Mergers and acquisitions matching for performance improvement: a DEA-based approach

Yang Lin, Ying-Ming Wang and Hai-Liu Shi

Economic Research-Ekonomska Istraživanja, 2020, vol. 33, issue 1, 3545-3561

Abstract: This article proposes a new data envelopment analysis (DEA)-based approach to deal with mergers and acquisitions (M&As) matching. To derive reliable matching degrees between bidder and target firms, we consider both technical efficiency and scale efficiency. Specifically, an inverse DEA model is developed for measuring the technical efficiency, while a conventional DEA model is employed to identify the return of scale of the merged decision-making units (DMUs). Then, an optimization model is formulated to generate matching results to improve DMUs’ performance. An empirical study of M&As matching Turkish energy firms is examined to illustrate the proposed approach. This study shows that both technical efficiency and scale efficiency have impacts on M&As matching practices.

Date: 2020
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DOI: 10.1080/1331677X.2020.1775673

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