An Agent-Based Model for Evaluating Post-acquisition Integration Strategies

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.