Using rough set and worst practice DEA in business failure prediction

Authors:
Jia-Jane Shuai;Han-Lin Li
Affiliations:
,Department of Information Management, Ming-Hsin University of Science and Technology, Hsin-Feng, Hsinchu, Taiwan;Institute of Information Management, National Chiao-Tung University, Hsinchu, Taiwan
Venue:
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Year:
2005

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Abstract

This paper proposes a hybrid approach that predicts the failure of firms based on the past business data, combining rough set approach and worst practice data envelopment analysis (DEA). The worst practice DEA can identify worst performers (in quantitative financial data) by placing them on the frontier while the rules developed by rough set uses non-financial information to predict the characteristics of failed firms. Both DEA and rough set are commonly used in practice. Both have limitations. The hybrid model Rough DEA takes the best of both models, by avoiding the pitfalls of each. For the experiment, the financial data of 396 Taiwan firms during the period 2002-2003 were selected. The results show that the hybrid approach is a promising alternative to the conventional methods for failure prediction.