摘要
随着经济高质量发展的持续深入,科技创新已然成为区域竞争力的决定性因素,亟需挖掘山东省科技创新的发展动能进而打造科技创新的经济新增长极,为资源优化配置提供有效支持。以2012—2020年山东省各地级市面板数据为研究样本,基于数据包络分析模型对山东省科技创新效率进行测度,并通过地理分布图示、分解分析与集聚分析研究了科技创新效率的时空演变、区域差异以及对科技创新效率产生影响的关键性因素。研究结果表明,山东省科技创新整体效能不断提升,在研究期间内整体趋势向好;山东省内各个地区之间存在较大的空间格局差异,区域科技创新效率差异是造成整体差异的重要因素;分解分析的结果表明,技术进步对全省科技创新效率的上升起到重要的推动作用,然而技术效率制约了科技创新效率的提升。研究可为山东省进一步发展科技创新效率提供重要启示。
This paper takes the panel data of all prefecture-level cities in Shandong Province from 2012 to 2020 as research samples,conducts static measurement analysis and dynamic measurement analysis of Shandong S&T innovation efficiency based on the data envelopment analysis model,and studies the spatial and temporal evolution of Shandong S&T innovation efficiency since the 18th National Congress,regional differences and key factors that have an impact on the S&T innovation efficiency by means of geographic distribution illustration,agglomeration analysis and decomposition analysis.The results of the study show that the overall efficiency of S&T innovation in Shandong Province has been improving,and the overall trend has been positive during the study period.There are large spatial patterns of variability among regions in Shandong Province,and regional differences are an important factor contributing to the overall differences.The results of the decomposition analysis show that technological progress has played an important role in promoting the rise of the S&T innovation efficiency in the province,but the technological efficiency has constrained the improvement of the S&T innovation efficiency,which also provides an opportunity for the further development of S&T innovation in Shandong Province.Therefore,it is an important insight for the further development of STI efficiency in Shandong Province.
作者
刘青
张晓南
李曼
LIU Qing;ZHANG Xiaonan;LI Man(Shandong Provincial Institute of Innovation and Development,Jinan 250102,China;Shandong Provincial Soil Pollution Prevention and Control Center,Jinan 250012,China)
出处
《甘肃科学学报》
2024年第4期116-125,共10页
Journal of Gansu Sciences
关键词
科技创新效率
数据包络分析
时空演变
分解分析
集聚分析
Technology and innovation efficiency
Data envelopment analysis
Spatial and temporal evolution
Agglomeration analysis
Decomposition analysis