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

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  • Yang Lin
  • Ying-Ming Wang
  • Hai-Liu Shi

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.

Suggested Citation

  • Yang Lin & Ying-Ming Wang & Hai-Liu Shi, 2020. "Mergers and acquisitions matching for performance improvement: a DEA-based approach," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 33(1), pages 3545-3561, January.
    • Handle: RePEc:taf:reroxx:v:33:y:2020:i:1:p:3545-3561
    DOI: 10.1080/1331677X.2020.1775673
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    Cited by:

    1. Hawkes, Adam & Muûls, Mirabelle & Hamilton, James W., 2023. "Big oil and the energy transition: Evidence from M&A," Energy Policy, Elsevier, vol. 183(C).

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