Evolutionary Mechanisms of Disruptive Innovation: A Multi-Agent Simulation Based on Complex Adaptive Systems

Despite extensive research on the antecedents of disruptive innovation, how disruptive innovation evolves through interacting mechanisms within complex adaptive systems remains insufficiently understood. To address this gap, this study conceptualizes disruptive innovation as an industry-level evolutionary process shaped by three differentiated mechanisms: the network mechanism, institutional mechanism, and resource mechanism. Drawing on Complex Adaptive Systems Theory, we develop an agent-based simulation model integrated with a genetic algorithm and complement the simulation with regression analysis to examine how these mechanisms shape technological penetration, market dynamics, and enterprise adoption. Based on 30 independent simulation replications with fixed random seeds and systematic sensitivity analysis, the results reveal three distinct evolutionary effects. First, higher social network connectivity does not necessarily accelerate disruptive-technology diffusion; when network advantages are concentrated among incumbent firms, stronger connectivity reinforces incumbent entrenchment and delays technological substitution. Second, government subsidies serve as an effective institutional lever, with greater subsidy intensity systematically accelerating the market penetration of disruptive technology. Third, initial resource endowment has limited influence on the timing of disruption, while heterogeneous resource configurations generate differentiated effects on market share, market price, and enterprise adoption. These findings demonstrate that disruptive innovation emerges not from isolated technological or organizational factors, but from the dynamic interactions of heterogeneous firms within a complex adaptive system. By distinguishing the different evolutionary functions of network connectivity, institutional intervention, and resource configuration, this study advances a mechanism-based understanding of disruptive innovation and provides implications for managing technological transitions through context-sensitive network development, targeted institutional support, and strategic resource allocation.