整合EVA的上市公司绩效评价模型研究  

Study on the Integrated EVA Performance Measurement of Listed Companies

作　　者：王平心[1] 陈琳[1] 李补喜[1] 

机构地区：[1]西安交通大学管理学院,陕西西安710049

出　　处：《数理统计与管理》2006年第2期186-194,共9页Journal of Applied Statistics and Management

基　　金：国家自然科学基金资助项目(70172010)

摘　　要：本文采用经济附加值(EVA)对传统绩效评价模式进行改进,建立了整合EVA的绩效评价(IEPM)模型。以我国沪深两市A股上市公司为研究对象,采用BP神经网络检验整合EVA的绩效评价模型相对于传统绩效评价模式的有效性,并运用统计方法对检验结果进行分析,发现整合EVA的绩效评价模型在评价上市公司的经营业绩时要明显优于传统绩效评价模式,而且其预测能力也显著强于传统绩效评价模式。这说明绩效评价模式在整合EVA之后可以更真实地反映公司的经营业绩,用它来评价和预测公司业绩将更为有效。This paper made a study on how to improve traditional performance measurements with Economic Value Added（EVA）. The integrated EVA performance measurement（IEPM） model was presented and its validity was tested. The difference between integrated EVA and traditional performanee measurements was empirically analyzed using BP neural network with the data from listed eompanies in China＇s A shares market. The results showed that integrated EVA performance measurement performed better than the traditional one in evaluating the firm＇s performance and its predictive ability was also proved to be superior to that of traditional one. So it is reasonable to use integrated EVA performance measurement to evaluate the firm＇s performance.

关 键 词：绩效评价 经济附加值 神经网络 

分 类 号：F272.5[经济管理—企业管理]