Bankruptcy prediction using neural networks
Decision Support Systems - Special issue on neural networks for decision support
Self organizing neural networks for financial diagnosis
Decision Support Systems
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Data Envelopment Analysis: A Comprehensive Text with Models, Applications References, and DEA-Solver Software with Cdrom
Measuring the performances of decision-making units using interval efficiencies
Journal of Computational and Applied Mathematics
Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks
Decision Support Systems
A comparison of supervised and unsupervised neural networks in predicting bankruptcy of Korean firms
Expert Systems with Applications: An International Journal
Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
One of the most significant threats of a national economy is the bankruptcy of its firms. Assessment of bankruptcy provides valuable information on which governments, investors and shareholders can base their financial decisions in order to prevent possible losses. Data envelopment analysis (DEA) has generally been used to assess the best relative efficiency of decision making units (DMUs). In this paper we modify directional distance formulation of DEA to assess bankruptcy. The method we develop is the most general non-oriented, non-radial directional distance model. This model measures worst relative efficiency within the range of zero to one. This is contrary to the best relative efficiencies of conventional DEA method. Our model locates worst performing DMUs and determines an inefficient frontier. This model simultaneously contracts output and expands input. This idea of bankruptcy assessment is in agreement with economic theory of bankruptcy. The study introduces a precise and comprehensive bankruptcy measure that could be used as an early warning system for bankruptcy assessment. Further, we apply our model to Information Technology (IT) and IT enabled services (ITES) companies in India as a case study. We find that Hewlett-Packard Globalsoft Ltd. has the least possibility of bankruptcy and Logix Microsystems has the greatest possibility of bankruptcy.