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Financial Benchmarking Using Self-Organizing Maps - Studying the International Pulp and Paper Industry
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Author(s): Tomas Eklund (Turku Centre for Computer Science, Finland), Barbro Back (Abo Akademi University, Finland), Hannu Vanharanta (Pori School of Technology and Economics, Finland)and Ari Visa (Tampere University of Technology, Finland)
Copyright: 2003
Pages: 27
Source title:
Data Mining: Opportunities and Challenges
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-051-6.ch014
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Abstract
Performing financial benchmarks in today’s information-rich society can be a daunting task. With the evolution of the Internet, access to massive amounts of financial data, typically in the form of financial statements, is widespread. Managers and stakeholders are in need of a tool that allows them to quickly and accurately analyze these data. An emerging technique that may be suited for this application is the self-organizing map. The purpose of this study was to evaluate the performance of self-organizing maps for the purpose of financial benchmarking of international pulp and paper companies. For the study, financial data in the form of seven financial ratios were collected, using the Internet as the primary source of information. A total of 77 companies and six regional averages were included in the study. The time frame of the study was the period 1995-2000. A number of benchmarks were performed, and the results were analyzed based on information contained in the annual reports. The results of the study indicate that self-organizing maps can be feasible tools for the financial benchmarking of large amounts of financial data.
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