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 proceedingConference contributionAcademicpeer-review


    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 languageEnglish
    Title of host publicationNew Frontiers in Artificial Intelligence
    Subtitle of host publicationJSAI-isAI 2016 Workshops, LENLS HAT-MASH, AI-Biz, JURISIN and SKL, Kanagawa, Japan, November 14-16, 2016. Revised Selected Papers
    EditorsSetsuya Kurahashi, Yuiko Ohta, Sachiyo Arai, Ken Satoh, Daisuke Bekki
    Place of PublicationCham
    Number of pages16
    ISBN (Electronic)978-3-319-61572-1
    ISBN (Print)978-3-319-61571-4
    Publication statusPublished - 1 Jan 2017
    Event8th JSAI International Symposium on AI: JSAI-isAI 2016 - Raiosha, Hiyoshi Campus, Keio University, Yokohama, Japan
    Duration: 14 Nov 201616 Nov 2016
    Conference number: 7

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349
    NameLecture Notes in Artificial Intelligence


    Conference8th JSAI International Symposium on AI
    Abbreviated titleJSAI-isAI


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