Journal Published Online: 25 March 2013
Volume 41, Issue 3

Corporate Performance Forecasting Using Hybrid Rough Set Theory, Neural Networks, and DEA



This paper proposed the hybrid model using rough set theory (RST), neural networks (NN), and data envelopment analysis (DEA) to predict the corporate performance directly. First, to evaluate corporate performance, the DEA was employed. Second, integrated RST with BPN techniques, which is one of the popular used models of NN, named RST+BPN, was used to build the corporate performance-prediction model and the corporate governance variables are used as predictive variables. This hybrid method enabled us to evaluate an individual firm and provided performance information without comparing it with other companies. The experimental result showed that the proposed model outperforms the NN model with nonextracted predictive variables and provides a promising alternative in corporate performance prediction.

Author Information

Lin, Chiun-Sin
Dept. of Business and Entrepreneurial Management, Kainan Univ., Luzhu Shiang, Taoyuan, TW
Lin, Tzu-Yu
Dept. of Management Science, National Chiao Tung Univ., Hsinchu City, TW
Chiu, Sheng-Hsiung
Dept. of Management Science, National Chiao Tung Univ., Hsinchu City, TW
Pages: 7
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Stock #: JTE20120027
ISSN: 0090-3973
DOI: 10.1520/JTE20120027