长江经济带科技成果转化效率测度及空间格局演化研究

Research on the Transformation Efficiency Measurement and Spatial Pattern Evolution of Scientific and Technological Achievements in the Yangtze River Economic Belt

科学评价科技成果转化效率是带动区域经济效益提高的重要保障.应用DEA模型及Malmquist指数分解法,基于2009~2018年长江经济带科技成果转化面板数据,测算了11个省、市及三大地区(上、中、下游)科技成果转化过程中的技术效率、技术进步及全要素生产率增长情况,并运用探索性空间数据分析方法探究了科技成果转化效率的空间聚集特征.研究表明:2009年后,长江经济带科技成果转化效率整体呈上升趋势;从上中下游三大地区来看,中游地区科技成果转化效率增幅高于上游、下游地区,中游地区科技成果转化效率增幅最低,长江经济带科技成果转化效率的主要限制因素为纯技术效率不高;长江经济带科技成果转化效率以异质性发展趋势为主,呈现空间负相关性的省区数量逐渐增多;而表现为空间正相关性的省区数量随着时间推移逐渐减少.

Scientific evaluation of the transformation efficiency of scientific and technological achievements is an important guarantee to promote the improvement of regional economic benefits. Using DEA model and Malmquist index decomposition method, based on the panel data of scientific and technological achievements transformation in the Yangtze River economic belt from 2009 to 2018, in this paper, the technological efficiency, technological progress and total factor production rate growth in the process of scientific and technological achievements transformation in 11 provinces, cities and three regions(upper, middle and lower reaches) are estimated. Using exploratory spatial data analysis method, the spatial aggregation characteristics of the transformation efficiency of scientific and technological achievements are explored. The results show that: after 2009, the transformation efficiency of scientific and technological achievements in the Yangtze River economic belt is on the rise as a whole;from the perspective of the upper, middle and lower reaches, the growth rate of transformation efficiency of scientific and technological achievements in the middle reaches is higher than that in the upper and lower reaches, and the growth rate of transformation efficiency of scientific and technological achievements in the middle reaches is the lowest With the transformation efficiency of scientific and technological achievements mainly in the trend of heterogeneity, the number of provinces with negative spatial correlation gradually increases, while the number of provinces with positive spatial correlation gradually decreases over time.