Digital Transformation and Modeling of Nature-Inspired Systems

With the tightening of environmental regulations, the need to identify tools that foster the development of sustainable systems is growing. The shift toward closed-loop, bio-like systems promotes the creation of nature-inspired systems. However, the transformation processes and toolkits vary across meso-level systems with differing economic activity. This research reveals the patterns of formation and develops governance models for the evolution of nature-inspired systems, considering the specifics of digital transformation and innovative activity in ensuring environmental security. Methodology includes the following: correlation and regression analysis, factor and cluster analysis, along with automated neural network simulations. The study resulted in the expansion of conceptual frameworks for “nature-inspired system” formation; revealed dependencies between the formation of a nature-inspired macrosystem and mesosystems, while identifying growth hotspots for nature-inspired systems in Russia; identified the priority determinants of nature-inspired mesosystem formation; proposed a composite index (DNIS—Development of a Nature-Inspired System) to assess the cumulative impact of determinants and evaluate ecological performance responses; and developed a typology of regional mesosystems based on economic/ecological performance and “green” technology adoption, enabling differentiated approaches to guiding nature-inspired system development. The findings presented in this study are recommended for applications in improving regional socio-economic development programs.