Research on ambidextrous digital innovation strategies of SMEs embedded in industrial internet platforms based on evolutionary game theory

In the accelerating digital economy, small and medium-sized enterprises (SMEs) encounter a dual challenge in pursuing ambidextrous digital innovation (exploratory and exploitative), constrained by limited resources and path dependence. Industrial internet platforms, functioning as central hubs for resources, technologies, and data, play a pivotal role in addressing these challenges. Existing research has not sufficiently examined how the strategic interactions among governments, platforms, and SMEs influence SMEs' ambidextrous digital innovation decisions within platform ecosystems. This study investigates these coupled strategies by constructing a group dynamic decision-making model grounded in evolutionary game theory. By employing replicator dynamics and evolutionary stability analysis, it reveals the patterns of strategic selection, and simulation experiments are conducted with reference to case studies. The results reveal significant coupling effects among the three parties' strategies: the system may converge to a "conservative equilibrium" or shift toward a "high-level innovation equilibrium." Critical factors, including ecosystem synergy value, technological spillover, government subsidy intensity, and the cost of platform empowerment, jointly determine the trajectory and pace of system evolution. Breaking away from suboptimal equilibria requires the establishment of risk-sharing and reward-sharing mechanisms, which foster evolutionary stability of the digital innovation ecosystem through tripartite collaboration. This research broadens the application of ambidextrous innovation theory in platform ecosystems and offers theoretical and practical insights for SME decision-making, platform empowerment, and policy design.