Skip to main content
SpringerLink
Log in

Multiple Criteria Linear Programming Data Mining Approach: An Application for Bankruptcy Prediction

  • Conference paper
Data Mining and Knowledge Management (CASDMKM 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3327))

Abstract

Data mining is widely used in today’s dynamic business environment as a manager’s decision making tool, however, not many applications have been used in accounting areas where accountants deal with large amounts of operational as well as financial data. The purpose of this research is to propose a multiple criteria linear programming (MCLP) approach to data mining for bankruptcy prediction. A multiple criteria linear programming data mining approach has recently been applied to credit card portfolio management. This approach has proven to be robust and powerful even for a large sample size using a huge financial database. The results of the MCLP approach in a bankruptcy prediction study are promising as this approach performs better than traditional multiple discriminant analysis or logit analysis using financial data. Similar approaches can be applied to other accounting areas such as fraud detection, detection of tax evasion, and an audit-planning tool for financially distressed firms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Altman, E.: Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance 23(3), 589–609 (1968)

    Article  Google Scholar 

  2. Altman, E., Haldeman, R.G., Narayanan, P.: ZETA Analysis: A New Model to Identify Bankruptcy Risk of Corporations. Journal of Banking and Finance 1(1), 29–54 (1977)

    Article  Google Scholar 

  3. Barniv, R., Agarwal, A., Leach, R.: Predicting Bankruptcy Resolution. Journal of Business Finance & Accounting 29(3/4), 497–520 (2002)

    Article  Google Scholar 

  4. Beaver, W.: Financial Rations as Predictors of Failure. Empirical Research in Accounting, Selected Studies. Supplement to the Journal of Accounting Research, 71–111 (1966)

    Google Scholar 

  5. Begley, J., Ming, J., Watts, S.: Bankruptcy Classification Errors in the 1980s: An Empirical Analysis of Altman’s and Ohlson’s Models. Review of Accounting Studies 1, 267–284 (1996)

    Article  Google Scholar 

  6. Bose, I., Mahapatra, R.K.: Business Data Mining—A Machine Learning Perspective. Information and Management 39, 211–225 (2001)

    Article  Google Scholar 

  7. Chan, C., Lewis, B.: A Basic Primer on Data Mining. Information Systems Management, 56–60 (Fall 2002)

    Google Scholar 

  8. Freed, N., Glover, F.: Evaluating Alternative Linear Programming Models to Solve the Two-Group Discriminant Problem. Decision Sciences 17, 151–162 (1986)

    Article  Google Scholar 

  9. Grice, J.S., Dugan, M.T.: The Limitations of Bankruptcy Prediction Models: Some Cautions for the Researcher. Review of Quantitative Finance and Accounting 17, 151–166 (2001)

    Article  Google Scholar 

  10. Grice, J.S., Ingram, R.W.: Tests of Generalizability of Altman’s Bankruptcy Prediction Model. Journal of Business Research 54, 53–61 (2001)

    Article  Google Scholar 

  11. Gupta, Y.P., Rao, R.P., Baggi, P.K.: Linear Goal Programming as an Alternative to Multivariate Discriminant Analysis: A Not. Journal of Business, Finance, and Accounting 17(4), 593–598 (1990)

    Article  Google Scholar 

  12. Hotchkiss, E.S.: Post-Bankruptcy Performance and Management Turnover. Journal of Finance 50(1), 67–84 (1995)

    Article  Google Scholar 

  13. Jones, F.L.: Current Techniques in Bankruptcy Prediction. Journal of Accounting Literature 6, 131–164 (1987)

    Google Scholar 

  14. Koehler, G.J., Erenguc, S.S.: Minimizing Misclassifications in Linear Discriminant Analysis. Decision Sciences 21, 63–85 (1990)

    Article  Google Scholar 

  15. Kou, G., Liu, X., Peng, Y., Shi, Y., Wise, M., Xu, W.: Multiple Criteria Linear Programming Approach to Data Mining: Models, Algorithm Designs and Software Development. Optimization Methods and Software 18, 453–473 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  16. Kou, G., Shi, Y.: Linux based Multiple Linear Programming Classification Program: version 1.0. College of Information Science and Technology, University of Nebraska-Omaha, Omaha, NE 68182, USA (2002)

    Google Scholar 

  17. McKee, T.E.: Developing a Bankruptcy Prediction Model via Rough Sets Theory. International Journal of Intelligent Systems in Accounting, Finance & Management 9, 159–173 (2000)

    Google Scholar 

  18. Mossman, C., Bell, G., Swartz, L.M., Turtle, H.: An Empirical Comparison of Bankruptcy Models. Financial Review 33, 35–53 (1998)

    Article  Google Scholar 

  19. Nanda, S., Pendharkar, P.: Linear Models for Minimizing Misclassification Costs in Bankruptcy Prediction. International Journal of Intelligent Systems in Accounting, Finance & Management 10, 155–168 (2001)

    Google Scholar 

  20. Ohlson, J.: Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research 18(1), 109–131 (1980)

    Article  MathSciNet  Google Scholar 

  21. Park, C.S., Han, I.: A Case-Based Reasoning with the Feature Weights Derived by Analytic Hierarchy Process for Bankruptcy Prediction. Expert Systems with Applications 23(3), 255–264 (2002)

    Article  Google Scholar 

  22. Platt, D.H., Platt, M.B.: Development of a Class of Stable Predictive Variables: The Case of Bankruptcy Prediction. Journal of Business Finance & Accounting, 31–51 (Spring 1990)

    Google Scholar 

  23. Platt, D.H., Platt, M.B.: A Re-Examination of the Effectiveness of the Bankruptcy Process. Journal of Business Finance & Accounting 29(9/10), 1209–1237 (Spring 2002)

    Article  Google Scholar 

  24. Pompe, P.P.M., Feelders, J.: Using Machine Learning, Neural Networks, and Statistics to Predict Corporate Bankruptcy. Microcomputers in Civil Engineering 12, 267–276 (1997)

    Article  Google Scholar 

  25. SAS/OR User’s Guide, SAS Institute Inc., Cary, NC (1990)

    Google Scholar 

  26. Shi, Y.: Multiple Criteria multiple Constraint-Levels Linear Programming: Concepts, Techniques and Applications. World Scientific Publishing, River Edge (2001)

    Book  Google Scholar 

  27. Shi, Y., Peng, Y., Xu, W., Tang, X.: Data Mining via Multiple Criteria Linear Programming: Applications in Credit Card Portfolio Management. International Journal of Information Technology & Decision Making 1(1), 131–151 (2002)

    Article  Google Scholar 

  28. Shi, Y., Wise, M., Luo, M., Lin, Y.: Data Mining in Credit Card Portfolio Management: A Multiple Criteria Decision Making Approach. In: Koksakan, M., Zionts, S. (eds.) Multiple Criteria Decision Making in the New Millennium, pp. 427–436 (2001)

    Google Scholar 

  29. Shi, Y., Yu, P.L.: Goal Setting and Compromise Solutions. In: Karpak, B., Zionts, S. (eds.) Multiple Criteria Decision Making and Risk Analysis Using Microcomputers, pp. 165–204. Springer, Berlin (1989)

    Chapter  Google Scholar 

  30. Shin, K.S., Lee, Y.J.: A Genetic Algorithm Application in Bankruptcy Prediction Modeling. Expert Systems with Applications 23(3), 321–328 (2002)

    Article  Google Scholar 

  31. Sung, T.K., Chang, N., Lee, G.: Dynamics of Modeling in Data Mining: Interpretive Approach to Bankruptcy Prediction. Journal of Management Information Systems 16(1), 63–85 (1999)

    Article  Google Scholar 

  32. Wilson, R.L., Sharda, R.: Bankruptcy Prediction using Neural Networks. Decision Support Systems 11, 545–557 (1994)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Accounting, College of Business Administration, University of Nebraska at Omaha, Omaha, Nebraska, 68182, USA

    Wikil Kwak

  2. College of Information Science and Technology, University of Nebraska at Omaha, Omaha, Nebraska, 68182, USA

    Yong Shi

  3. Accounting and Information Systems, The University of Akron, College of Business Administration, 259 South Broadway, Akron, OH, 44325-4802, USA

    John J. Cheh

  4. Department of Management and Information System, Korea Advanced Institute of Science and Technology, Seoul, Korea

    Heeseok Lee

Authors
  1. Wikil Kwak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John J. Cheh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Heeseok Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100080, China; College of Information Science and Technology, University of Nebraska at Omaha, 68182, Omaha, NE, USA

    Yong Shi

  2. Institute of Policy & Management, Chinese Academy of Sciences, P.O. Box, 100080, Beijing, P.R. China

    Weixuan Xu

  3. College of Information Science and Technology, University of Nebraska at Omaha, 68182, NE, USA

    Zhengxin Chen

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kwak, W., Shi, Y., Cheh, J.J., Lee, H. (2004). Multiple Criteria Linear Programming Data Mining Approach: An Application for Bankruptcy Prediction. In: Shi, Y., Xu, W., Chen, Z. (eds) Data Mining and Knowledge Management. CASDMKM 2004. Lecture Notes in Computer Science(), vol 3327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30537-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30537-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23987-1

  • Online ISBN: 978-3-540-30537-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation