Introduction. In the current situation, the society is subject to extremely dynamic changes and strategic developments are becoming obsolete more rapidly. It is cognitive modeling of complex semi-structured systems that is one of the modern methods that presents technological solutions in response to the challenge of obsolescence of strategies. The practice of strategizing Russia’s regions makes it possible to single out the regional dimension as a self-sufficient subject of cognitive modeling. The objective of the article is to summarize many years of experience of applying the method of cognitive modeling of regional socio-economic processes and the application of the obtained models in educational, scientific and administrative activities of the region on the basis of the study conducted. Materials and Methods. The database of Analytic software application was used as the information resource. Cognitive modeling was the main method employed and was considered in more detail; statistical methods, comparative analysis, and an expert survey were also used. Results. Specific examples of research conducted in the Nizhny Novgorod Region, the Samara Region, and the Republic of Mordovia have shown the advantages of using cognitive modeling technology in the educational, scientific, and administrative activities in a region. The factor-digital cognitive model of a region becomes the basis for organizing trainings on the strategy of sustainable development at the regional and interregional levels. Analytic software application supports the research process and is integrated into the electronic information and educational environment of regional universities. Discussion and Conclusion. The cognitive modeling method makes it possible to solve the problems of static and dynamic analysis of a region as a complex system in various subject areas. The factor-digital models of regions obtained using Analytic software application are of a universal nature and are relatively easily modified under the framework conditions of any other region of Russia on remote access platforms.

Introduction. The growing dependence of regional economies on innovation determines the importance of regional innovation policy, it being an integral part of regional economic policy. Within its framework, a constant assessment of mutual impact of the factors of regional development and successful startups is necessary. The goal of this study is to identify such basic factors. Materials and Methods. Regional socio-economic complexes of the Republic of Mordovia, Nizhny Novgorod Region and Samara Region are considered as the research object. Regional primary and secondary statistics on the research topic, legislative and regulatory acts of the federal and regional levels form the information basis of the study. The methods of system analysis, economic statistics, expert survey, economic and mathematical modeling as well as cognitive modeling were employed. Results. The primary and final lists of factors of mutual impact of innovative startups and the regional environment have been compiled. The features of modern startups and their interaction with the external environment have been exposed. The cause-and-effect relations between the factors have been identified. A quantitative and qualitative analysis of the factors, their grouping and classification for the subsequent modeling of innovative processes in the region has been performed. Discussion and Conclusion. The results obtained serve as the basis for correlation and regression analysis and the subsequent provision of a cognitive model of the regional innovation process that takes into account the peculiarities of the regions under consideration. The verified cognitive model makes it possible to construct prognostic scenarios of the impact of innovations on the regional growth and the influence of the regional environment on the growth of innovations, to conduct a justification, a comparative analysis and an assessment of the consequences of management decisions on development of the regional infrastructure to support entrepreneurship as well as to evaluate the adaptability of innovative startups to changes in external and internal environment factors.