Abstract
The study tested the scientific hypothesis about the possibility of creating a neural recurrent model of the circular economy for an adequate representation of its key processes. To develop such a model, various conceptual models, mathematical descriptions of certain circular economic processes, and approaches were taken for analysis. Next, the parameters and indicators used by some groups of researchers to measure indicators of the circular economy were reviewed. Simulation modeling based on system dynamics and deep recurrent neural network modeling based on the multilayer feed-forward neural network configuration were used to build a model containing many deep multi-level feedbacks. The simulation and neuronet tools not only allowed to work with quantitative data obtained during the simulation model run, but also to evaluate the information suitability of the constructed model. The results confirmed the scientific hypothesis and permitted to make conclusions that should form the basis for further research of circular economy processes, apply project management tools at the level of public administration and corporate governance to address the identified threats when planning strategic development programs for countries, regions, cities, industries, and companies.
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Khalimon, E.A., Brikoshina, I.S., Guseva, M.N. (2023). The System Dynamics Model for the Impact Assessment of Project Management on Circular Economic Processes. In: Obradović, V. (eds) Sustainable Business Change. Springer, Cham. https://doi.org/10.1007/978-3-031-23543-6_9
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