This study aims to develop business failure prediction models using the data of selected firms from ISE markets. The sample data comprise ten selected financial ratios for 27 non-going concerns (failed businesses) and paired 27 going concerns. Two non-parametric classification methods are used in the study: Artificial Neural Networks (ANN) and Decision Trees. The classification results show that there is equilibrium in the classification of the training samples by the models, but ANN model outperform the decision tree model in the classification of the testing samples. Further, the potential usefulness of ANN and Decision Tree type data mining techniques in the analysis of complex and non-linear relationships are observed.M.B.A. - Master of...
The purpose of this study is to explore the applicability of a form of the artificial neural network...
The prediction of business failure is a widely studied subject in financialliterature. Many earlier ...
Corporate failure is one of the most popular prediction problems because early identification of at-...
Operational failures are closely related to many interest groups within and outside of the companies...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
Research background: The issue of predicting the financial situation of companies is a relatively yo...
AbstractDue to the uncertainty of the current business environment and global competition, not only ...
Over the last 35 years, the topic of company failure prediction has developed to a major research do...
Over the last 35 years, the topic of company failure prediction has developed to a major research do...
Prediction of corporates bankruptcies is a topic that has gained more importance in the last two dec...
Business failure prediction is a topic of great importance for a lot of people (shareholders, banks,...
Research analysis of small enterprises are still rare, due to lack of individual level data. Small e...
This study examines the use of data mining techniques namely decision tree, neural networks and logi...
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University...
The purpose of this study is to explore the applicability of a form of the artificial neural network...
The prediction of business failure is a widely studied subject in financialliterature. Many earlier ...
Corporate failure is one of the most popular prediction problems because early identification of at-...
Operational failures are closely related to many interest groups within and outside of the companies...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
A growing number of predicting corporate failure models has emerged since 60s. Economic and social c...
Research background: The issue of predicting the financial situation of companies is a relatively yo...
AbstractDue to the uncertainty of the current business environment and global competition, not only ...
Over the last 35 years, the topic of company failure prediction has developed to a major research do...
Over the last 35 years, the topic of company failure prediction has developed to a major research do...
Prediction of corporates bankruptcies is a topic that has gained more importance in the last two dec...
Business failure prediction is a topic of great importance for a lot of people (shareholders, banks,...
Research analysis of small enterprises are still rare, due to lack of individual level data. Small e...
This study examines the use of data mining techniques namely decision tree, neural networks and logi...
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University...
The purpose of this study is to explore the applicability of a form of the artificial neural network...
The prediction of business failure is a widely studied subject in financialliterature. Many earlier ...
Corporate failure is one of the most popular prediction problems because early identification of at-...