作　　者： (张永安）; (郄海拓）;

机构地区： 北京工业大学经济与管理学院,北京100124

出　　处： 《科技进步与对策》 2017年第17期127-136,共10页

摘　　要： 以2014-2016年国务院12项创新政策为研究对象,基于国内外学者研究成果并结合创新政策特点,构建PMC指数模型,包含9个一级变量及37个二级变量。通过文本挖掘方式对12项国务院创新政策进行深入挖掘和量化评价,并结合PMC曲面将最终结果直观反映出来,发现待评价的12项政策均为优秀级别。为便于分析和改进,对传统政策评分等级进行二次划分,将优秀级别分为优上和优下两个级别,通过多投入产出表和各项政策PMC指数汇总表对两级变量得分进行两级追溯和确定,找到政策薄弱环节,对新政策制定或原有政策修改具有一定借鉴意义。 This article is based on the 12 innovation policies of the state council during 2014 to 2016. Based on the researches of domestic and foreign scholars and combined the results and the characteristics of innovation policies, we put up with the PMC index model with 9 primary variables and 37 secondary variables. The text mining methodology helps us to dig deeper and finish quantitative evaluation of 12 innovation policies of the state council. The final result could be seen clearly through the PMC surface. The 12 policies are good level, so we rate second division of the evaluation ranking by separating the good level into upper good level and lower good. The results of every primary and secondary variables could be traced and confirmed in the mult-input-output tables and PMC index summary table of various policies, which helped to find the weakness of the policies and provide specific and feasible guidance to policy formulation and modification.

关 键 词： 创新政策 政策评价 评价模型 指数模型