Journal of the Korean Operations Research and Management Science Society (한국경영과학회지)

The Korean Operations Research and Management Science Society (한국경영과학회)
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Financial Performance Evaluation using Self-Organizing Maps: The Case of Korean Listed Companies

자기조직화 지도를 이용한 한국 기업의 재무성과 평가

  • Published : 2001.09.01
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Abstract

The amount of financial information in sophisticated large data bases is huge and makes interfirm performance comparisons very difficult or at least very time consuming. The purpose of this paper is to investigate whether neural networks in the form of self-organizing maps (SOM) can be successfully employed to manage the complexity for competitive financial benchmarking. SOM is known to be very effective to visualize results by projecting multi-dimensional financial data into two-dimensional output space. Using the SOM, we overcome the problems of finding an appropriate underlying distribution and the functional form of data when structuring and analyzing a large data base, and show an efficient procedure of competitive financial benchmarking through clustering firms on two-dimensional visual space according to their respective financial competitiveness. For the empirical purpose, we analyze the data base of annual reports of 100 Korean listed companies over the years 1998, 1999, and 2000.

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References

  1. TUCS Technical Report no.8 Managing Complexity in Large Data Bases Using Self-Organizing Maps Back, B.;M. Irjala;K. Sere;H. Vanharanta
  2. Accounting, Management, and Information Technologies v.8 no.4 Managing Complexity in Large Databases Using Self-Organizing Maps Back, B.;K. Sere;H. Vanharanta
  3. Omega, International Journal of Management Science v.23 no.3 The Comparative Ability of Self-organizing Neural Networks to Define Cluster Structure Chen, S.K.;P. Mangiameli;D. West
  4. Nenet version 1.1 Elomaa, J.;J. Halme;P. Hassinen;P. Hodju;J. Ronkko
  5. Biological Cybernetics v.67 no.1 Self-organizing maps: Ordering, convergence properties and energy functions Erwin, E.;K. Obermayer;K. Schulten
  6. Omega, International Journal of Management Science v.22 Towards a General Non-parametric Model of Corporate Performance Fernandez Castro, A.;P. Smith
  7. Training v.27 Benchmarking: Measuring yourself against the best Geber, B.
  8. Strategic Management Journal v.17 The Application of Cluster Analysis in Strategic Management Research: an Analysis and Critique Ketchen, D.;C. Shook
  9. Neurocomputing v.21 Predicting bankruptcies with the self-organizing map Kiviluoto, K.
  10. Self-Organization and Associative Memory Kohonen, T.
  11. Self-Organizing Maps Kohonen, T.
  12. Neurocomputing v.21 The Self-Organizing Map Kohonen, T.
  13. SOM_PAK: The Self-Organizing Map Program Package Kohonen, T.;J. Hynninen;J. Kangas;J. Laaksonen
  14. Neural Networks in the Capital Markets Self Organizing Neural Networks: The Financial State of Spanish Companies Martin-del-Brio, B.;C. Serrano-Cinca;Apostolos-Paul Refenes(ed.)
  15. Omega, International Journal of Management Science v.19 no.4 Multidimensional Scaling Applied to Corporate Failure Mar-Molinero, C.;M. Ezzamel
  16. Information and Management v.32 The Acceptance of Visual Information in Management Meyer, J.A.
  17. Parallel Distributed Processing Rumelhart, D.E.;J.L. McClelland
  18. Applied Multivariate Statistical Analysis Johnson, R.A.;D.W. Wichen
  19. British Accounting Review v.27 Accounting Identities and the Distribution of Ratios Trigueiros, D.
  20. Acta Academiae Aboensis, Ser. B. v.55 no.1 Hyperknowledge and Continuous Strategy in Executive Support Systems Vanharanta, H.
  21. Omega, International Journal of Management Science v.22 Visualising Interfirm Comparison Vermuelen, E.M.;J. Spronk;D. Van Der Wijst