Power Governance and Knowledge Transfer: An Asymmetric Evolutionary Game Analysis of Reverse Cross‐Border M&A Integration
ABSTRACT This study examines the trade‐off between control and autonomy in reverse cross‐border mergers and acquisitions (M&As). It theorizes how different post‐merger integration (PMI) strategies shape knowledge‐transfer dynamics between emerging‐market parents and advanced‐economy subsidiaries. Drawing on evolutionary game theory as a foundation, we develop an asymmetric model that captures the co‐evolution of governance behaviors between parents and subsidiaries. To assess the robustness of this model, we employ simulation‐based validation techniques. The analysis demonstrates that governance decisions by the parent firm play a pivotal role in determining the evolutionary outcome of the knowledge‐transfer game, leading to the emergence of two distinct types of dynamically stable equilibria: (1) structural integration coupled with subsidiary resistance, and (2) autonomy‐granting coupled with subsidiary cooperation. Furthermore, when the efficiency loss in knowledge transfer is lower than the management and knowledge‐loss costs associated with structural integration, autonomy granting yields superior long‐term outcomes; otherwise, the system converges on a suboptimal but stable low‐efficiency state. The study identifies threshold effects related to absorptive capacity, knowledge acquisition, and transfer efficiency, and highlights governance as a central mechanism for shaping post‐acquisition knowledge flows. The findings contribute to advancing the theory of PMI by establishing a correlation between strategic integration choices and dynamic patterns of learning, cooperation, and long‐term value creation.
Authors
- Yihua Wu (ORCID: https://orcid.org/0000-0001-9503-6038)
Institutions
- Institute of Scientific and Technical Information of China (CN)
Publication Details
- Journal
- Thunderbird International Business Review
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1002/tie.70051
- Primary Topic
- Game Theory and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00