COMPREHENSIVE MODEL FOR OPTIMIZING THE DEVELOPMENT OF ENTERPRISE INNOVATION ACTIVITIES UNDER EXTREME CONDITIONS

Abstract

The article presents a theoretical and methodological approach to developing a comprehensive model for optimizing the innovation activities of enterprises under extreme conditions caused by economic crises, pandemics, natural disasters, and other destabilizing factors. It is established that innovation serves as a key tool for ensuring enterprise resilience, adaptability, and competitiveness in an environment of heightened uncertainty. The proposed concept of a comprehensive approach combines five interrelated components: the creation of internal innovation units or R&D centers; partnerships with research institutions and universities; the implementation of knowledge management systems; the application of open innovation methods; and investment in digital technologies and automation. To quantitatively substantiate the proposed approach, a mathematical model is developed that formalizes the relationships between the main components of innovation activity and the resource constraints of enterprises. The model is based on maximizing the utility function of innovation activity, taking into account weighted coefficients that reflect the influence of R&D investment, partnerships, knowledge management systems, open innovations, and digital technologies. An improved version of the model includes nonlinear dependencies, external factors (economic, political, environmental), and interactive effects between variables that reflect real-world enterprise functioning. The study also substantiates the use of adaptive strategies that ensure dynamic updates of model parameters, sensitivity analysis to identify investment priorities, and monitoring mechanisms through key performance indicators (KPIs). The implementation of the comprehensive optimization model enables more efficient resource allocation, accelerates innovation processes, and strengthens enterprise competitiveness even under unstable conditions. The results of this research can be applied to strategic planning, risk management, and the development of sustainable business policies under extreme circumstances.