Dynamic analysis and optimal control of knowledge diffusion model in regional innovation ecosystem under digitalization

• Published in: Scientific reports Vol. 14; no. 1; pp. 13124 - 17
• Main Authors: He, Zitong, Wang, Haijun, Hu, Yuhan, Ma, Xiaolin, Zhao, Huiyan
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 07.06.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/1041; 704/844/843; Control systems; Decision making; Diffusion; Digital technology; Digital transmission; Digitization; Ecosystems; Efficiency; Empowerment; Humanities and Social Sciences; Innovations; Knowledge; multidisciplinary; Science; Science (multidisciplinary); Sustainable development
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-63634-3

Knowledge diffusion in regional innovation ecosystems is an important factor that influences the regional innovation efficiency. In regional innovation ecosystems under digital empowerment, the knowledge diffusion enables the optimal allocation of innovation resources and promotes the sustainable development and ecological evolution of regional innovation ecosystems. In this paper, a SEIR (Susceptible–Exposed–Infected–Recovered) model is proposed for knowledge diffusion in regional innovation ecosystems under digitization. The basic reproduction number of the proposed model is calculated and its stability is validated. Finally, the expressions for the optimal control system and the optimal control parameters are presented. According to the research conclusions of this paper, the knowledge-diffusion ability of innovation agents in an innovation ecosystem affects the knowledge diffusion in a system; the contact rate between innovation agents affects the efficiency of knowledge diffusion in the system and the structure of the system; the digital transmission ability of innovation agents affects the breadth of knowledge diffusion in the system; and the self-learning ability of innovation agents affects the efficiency of knowledge diffusion in the system.The digital technologies help heterogeneous innovation agents in regional innovation ecosystems to break down the knowledge silos. At the same time, the digital technologies enhance the ability of innovation agents to absorb and learn knowledge in regional innovation ecosystems under digitization, thereby increasing the infection rate of knowledge diffusion in such systems.These conclusions extend the theoretical boundaries of innovation ecosystems and knowledge diffusion and offer management implications for enterprises and governments in decision-making.