DocumentCode :
478126
Title :
Improvement of EVA on Traditional Performance Measurement: An Application of Neural Network
Author :
Chen, Lin ; Qiao, Zhilin
Author_Institution :
Northwestern Polytech. Univ., Xi´´an
Volume :
2
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
424
Lastpage :
428
Abstract :
Economic value added (EVA) is a good method to measure the company´s true value. This paper discussed on how to improve traditional performance measurement using EVA with neural network. It presented the integrated EVA performance measurement (IEPM) model and analyzed its superiority empirically with BP neural network. All the data came from China´s listed companies. The final results showed that both the measurement ability and prediction ability of IEPM model were superior to those of traditional performance measurement. It suggests that introducing EVA to performance measurement well reflects the company´s real economic profit and neural network model will be well applied to economic area, especially to the company´s performance measurement.
Keywords :
backpropagation; economics; neural nets; BP neural network; economic profit; economic value added; integrated EVA performance measurement model; Computer networks; Costs; Economic forecasting; Environmental economics; Linear regression; Management training; Measurement; Neural networks; Performance analysis; Technological innovation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
Type :
conf
DOI :
10.1109/ICNC.2008.52
Filename :
4667030
Link To Document :
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