科技成果转化绩效评价指标体系的比较分析

Comparative Analysis Study on Evaluation Index System of Transformation Performance of Scientific and Technological Achievement

首先确定与科技成果转化绩效评价高度相关的56篇影响力大的样本文献,然后对这些文献采用文献计量法和比较分析法从科技成果转化绩效评价指标体系的设计原则、层次设置、底层评价指标的个数、不同被评价对象的评价指标选取、评价指标权重确定方法分别进行对比分析。结果表明,在设计科技成果转化绩效评价指标体系时遵循最多的3项原则分别是可操作性、科学性和系统性;2层的评价指标体系采用的文献篇数最高(占比64.29%);底层评价指标个数为13~17的文献数量之和为17,相对最多(占比30.36%);科技成果转化绩效评价方面在微观、中观、宏观3个层面上存在着失衡现象,微观层面、中观层面、宏观层面的占比分别为62.5%、33.93%、3.57%;主观赋权法和客观赋权法的使用频次接近,使用的具体赋权法的占比由高到低排序分别是层次分析法(占比33.93%)、数据包络分析法(占比17.86%)、专家调查法(占比10.7%)、主成分分析法(占比8.92%)、熵值法(占比8.92%)。

First, this paper determines 56 influential sample documents that are highly correlated with performance evaluation of sci- entific and technological achievements transformation. And then by using the methods of literature measurement and comparative analysis, these documents are analyzed separately from design principles, level setting, the number of the last level index, evaluation selection of different evaluated object, evaluation of index weight detemaination methods of scientific and technological achievements transformation per- formance evaluation index system. The results show that operational, scientific and systematic are most followed when designing scientific and technological achievements transformation performance evaluation index system. Evaluation index system of level 2 uses the maximum number of articles in the literature and accounts for 64.29 percent. The number of documents with the number of last level index of 13 - 17 is relative maximum （accounting for 30.36 percent）. Performance evaluation of scientific and technological achievements transformation exists imbalance at the micro level, middle level and macro level. And micro level, middle level and macro level are accounting for re- spectively 62.5 percent, 33.93 percent and 3.57 percent. The frequency use of subjective and objective weighting method is near and the accounting descending sort which is using specific weighting method are respectively analytic hierarchy process （accounting for 33.93 per- cent）, data envelopment analysis （accounting for 17.86 percent）, expert investigation （accounting for 10.7 percent）, principal compo- nent analysis （accounting for 8.92 percent） and entropy method （accounting for 8.92 percent）.