Valuing reciprocal synergies in merger and acquisition deals using the real option analysis

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 reciproca...

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Published in:Administrative Sciences
Main Author: Čirjevskis, Andrejs
Format: Article in Journal/Newspaper
Language:English
Published: Basel: MDPI 2020
Subjects:
Online Access:http://hdl.handle.net/10419/240017
https://doi.org/10.3390/admsci10020027
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spelling ftzbwkiel:oai:econstor.eu:10419/240017 2024-01-21T10:03:59+01:00 Valuing reciprocal synergies in merger and acquisition deals using the real option analysis Čirjevskis, Andrejs 2020 http://hdl.handle.net/10419/240017 https://doi.org/10.3390/admsci10020027 eng eng Basel: MDPI gbv-ppn:1730511899 Journal: Administrative Sciences ISSN: 2076-3387 Volume: 10 Year: 2020 Issue: 2 Pages: 1-25 Basel: MDPI doi:10.3390/admsci10020027 http://hdl.handle.net/10419/240017 RePEc:gam:jadmsc:v:10:y:2020:i:2:p:27-:d:352621 http://www.econstor.eu/dspace/Nutzungsbedingungen https://creativecommons.org/licenses/by/4.0/ ddc:350 acquisitions core competence knowledge transfer real options synergy doc-type:article 2020 ftzbwkiel https://doi.org/10.3390/admsci10020027 2023-12-25T00:42:50Z 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 inM&Adeals? 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. Article in Journal/Newspaper Arctic EconStor (German National Library of Economics, ZBW) Arctic Administrative Sciences 10 2 27
institution Open Polar
collection EconStor (German National Library of Economics, ZBW)
op_collection_id ftzbwkiel
language English
topic ddc:350
acquisitions
core competence
knowledge transfer
real options
synergy
spellingShingle ddc:350
acquisitions
core competence
knowledge transfer
real options
synergy
Čirjevskis, Andrejs
Valuing reciprocal synergies in merger and acquisition deals using the real option analysis
topic_facet ddc:350
acquisitions
core competence
knowledge transfer
real options
synergy
description 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 inM&Adeals? 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.
format Article in Journal/Newspaper
author Čirjevskis, Andrejs
author_facet Čirjevskis, Andrejs
author_sort Čirjevskis, Andrejs
title Valuing reciprocal synergies in merger and acquisition deals using the real option analysis
title_short Valuing reciprocal synergies in merger and acquisition deals using the real option analysis
title_full Valuing reciprocal synergies in merger and acquisition deals using the real option analysis
title_fullStr Valuing reciprocal synergies in merger and acquisition deals using the real option analysis
title_full_unstemmed Valuing reciprocal synergies in merger and acquisition deals using the real option analysis
title_sort valuing reciprocal synergies in merger and acquisition deals using the real option analysis
publisher Basel: MDPI
publishDate 2020
url http://hdl.handle.net/10419/240017
https://doi.org/10.3390/admsci10020027
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation gbv-ppn:1730511899
Journal: Administrative Sciences
ISSN: 2076-3387
Volume: 10
Year: 2020
Issue: 2
Pages: 1-25
Basel: MDPI
doi:10.3390/admsci10020027
http://hdl.handle.net/10419/240017
RePEc:gam:jadmsc:v:10:y:2020:i:2:p:27-:d:352621
op_rights http://www.econstor.eu/dspace/Nutzungsbedingungen
https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/admsci10020027
container_title Administrative Sciences
container_volume 10
container_issue 2
container_start_page 27
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