Predicting the Factors Influencing the Probability of Failure of Central Public Sector Enterprises - Pardeshi, Bhushan; Bisoyi, Padmalochana; Burbure, Pranita (International Journal of Psychosocial Rehabilitation, 2020)
In this study, the researchers tried to discover the extent to which internal factors explain the probability of failure of manufacturing central public sector enterprises. This study is apparent because of the increasing number of failures. The policies, regulations, and new strategies should be developed to assist the management and policymakers by investigating the factors that influence the probability of failure. For the purpose of this study, six medium and light engineering enterprises were selected as a sample, covering a study period of ten years. 15 variables were selected from the extensive review of past research that are identically correlated with the occurrence of failure. These variables were tested by using binary logistic regression. This model uses a binary dependent variable, a dummy variable for failure. The dummy variable is ‘o’ if the enterprise is non-failure and ‘1’ for failure. The result of logistic regression shows that working capital, net profit, return of assets, gross value added to capital employed, labor cost to sales, capital output ratio, and sales to total assets significantly influence the probability of failure. This study reveals the magnitude of firm-specific factors in determining and/or explaining the failure of enterprises. The study also examined financial health by using the Altman’s Z score model. The results show that the failed Central Public Sector Enterprises have registered a negative Z score and fall under the category of distress zone. The failure of Central Public Sector Enterprises may be avoided if indications and influencing factors are timely established and proper measures are taken to improve the financial situation. The study recommends testing the factors of failure every year after preparation of the financial report.