Abstract: Innovative ecosystem is one of the tools to create conditions for achieving competitive positions that reduces vulnerability to possible factors of market instability. At the same time, the need for efficient measures to develop digital ecosystems implies not only an understanding of their qualitative content, but also an accurate quantitative assessment. [...] Load More The aim of this study is to develop a dynamic model to diagnose the development parameters of an innovation ecosystem. Factors of synergetic effect of mergers and acquisitions in the entrepreneurial structures and in the biological system were substantiated and systematized. Using the generalization method, motivational drivers for mergers and acquisitions were identified, while the synectic method provided a rationale for the analogies of behavior of subjects in ecosystems in role positions pf "predator" and "victim". The consequences of mergers and acquisitions in biological and economic systems are argumentative. The components of the innovation ecosystem as a dynamic system have been determined and the qualitative characteristics of linear dependencies between them under conditions of the equilibrium state of the ecosystem have been substantiated using a linear function. The Lotka-Volterra equations served as a tool to describe the behavior of two business units from the point of view of the predator-victim roles. The parameters of this predictive model are the components that ensure the dynamic state of the innovation ecosystem. In order to describe the process of acquisition and merger in the business environment, large business enterprises were defined as "predators", while small business enterprises were defined as "victims". The correlation analysis determined the inversely proportional and volatile nature of the relationship between the dynamic series of newly established business units and the number of bankrupt businesses. Different numerical values of the parameters of the innovation ecosystem functioning have been modeled characterizing different modifications of its state (equilibrium, gradual decline, complete extinction, and exponential growth). The study also determined parameters for modeling exponential growth of the ecosystem. The results are confirmed by the model adequacy indicators, which prove their reliability. The results of this study may be useful for diagnostics and management of the innovation ecosystem in order to ensure its sustainable growth by both business and government authorities.

Keywords: innovation, ecosystem, dynamic system, merger, acquisition, synergistic effect