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

Mergers and acquisitions (M&As) are significant corporate restructuring activities that attract the attention of shareholders as they focus on wealth creation. Such transactions are considered as very risky and challenging and at the same time very important company investment decisions. Empirical research academicians are keen to know whether mergers and acquisitions as investment transactions lead to the creation or destruction of company value. To date, few studies have analysed the determinants for predicting the success and failure of mergers and acquisitions in India. This paper attempted to use logistic regression to find out the probability of post mergers and aquisitions success or failure of manufacturing companies in India.. The period of study was from 2000 to 2008 for M&A deals during 1997 to 2011. In the study, the rate of EVA (economic value added), considered as a better measure of performance, was used as dependent variable and the independent variables used were 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, and interest coverage ratio. The study found that the probability of a given firm being successful after M&A increased as the pre-M&A current ratio, net profit margin decreased; while its pre-M&A quick ratio and asset turnover ratio increased. It was also estimated that the Z score below 0.02 in the case of M&A would indicate the company was probably headed for failure, while companies with scores above 0.02 were likely to be successful.