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Motive archetypes in Mergers and Acquisitions (M&A): the implications of a configurational approach to performance

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter

Publication date2007
Host publicationAdvances in Mergers and Acquisitions
EditorsCary Cooper, Sydney Finkelstein
Number of pages29
ISBN (Electronic)9781849504676
ISBN (Print)9780762313815
<mark>Original language</mark>English

Publication series

NameAdvances in Mergers and Acquisitions
ISSN (Print)1479-361X


Why do managers continue to transact merger & acquisition (M&A) deals, in massive number and dollar terms, when so many are deemed to fail? This paradox is central to the study of M&A. Despite considerable research effort being devoted to refining and redefining assessments of M&A performance the consensus of opinion remains that most M&A fail. Certain of the high percentage of M&A failure, performance academics infer that the continued massive levels of transactions can only be explained as misguided actions by managers. This chapter believes that the performance paradox can begin to unravel if we move beyond simple inference of managerial intentions and observe what actually takes place in practice. For instance the underlying assumptions of performance academics, that; 1) each M&A must create greater value for acquiring shareholders; 2) no other reasons for an M&A are legitimate, are not adequate for capturing ‘legitimate’ managerial action in practice. This suggests that part of the reason for so many M&A appearing to be failures is a result of the ‘myopia’ of performance studies themselves, where assumed and simplified motives have resulted in crude categorisations and confounded data. These limitations in the M&A performance literature are addressed in this chapter by; 1) demonstrating a broader set of motivations for M&A; 2) establishing their legitimacy; 3) showing that motivations may not be singular in nature but intertwined and complex; 4) presenting a way in which this greater complexity may be conceived in order for more sensitive empirical tests to be performed.