Clustering and Visualization of Bankruptcy Patterns Using the Self-Organizing Maps

Andrzej Burda; Krzysztof Pancerz

doi:10.56583/br.1045

Published : 2015-01-09

Vol. 12 No. 3 (2014)

Clustering and Visualization of Bankruptcy Patterns Using the Self-Organizing Maps

Andrzej Burda

Krzysztof Pancerz

DOI: https://doi.org/10.56583/br.1045

Abstract

Pattern recognition of bankrupt or non-bankrupt enterprises may not only extend or confirm the knowledge in economics, but also deliver to experts, from the standpoint of the decision support, a view of the economic and financial situation of the audited enterprise. Therefore, it may be an effective tool for early warning of the bankruptcy risk of the enterprise. Such a tool is especially important for small and medium enterprises (SMEs) in the underdeveloped regions. The research described in the paper is intended for generation and visualization of the state of SMEs in the Podkarpacie region on the basis of information included in financial reports. A self-organizing map (SOM), often called the Kohonen net, has been used in the unsupervised modelling mode. Results of research show a high potential of the method to the stated objectives and the simplicity of the representation of knowledge transferred to entrepreneurs and financial analysts.

Keywords:

Self-Organizing Map, clustering, visualization, small and medium enterprises, bankruptcy

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Burda, A., & Pancerz, K. (2015). Clustering and Visualization of Bankruptcy Patterns Using the Self-Organizing Maps. Regional Barometer. Analyses & Prognoses, 12(3), 133–138. https://doi.org/10.56583/br.1045

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Andrzej Burda

br@akademiazamojska.edu.pl

Affiliation:

University of Management and Administration in Zamość Poland

Krzysztof Pancerz

br@akademiazamojska.edu.pl

Affiliation:

University of Management and Administration in Zamość Poland