DECISION SUPPORT SOLUTION TO BUSINESS FAILURE PREDICTION
Marin Andreica and
Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, 2017, vol. 11, issue 1, 99-106
This paper aims to develop a practical decision support solution to business failure prediction, as early warning signals of potential financial distress could become a true asset in the decision making process of a firm. Several prediction models, such as decision trees and neural networks are built on a sample of Romanian firms and tested for their prediction ability. In order to try to improve the prediction ability of the tree model, we propose a method based on principal component analysis. The high prediction accuracy of the models suggests that the proposed decision support solution can become a practical tool for any decision maker.
Keywords: decision support solution; financial distress; prediction; CHAID trees; neural networks (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:rom:mancon:v:11:y:2017:i:1:p:99-106
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