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DECISION SUPPORT SOLUTION TO BUSINESS FAILURE PREDICTION

Madalina Popescu, Marin Andreica and Ion-Petru Popescu

Proceedings of the INTERNATIONAL MANAGEMENT CONFERENCE, 2017, vol. 11, issue 1, 99-106

Abstract: 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)
Date: 2017
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