Cross-Border Acquisitions: Assessment of Financial Efficiency Using Data Envelopment Analysis

Authors

  • Samta Jain The Institute of Cost Accountants of India
  • P. K. Jain The Institute of Cost Accountants of India

DOI:

https://doi.org/10.33516/rb.v46i1-2.17-26p

Keywords:

Cross-Border Acquisitions, DEA, Variable Returns to Scale Model, Malmquist Productivity Index.

Abstract

The objective of the paper is to assess the financial efficiency of Indian acquiring companies engaged in cross-border acquisitions. A model based on DEA has been developed to assess the corporate performance. Financial evaluation, being the most widely used approach to assess the performance of companies, are based on financial statements. Hence, the measures of financial performance (based on financial ratios) for a period of one year pre and post-acquisition including: liquidity ratios, activity ratios and leverage ratios are employed as inputs and profitability ratios as output indices of Data Envelopment Analysis (DEA) model. There has been a significant deterioration in the financial performance of the majority of the acquirers post-acquisition. On an average the financial efficiency of acquirers declined to 80%.The model so developed can be used in comparing the efficiency of different multinational companies to provide some suggestions for future. Such analyses can further provide insights to managers to guide their future endeavours. Major advantage of using DEA is that it indicates how much the inefficient firm deviates from the efficient firm; thus allowing for possible efficiency improvement. To the best knowledge of the authors, no cross-border acquisition study has evaluated the financial performance of acquirers across different industries using DEA. Hitherto, the focus of researches have been only on one industry, say banking industry, insurance industry, health industry.

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Published

2020-07-31

How to Cite

Jain, S., & Jain, P. K. (2020). Cross-Border Acquisitions: Assessment of Financial Efficiency Using Data Envelopment Analysis. Research Bulletin, 46(1-2), 17–26. https://doi.org/10.33516/rb.v46i1-2.17-26p

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