中国R&D机构科技投入与产出变动趋势分析  

An Analysis of the Trend of Science and Technology Input and Output Fluctuation in China's R&D Institutions

作　　者：陈祺琪[1,2] 

机构地区：[1]中原工学院,郑州450007 [2]华中农业大学湖北农村发展研究中心,武汉430070

出　　处：《中原工学院学报》2017年第5期67-75,共9页Journal of Zhongyuan University of Technology

基　　金：国家自然科学基金重点项目(71333006);国家社会科学基金项目(15BGL207)

摘　　要：基于2005-2014年我国R&D机构数据,对科技产出与投入指标进行了灰关联分析,并对2015-2020年科技活动指标进行了趋势预测。结果表明:2005-2014年我国R&D机构科技活动发展态势良好,除R&D机构数指标外,其余科技活动指标均呈明显增长趋势;2015-2020年我国R&D机构科技发展迅速,科技活动指标变动趋势合理,且投入产出指标关系更加清晰。结合我国R&D机构科技活动发展现状,必须从R&D机构资金投入、人事考评制度、绩效激励机制等方面进行必要改革,提高我国R&D机构科技活动资源利用效率。The article made a Grey correlation analysis on the S&T inputs and outputs of R&D institutions in china from 2005 to 2014.The information renewal GM(1,1)model is selected to do the trend prediction and Grey correlation analysis on the S&T inputs and outputs of R&D institutions in china from 2015 to2020 based on compared the conventional GM(1,1)model with the information renewal GM(1,1)model.Three main results are gotten,firstly,the S&T development of R&D institutions is in the rapid growth period in china from 2005 to 2014,and many of R&D indexes have a significant growth trend except the index of institutions numbers.Secondly,the S&T development of R&D institutions has a reasonable organization and obvious development during 2015 to 2020;what is more,there is a more clear relationship between the output indexes and input indexes of R&D institutions.Thirdly,There are three index(projects of R&D,scientific papers issued and publications on S&T)belonged to the human power-oriented index;other two outputs index(number of patents applications accepted and granted)are the capital-oriented index.Based on the conclusion and given more consideration to the development status of R&D institutions in china,some suggestion about how to improve the utilization efficiency of S&T resources from the perceptive of capital investment,personnel evaluation system and performance incentive mechanism of R&D institutions are given.

关 键 词：R&D机构 产出与投入 灰关联分析 新陈代谢GM(1 1)模型 趋势预测 

分 类 号：F124[经济管理—世界经济]