An agent-based model for evaluating post-acquisition integration strategies

Jing Su; Mohsen Jafari Songhori; Takamasa Kikuchi; Masahiro Toriyama; Takao Terano

doi:10.1007/978-3-319-61572-1_13

An agent-based model for evaluating post-acquisition integration strategies

Jing Su^*, Mohsen Jafari Songhori, Takamasa Kikuchi, Masahiro Toriyama, Takao Terano

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Mergers and acquisitions become popular means for the development of modern corporations, allowing companies to obtain quick access to new markets and source to grow. Post-acquisition integration has been recognized to be influential to the success of M&A. In this paper, we develop an agent-based model to study post-acquisition integration strategies for M&A according to the behavioral theory of the firm. Especially, the model conceptualizes firms conducting search over associated NK performance landscapes. Using this model, our simulation experiments indicate that strategies of personnel allocation, high level manager’s feedback and the frequency of exchanging information could have impact on company’s performance after M&A.

Original language	English
Title of host publication	New Frontiers in Artificial Intelligence
Subtitle of host publication	JSAI-isAI 2016 Workshops, LENLS HAT-MASH, AI-Biz, JURISIN and SKL, Kanagawa, Japan, November 14-16, 2016. Revised Selected Papers
Editors	Setsuya Kurahashi, Yuiko Ohta, Sachiyo Arai, Ken Satoh, Daisuke Bekki
Place of Publication	Cham
Publisher	Springer
Pages	188-203
Number of pages	16
ISBN (Electronic)	978-3-319-61572-1
ISBN (Print)	978-3-319-61571-4
DOIs	https://doi.org/10.1007/978-3-319-61572-1_13
Publication status	Published - 1 Jan 2017
Externally published	Yes
Event	8th JSAI International Symposium on AI: JSAI-isAI 2016 - Raiosha, Hiyoshi Campus, Keio University, Yokohama, Japan Duration: 14 Nov 2016 → 16 Nov 2016 Conference number: 7

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	10247
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer

Conference

Conference	8th JSAI International Symposium on AI
Abbreviated title	JSAI-isAI
Country/Territory	Japan
City	Yokohama
Period	14/11/16 → 16/11/16

Keywords

n/a OA procedure

Access to Document

10.1007/978-3-319-61572-1_13

Cite this

Su, J., Songhori, M. J., Kikuchi, T., Toriyama, M., & Terano, T. (2017). An agent-based model for evaluating post-acquisition integration strategies. In S. Kurahashi, Y. Ohta, S. Arai, K. Satoh, & D. Bekki (Eds.), New Frontiers in Artificial Intelligence: JSAI-isAI 2016 Workshops, LENLS HAT-MASH, AI-Biz, JURISIN and SKL, Kanagawa, Japan, November 14-16, 2016. Revised Selected Papers (pp. 188-203). (Lecture Notes in Computer Science; Vol. 10247), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-319-61572-1_13

Su, Jing ; Songhori, Mohsen Jafari ; Kikuchi, Takamasa et al. / An agent-based model for evaluating post-acquisition integration strategies. New Frontiers in Artificial Intelligence: JSAI-isAI 2016 Workshops, LENLS HAT-MASH, AI-Biz, JURISIN and SKL, Kanagawa, Japan, November 14-16, 2016. Revised Selected Papers. editor / Setsuya Kurahashi ; Yuiko Ohta ; Sachiyo Arai ; Ken Satoh ; Daisuke Bekki. Cham : Springer, 2017. pp. 188-203 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence).

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title = "An agent-based model for evaluating post-acquisition integration strategies",

abstract = "Mergers and acquisitions become popular means for the development of modern corporations, allowing companies to obtain quick access to new markets and source to grow. Post-acquisition integration has been recognized to be influential to the success of M&A. In this paper, we develop an agent-based model to study post-acquisition integration strategies for M&A according to the behavioral theory of the firm. Especially, the model conceptualizes firms conducting search over associated NK performance landscapes. Using this model, our simulation experiments indicate that strategies of personnel allocation, high level manager{\textquoteright}s feedback and the frequency of exchanging information could have impact on company{\textquoteright}s performance after M&A.",

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author = "Jing Su and Songhori, {Mohsen Jafari} and Takamasa Kikuchi and Masahiro Toriyama and Takao Terano",

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editor = "Setsuya Kurahashi and Yuiko Ohta and Sachiyo Arai and Ken Satoh and Daisuke Bekki",

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Su, J, Songhori, MJ, Kikuchi, T, Toriyama, M & Terano, T 2017, An agent-based model for evaluating post-acquisition integration strategies. in S Kurahashi, Y Ohta, S Arai, K Satoh & D Bekki (eds), New Frontiers in Artificial Intelligence: JSAI-isAI 2016 Workshops, LENLS HAT-MASH, AI-Biz, JURISIN and SKL, Kanagawa, Japan, November 14-16, 2016. Revised Selected Papers. Lecture Notes in Computer Science, vol. 10247, Lecture Notes in Artificial Intelligence, Springer, Cham, pp. 188-203, 8th JSAI International Symposium on AI, Yokohama, Japan, 14/11/16. https://doi.org/10.1007/978-3-319-61572-1_13

An agent-based model for evaluating post-acquisition integration strategies. / Su, Jing; Songhori, Mohsen Jafari; Kikuchi, Takamasa et al.
New Frontiers in Artificial Intelligence: JSAI-isAI 2016 Workshops, LENLS HAT-MASH, AI-Biz, JURISIN and SKL, Kanagawa, Japan, November 14-16, 2016. Revised Selected Papers. ed. / Setsuya Kurahashi; Yuiko Ohta; Sachiyo Arai; Ken Satoh; Daisuke Bekki. Cham: Springer, 2017. p. 188-203 (Lecture Notes in Computer Science; Vol. 10247), (Lecture Notes in Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - An agent-based model for evaluating post-acquisition integration strategies

AU - Su, Jing

AU - Songhori, Mohsen Jafari

AU - Kikuchi, Takamasa

AU - Toriyama, Masahiro

AU - Terano, Takao

N1 - Conference code: 7

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Mergers and acquisitions become popular means for the development of modern corporations, allowing companies to obtain quick access to new markets and source to grow. Post-acquisition integration has been recognized to be influential to the success of M&A. In this paper, we develop an agent-based model to study post-acquisition integration strategies for M&A according to the behavioral theory of the firm. Especially, the model conceptualizes firms conducting search over associated NK performance landscapes. Using this model, our simulation experiments indicate that strategies of personnel allocation, high level manager’s feedback and the frequency of exchanging information could have impact on company’s performance after M&A.

AB - Mergers and acquisitions become popular means for the development of modern corporations, allowing companies to obtain quick access to new markets and source to grow. Post-acquisition integration has been recognized to be influential to the success of M&A. In this paper, we develop an agent-based model to study post-acquisition integration strategies for M&A according to the behavioral theory of the firm. Especially, the model conceptualizes firms conducting search over associated NK performance landscapes. Using this model, our simulation experiments indicate that strategies of personnel allocation, high level manager’s feedback and the frequency of exchanging information could have impact on company’s performance after M&A.

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BT - New Frontiers in Artificial Intelligence

A2 - Kurahashi, Setsuya

A2 - Ohta, Yuiko

A2 - Arai, Sachiyo

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A2 - Bekki, Daisuke

PB - Springer

CY - Cham

T2 - 8th JSAI International Symposium on AI

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ER -

Su J, Songhori MJ, Kikuchi T, Toriyama M, Terano T. An agent-based model for evaluating post-acquisition integration strategies. In Kurahashi S, Ohta Y, Arai S, Satoh K, Bekki D, editors, New Frontiers in Artificial Intelligence: JSAI-isAI 2016 Workshops, LENLS HAT-MASH, AI-Biz, JURISIN and SKL, Kanagawa, Japan, November 14-16, 2016. Revised Selected Papers. Cham: Springer. 2017. p. 188-203. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). doi: 10.1007/978-3-319-61572-1_13

An agent-based model for evaluating post-acquisition integration strategies

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