Economic and Mathematical Modeling of Risks in the Service Business Model of a Network Enterprise

The aim of the research is to develop an economic and mathematical model of risk assessment in the service business model of a network enterprise, capable of formalizing the impact of various risk factors on the stability of the network structure and developing effective strategies for managing them. Materials and methods. The paper uses stochastic methods, optimization methods, graph theory, and system dynamics. The modeling algorithm includes the stages of risk identification, parameter formalization, cascade effects analysis, network structure assessment, and management strategy optimization. The example of the MindSphere IoT-platform and the ecosystem of its participants is used as an empirical base. Results . A comprehensive approach to quantitative risk ssessment in digital ecosystems has been developed based on cascade analysis, assessment of the centrality of ecosystem nodes, and damage modeling. A comprehensive approach to quantitative risk assessment involves the integration of methods that allow not only to measure the probability and potential damage of individual threats, but also consider their interrelationships, development dynamics and impact on the structure of the service business model of a network enterprise. This approach provides not only the calculation of expected losses, but also the identification of critical points of the system, the development of preventive measures and visualization of the results for informed decision-making, which is especially important for a complex ecosystem where risks are increased due to the interdependence of its participants. Conclusion. The developed model allows quantifying interrelated risks in service business models, taking into account the network interconnection of risks and structural vulnerabilities of ecosystems. This ensures informed decision-making when managing the stability of the network structure. The results are of practical importance for the industry, which is actively implementing IoT and cloud solutions