Multiparty co-evolution of digital innovation ecosystems: from a perspective of data elements

Purpose The purpose of this paper is to analyse the multiparty co-evolution of digital innovation ecosystems from the perspective of data elements. Design/methodology/approach Based on the logistic model and the Lotka-Volterra model, this study constructs a multi-agent symbiotic evolution model for the digital innovation ecosystems and conducts a comprehensive study from theoretical, empirical, and simulation perspectives. Findings The research reveals that symbiotic units such as leading agents, complementary agents, and embedded agents drive the symbiotic evolution of the digital innovation ecosystem by forming different symbiotic patterns. The symbiotic coefficient, as a crucial parameter, plays a significant role in determining both the ultimate equilibrium state of the digital innovation ecosystem and the evolution direction of the three types of agents based on data elements. Leading agents serve as the development engine within the system. The mutually beneficial symbiotic model is identified as the optimal symbiotic model. Originality/value This study transcends traditional “single-core” and “dual-agent” paradigms by adopting a multi-agent participation perspective. Based on the differences in ownership and similarity of data elements possessed by the agents, it still defines the core agent as the leading agent while further segmenting stakeholders into complementary agents and embedded agents. Additionally, this paper constructs a symbiotic evolution model for the digital innovation ecosystem grounded in dynamic game theory, which uncovers the dynamic laws governing the evolution of symbiotic relationships. The model contributes to the establishment of a dynamic development system characterized by multi-agent participation, market-oriented operation, and collaborative governance.