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Cited by 208

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Marketing research on mergers and acquisitions: a systematic review and future directions

Open access
Christofi, Michael, Leonidou, Erasmia, Vrontis, Demetris·2017·International Marketing Review

Abstract

Purpose: The purpose of this paper is to systematically review and critically examine marketing research on mergers and acquisitions (M&As), and articulates its importance and relevance in consideration of the growing influence of the M&A phenomenon in the global economy. Design/methodology/approach: A two-stage systematic review of the extant literature was conducted focusing on peer-reviewed journal articles published during a 28 year period – from 1987 to 2014. Findings: A systematic analysis of 32 journal articles reveals that M&A research is a vibrant and rapidly growing stream of the broader marketing domain, and that it is contextually, methodologically and thematically diverse. The findings also highlight several literature trends and shortcomings, as well as the complex nature of the relationship between marketing and M&As. Originality/value: On the basis of the critique, we develop an ambitious research agenda that raises exciting new research questions for the scholar community and helps promote future theory development in marketing, strategy, and other related disciplines.

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Metadata

Authors
Christofi, M., Leonidou, E., & Vrontis, D.
Venue
International Marketing Review
Publisher
Emerald
Published
2017-09-11
Volume
34
Issue
5
Pages
629-651
ISSN
0265-1335 (ISSN-L)
OpenAlex
W2738658193
Cited by
208
References
1
FWCI
10.20
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Marketing research on mergers and acquisitions: a systematic review and future directions. https://app.cochat.ai/papers/10.1108/imr-03-2015-0100
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Christofi, M., Leonidou, E., & Vrontis, D. (2017). Marketing research on mergers and acquisitions: a systematic review and future directions. International Marketing Review. https://doi.org/10.1108/imr-03-2015-0100

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.