Research on symbiosis models in manufacturing innovation ecosystems

Abstract

The symbiotic evolution model of manufacturing innovation ecosystems plays a critical role in driving high-quality development in the manufacturing sector. However, existing studies predominantly focus on the linear symbiotic relationships between manufacturing and related industries, overlooking the complexity of multi-actor, multi-level dynamic interactions in such ecosystems. This study applies symbiosis theory to develop a Lotka-Volterra evolution model for an innovation ecosystem comprising manufacturing core enterprises, supporting enterprises, and research institutions. Numerical simulations conducted using MATLAB explore the system’s symbiotic evolution patterns. The findings reveal that mutualistic symbiosis represents the optimal evolutionary pattern, effectively fostering collaboration and scaling growth among all actors. In contrast, commensal symbiosis limits system efficiency due to asymmetrical resource flows, while parasitic symbiosis, although boosting short-term competitiveness for specific actors, undermines overall stability and cooperation. Research institutions emerge as pivotal innovation drivers, playing an indispensable role in technological support and knowledge spillovers. Based on these results, the study recommends optimizing the health of manufacturing digital innovation ecosystems by enhancing resource-sharing platforms, guiding policy support, and strengthening industry-academia-research collaboration. The research’s novelty lies in developing a triadic evolutionary game model tailored to the manufacturing innovation ecosystem, integrating evolutionary game theory (EGT), the Lotka-Volterra model, and ecosystem innovation theory, thereby expanding their theoretical and practical applications.

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