Computer-aided Numerical Simulation Analysis of Collaborative Innovation within Government-Industry-University-Institute Models Using Evolutionary Game Theory

Abstract

Collaborative innovation among government, industry, universities, and institutes (GIUI) is an essential approach for achieving national development driven by innovation and enhancing regional competitiveness. However, the existing collaborative innovation faces challenges such as uneven distribution of benefits, unequal risk sharing, and inadequate institutional and policy support. This study harnesses the power of numerical simulation to dissect the complexities of GIUI collaboration, using the evolutionary game theory to construct a payoff matrix. By conducting numerical simulations using the Matlab software program, we identify two asymptotically stable points in the system. Our findings highlight that variables such as the gain coefficient (t) from government engagement with industry and academic institutes, the preferential tax rate (K) offered to industry, and the subsidy (A) invested in academic institutes significantly influence the consensus towards collaborative innovation. Furthermore, our analysis suggests that governments should actively monitor and coordinate the distribution of benefits within complex multi-agent collaborative innovation networks. By taking an active role in ensuring a fair and efficient distribution, governments can directly address the challenges arising from the current framework. This study employs computational methods to offer an advanced approach to understanding and optimizing the dynamics of collaborative innovation within the GIUI framework. By utilizing computer methods such as numerical simulation, we gain valuable insights into the complexities of collaborative innovation and provide a foundation for government decision-making.