Valuing Reciprocal Synergies in Merger and Acquisition Deals Using the Real Option Analysis
Andrejs Čirjevskis
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Andrejs Čirjevskis: Business Department, RISEBA University of Applied Sciences in Business, Arts, and Technology, LV-1048 Riga, Latvia
Administrative Sciences, 2020, vol. 10, issue 2, 1-25
Abstract:
This research explores how global cosmetic players sense emerging market demand for new technologies and products, seize opportunities through the acquisition of core competencies that they needed, and transform their global value chain. The aim of this paper to assess the prerequisites of reciprocal synergies in merger and acquisition (M&A) deals pursuing global growth. To achieve this aim, the author asked a research question: what is the best way to measure the competence-based synergies as added market value in M&A deals? To answer this question, the author researched the latest theoretical findings on the antecedents of synergy in the merger and acquisition processes. The valuation of reciprocal synergies with real options was discussed with a focus on input variables’ values. Based on in-depth content analysis, the ARCTIC (A—Advantage, R—Relatedness, C—Complexity of Competence, T—Time of Integration, I—Implementation Plan, C—Cultural Fit) framework was developed and tested. The author selected three case studies to test the methodology empirically, namely, L’Oréal’s Body Shop acquisition in 2006 and divestiture in 2017, the acquisition of The Body Shop by Brazilian’s Natura Group in 2017, and the acquisition of Avon Products by Natura that was announced in 2019. The model for the valuation of reciprocal synergies used and discussed real options with a special focus on input variables’ values.
Keywords: acquisitions; core competence; knowledge transfer; synergy; real options (search for similar items in EconPapers)
JEL-codes: L M M0 M1 M10 M11 M12 M14 M15 M16 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jadmsc:v:10:y:2020:i:2:p:27-:d:352621
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