancheng, Zhenjiang and Suqian). [Conclusion] Location entropy was quoted into tourism economic analysis, the method was simple and easy to understand, the result was accurate and convincing, which provided a reference for travel economic development and investment decision-making of Jiangsu.展开更多
Using datasets on high-tech industries in Beijing as empirical studies, this paper attempts to interpret spatial shift of high-tech manufacturing firms and to examine the main determinants that have had the greatest e...Using datasets on high-tech industries in Beijing as empirical studies, this paper attempts to interpret spatial shift of high-tech manufacturing firms and to examine the main determinants that have had the greatest effect on this spatial evolution. We aimed at merging these two aspects by using firm level databases in 1996 and 2010. To explain spatial change of the high-tech firms in Beijing, the Kernel density estimation method was used for hotspot analysis and detection by comparing their locations in 1996 and 2010, through which spatial features and their temporal changes could be approximately plotted. Furthermore, to provide quantitative results, Ripley′s K-function was used as an instrument to reveal spatial shift and the dispersion distance of high-tech manufacturing firms in Beijing. By employing a negative binominal regression model, we evaluated the main determinants that have significantly affected the spatial evolution of high-tech manufacturing firms and compared differential influence of these locational factors on overall high-tech firms and each sub-sectors. The empirical analysis shows that high-tech industries in Beijing, in general, have evident agglomeration characteristics, and that the hotspot has shifted from the central city to suburban areas. In combination with the Ripley index, this study concludes that high-tech firms are now more scattered in metropolitan areas of Beijing as compared with 1996. The results of regression model indicate that the firms′ locational decisions are significantly influenced by the spatial planning and regulation policies of the municipal government. In addition, market processes involving transportation accessibility and agglomeration economy have been found to be important in explaining the dynamics of locational variation of high-tech manufacturing firms in Beijing. Research into how markets and the government interact to determine the location of high-tech manufacturing production will be helpful for policymakers to enact effective policies toward a more efficient urban spatial structure.展开更多
文摘[Objective] The paper aimed to reflect the spatial pattern and temporal and spatial evolution characteristics, the differences between inter-regional tourism economy was measured from the quality aspect, which provided a reference for the local governments in the future tourism development. [Method] Using the location entropy methods, three time periods side of tourism-related date of 2000, 2005, 2007 were selected, from the angle of the spatial pattern and the evolution of the differences within the different scales, the spatial and temporal evolution characteristics of the economic development level of Jiangsu were analysed. [Result] The results showed that from the aspect of spatial evolution pattern, as time goes on, the economic development of Jiangsu tourism has experienced morphological evolution of concentration- dispersion decrease-stability; when it comes to the development of the tourism economy, in recent years, the overall gap between the tourism economy in Jiangsu did not widen, the gap mainly led by the region one after another. According to their volatility, it will be divided into four categories: A Stable type (Wuxi, Xuzhou, Lianyungang and Taizhou), B Increasing type (Huai’an), C Fluctuations type (Nanjing, Changzhou, Suzhou and Yangzhou) and D Depression type (Nantong, Yancheng, Zhenjiang and Suqian). [Conclusion] Location entropy was quoted into tourism economic analysis, the method was simple and easy to understand, the result was accurate and convincing, which provided a reference for travel economic development and investment decision-making of Jiangsu.
基金Under the auspices of National Natural Science Foundation of China(No.40971075)
文摘Using datasets on high-tech industries in Beijing as empirical studies, this paper attempts to interpret spatial shift of high-tech manufacturing firms and to examine the main determinants that have had the greatest effect on this spatial evolution. We aimed at merging these two aspects by using firm level databases in 1996 and 2010. To explain spatial change of the high-tech firms in Beijing, the Kernel density estimation method was used for hotspot analysis and detection by comparing their locations in 1996 and 2010, through which spatial features and their temporal changes could be approximately plotted. Furthermore, to provide quantitative results, Ripley′s K-function was used as an instrument to reveal spatial shift and the dispersion distance of high-tech manufacturing firms in Beijing. By employing a negative binominal regression model, we evaluated the main determinants that have significantly affected the spatial evolution of high-tech manufacturing firms and compared differential influence of these locational factors on overall high-tech firms and each sub-sectors. The empirical analysis shows that high-tech industries in Beijing, in general, have evident agglomeration characteristics, and that the hotspot has shifted from the central city to suburban areas. In combination with the Ripley index, this study concludes that high-tech firms are now more scattered in metropolitan areas of Beijing as compared with 1996. The results of regression model indicate that the firms′ locational decisions are significantly influenced by the spatial planning and regulation policies of the municipal government. In addition, market processes involving transportation accessibility and agglomeration economy have been found to be important in explaining the dynamics of locational variation of high-tech manufacturing firms in Beijing. Research into how markets and the government interact to determine the location of high-tech manufacturing production will be helpful for policymakers to enact effective policies toward a more efficient urban spatial structure.
