国务院创新政策量化评价——基于PMC指数模型

发布时间：2018-06-22 14:05

本文选题：创新政策 + PMC　；参考：《科技进步与对策》2017年17期

【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。
[Abstract]:Taking 12 innovation policies of the State Council from 2014-2016 as the research object, based on the research results of scholars at home and abroad and combining the characteristics of innovation policies, the PMC index model is constructed, which includes 9 first-class variables and 37 second-level variables. Through text mining, 12 innovation policies of the State Council are deeply excavated and quantitatively evaluated, and the final results are intuitively reflected by the PMC surface. It is found that the 12 policies to be evaluated are all excellent grades. In order to facilitate the analysis and improvement, the traditional policy rating is divided into two levels: superior and superior. Through the multi-input-output table and the policy PMC index summary table, the two-level variable score is traced back and determined, and the weak link of the policy is found, which has certain reference significance for the new policy formulation or the original policy revision.
【作者单位】：北京工业大学经济与管理学院;
【基金】：国家自然科学基金项目(70972115) 北京市教委重点项目(SZ20071005002) 国家部委项目(3A011212200901;40011212201502;40011212201501;40011212201408;40011212201407;40011212201404)
【分类号】：F124.3

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