基于熵值法修正PLS权重的学术期刊综合评价  

Academic Journal Comprehensive Evaluation: Improving PLS Weight Based on the Entropy Value Method

作　　者：熊国经[1] 熊玲玲[1] 陈小山[1] 

机构地区：[1]南昌大学经济管理学院,南昌330031

出　　处：《情报杂志》2017年第6期192-196,201,共6页Journal of Intelligence

基　　金：国家社会科学基金项目"非参数估计的影响因素优化匹配方法与应用研究"(编号:14BTJ016)研究成果之一;创新专项资金:校级项目"基于PLS结构方程模型的学术期刊评价实证研究"(编号:cx2016132)研究成果之一

摘　　要：[目的/意义]期刊评价指标间多重共线性与指标权重不确定性是学术期刊评价面临的两大难题。基于此,提出一种新的复合评价模型。[方法/过程]首先以图情类期刊为例构建PLS路径模型得到各指标外部权重,其次通过熵值法的差异系数对PLS路径模型的外部权重进行修正,最终确定各指标的权重、构造加权规范矩阵,最后用加权TOPSIS法比较样本期刊与最优解的相对贴近度并进行排序分析。[结果/结论]通过实证研究表明,该方法有效消除了指标间的多重共线性,合理为指标赋权,且对期刊的评价结果是有效的、合理的。[ Purpose/Significance ] The multicollinearity and the index weight uncertainty of the periodical evaluation index are the two major problems of the evaluation of academic journals. A new composite evaluation model is proposed. [ Method/Process] The first step is to get the external weight of each index via constructing the PLS path model based on the LIS journals, the second step is to modify the ex- ternal weight of the PLS path model by the coefficient of difference of the entropy method, and determine the weight of each index and construct the weighting norm matrix. Finally, the relative TOPSIS method is used to compare the sample journals with the optimal solution. [ Result/Conclusion] The empirical results show that this method can effectively eliminate the multicollinearity between the indexes, the indicator weight allocation is reasonable, and the evaluation results of the journals are effective and reasonable.

关 键 词：期刊评价 多重共线性 复合评价模型 PLS路径模型 熵值法 加权TOPSIS 

分 类 号：G203[文化科学—传播学]