摘要
[目的/意义]为满足决策者对企业专利质量评价过程中希望降低外部因素影响,凸显稀缺性指标导向作用的需求,对基于自适应层次分析法的企业专利质量评价方法进行深入研究。[方法/过程]该方法根据企业专利情报数据的分布特征,对评价指标的权重进行动态调整,降低数据分布集中的指标权重,提升数据分布离散的指标权重。[结果/结论]实现弱化外部因素影响,凸显稀缺性指标导向作用的目的,同时使定量评价更为科学合理。以北京市海淀区6家高新技术企业专利情报数据为例,检验评价方法的有效性。
[ Purpose/significance] In order to meet the need of decision makers in enterprises to reduce the impact of external factors during the patent quality evaluation process and to highlight the guiding role of the scarcity index, anin -depth study is presented by this article aboutthe patent quality evaluation methodology based on the analysis of adaptive enterprise AHP. [ Method/process] According to the distribution characteristics of enterprise patent intelligence data, the weight of evaluation indexes was adjusted dynamically by reducing the weight of the index of data concentrated distri- bution and increasing the weight of the data discrete distribution. [ Result/conclusion ] This study takes patent intelli- gence data of six high-tech enterprises in Haidian District of Beijing as examples to test the effectiveness of the adaptive analytic hierarchy process in order to highlight the scarcity index＇ s guiding role, weaken external factors and makethe quantitative evaluation more scientific and reasonable,
出处
《图书情报工作》
CSSCI
北大核心
2016年第7期110-115,共6页
Library and Information Service
