低代码平台(Low-Code Development Platform,LCDP)是近些年发展起来,敏捷响应企业业务需求迭代发展和支撑企业数字化转型的一项新技术。友好的可视化环境,图形化拖曳式配置操作界面,开发工作的自助化、敏捷化、扁平化,满足了多团队跨地...低代码平台(Low-Code Development Platform,LCDP)是近些年发展起来,敏捷响应企业业务需求迭代发展和支撑企业数字化转型的一项新技术。友好的可视化环境,图形化拖曳式配置操作界面,开发工作的自助化、敏捷化、扁平化,满足了多团队跨地域协作和多种开发形式。越来越多的企业青睐这种无代码或低代码的信息系统开发,既能够敏捷响应业务需求、快速搭建应用系统,又能降低企业开发成本和运维成本。通过低代码平台设计实现基于领域模型驱动的井筒工艺数据采集平台,构建新一代支持云端部署、PC端、移动端等多终端自适应屏幕的应用,弹性伸缩资源调配,提供更稳定、高效的企业级数据采集应用平台,解决数据多系统分散采集、效率低下等问题,为企业数字化转型提供数据要素的支持。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 m展开更多
文摘低代码平台(Low-Code Development Platform,LCDP)是近些年发展起来,敏捷响应企业业务需求迭代发展和支撑企业数字化转型的一项新技术。友好的可视化环境,图形化拖曳式配置操作界面,开发工作的自助化、敏捷化、扁平化,满足了多团队跨地域协作和多种开发形式。越来越多的企业青睐这种无代码或低代码的信息系统开发,既能够敏捷响应业务需求、快速搭建应用系统,又能降低企业开发成本和运维成本。通过低代码平台设计实现基于领域模型驱动的井筒工艺数据采集平台,构建新一代支持云端部署、PC端、移动端等多终端自适应屏幕的应用,弹性伸缩资源调配,提供更稳定、高效的企业级数据采集应用平台,解决数据多系统分散采集、效率低下等问题,为企业数字化转型提供数据要素的支持。
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 m
