Application of Game Theory in M&A Decision of Listed Manufacturing Companies

Abstract

This study investigates the tripartite game mechanism in mergers and acquisitions (M&A) between state-owned enterprises (SOEs) and listed companies in the manufacturing sector. A dynamic evolutionary game model involving the government, SOEs, and listed companies is constructed based on evolutionary game theory. Python-based simulations and case validation are employed to analyze equilibrium stability. Key findings include: 1) Narrowing M&A price differentials increases the likelihood of SOEs adopting high-price strategies and government support; 2) Rising transaction costs drive SOEs to raise acquisition prices while enhancing listed companies' acceptance rates; 3) Widening income gaps boost listed companies' acceptance but reduce government incentives; 4) Government capital assistance directly influences strategic choices—greater capital disparities between parties promote high-price acquisitions and transaction success. The research provides a game-theoretic framework to optimize M&A decision-making, revealing how institutional dynamics and resource allocation shape cross-ownership restructuring outcomes.