Supporting Information System Integration Decisions in the Post-Merger Context

Authors

  • Ksenija Lace Department of Artificial Intelligence and Systems Engineering, Faculty of Computer Science and Information Technology, Riga Technical University, 6A Kipsalas Street, Riga, LV-1048 https://orcid.org/0000-0001-8196-1863

DOI:

https://doi.org/10.7250/csimq.2023-34.02

Keywords:

Mergers and Acquisitions, Post-Merger Integration, Information System Integration, Decision-Making

Abstract

Consolidation of organizations and assets through Mergers and Acquisitions (M&A) is one of the strategies for organizational growth. However, despite the big popularity, the results of M&A initiatives are questionable. The main idea behind M&A is to create a new organization by combining several existing organizations. This new organization is created through a transformation process often called a post-merger. A significant part of the post-merger process is the integration of information systems. The success of post-merger information systems integration is the result of successful integration decisions. This study focuses on the problem of how a novice organization in post-merger initiatives can handle complexity in the decision-making process of post-merger information systems integration with its internal resources, without involvement of an external expertise, but with a support method to compensate the lack of expertise for informed decision-making. The extended decision-making process can be divided into three phases – identification of necessary decisions, decision-making, and decision implementation. This study focuses on the first two phases. For each of the phases, a specialized sub-method was developed, focused, respectively, on the identification of necessary decisions (AMILI) and decision-making as a choice between possible integration options (AMILP). Supporting tools were also developed for each of the sub-methods.

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Published

30.04.2023

How to Cite

Lace, K. (2023). Supporting Information System Integration Decisions in the Post-Merger Context. Complex Systems Informatics and Modeling Quarterly, 34, 30-61. https://doi.org/10.7250/csimq.2023-34.02