Predicting Success of Mergers and Acquisitions in Manufacturing Sector in India: A Logistic Analysis

Abstract

Mergers and acquisitions (M&As) are the significant corporate restructuring activities that attract the attention among shareholders as they focus on wealth creation. The transactions that involve M&A deals are considered as very risky and challenging in nature. Thus, decision in M&A transactions is considered as most important investment decision of a company. It gives an immense opportunity for researchers to examine, observe and analyse the implications of these investment decisions on the value of shareholders wealth. Thus, academicians have done empirical research to know whether mergers and acquisitions finally lead to creation or destruction of company value or not. However, limited studies have analysed the determinants for predicting the success and failure of mergers and acquisitions in India. Hence, this paper attempted to find out the probability of the manufacturing companies in India being successful or unsuccessful after mergers and acquisitions using logistic regression. The period of study is from 2000 to 2008 for M&A deals during 1997 to 2011. In the study, rate of EVA (economic value added) which is considered as a better measure of performance, is used as dependent variable and the independent variables used are M&A Experience, Size of Acquirer, pre M&A current ratio, quick ratio, return on asset, return on capital employed, return on net worth, net profit margin, asset turnover ratio, interest coverage ratio. From the study it is found that the probability of a given firm being successful after M&A increases as the pre M&A current ratio, net profit margin decreases; while its pre M&A quick ratio and asset turnover ratio increases. It is also estimated that the Z score below 0.02 in case of M&A would indicate the company is probably headed for failure, while companies with scores above 0.02 are likely to be successful.