In the article, the authors emphasize that industrial regions play an important role in the increasing of technological independence of Russia. We show that the decline in the share of processing industries in the gross regional product can not be treated as a negative de-industrialization of the economy. The article proves that the increase in the speed of changements, instability of socio-economic systems, the diverse risks predetermine the need to develop new methodological approaches to predictive research. The studies aimed at developing a technology for the design of the desired image of the future and the methodology for its evaluation are of high importance. For the initial stage of the research, the authors propose the methodological approach for assessing the desired image of the future of metallurgy as one of the most important industry of the region. We propose the term of «technological image of the regional metallurgy». We show that repositioning the image of the regional metallurgical complex is quite a long process. This have determined the need to define the stages of repositioning. The proposed methodology of the evaluation of desired future includes the methodological provisions to quantify the characteristics of goals achieved at the respective stages of the repositioning of the metallurgy. The methodological approach to the design of the desired image of the future implies the following stages: the identification of the priority areas of the technological development of regional metallurgy on the basis of bibliometric and patent analysis; the evaluation of dynamics of the development of the structure of metal products domestic consumption based on comparative analysis and relevant analytical methods as well as its forecasting; the design of the factor model, allowing to identify the parameters quantifying the technological image of the regional metallurgy based on the principal components method,; systematization of predicted values of the parameters defining the stages of repositioning and designing the new technological image of the regional metallurgy; the development of mathematical model for the recognition of the technological image of a regional metallurgy on the basis of neural networks.

In recent years, inter-regional cooperation has increased in one of the most important areas of economy, namely, its innovative development. The Strategy of Spatial Development of the Russian Federation for the period until 2025 set various aims for scientific, technological and innovative development of the country. Inter-regional cooperation is one of the means for achieving these aims. Thus, we decided to examine interactions between closely located innovation-active territories such as entities of the Russian Federation and promising federal centres of economic growth. The study focuses on 8 industrialised innovation-active entities located on the territory of the Urals, Volga region and Western Siberia. The administrative centres of these regions rank as promising centres of economic growth and have opportunities to establish world-class Research and Educational Centres. For assessing the level of interaction between the regions in terms of innovation activity, we applied a method of spatial autocorrelation. Drawing on the Moran’s test, we assessed the autocorrelation between geographically close territories based on the data for 2007, 2013 and 2018. We took into account possible transformations of dynamic spatial effects caused by external and internal changes. According to the study, in 2007, a trend of regional clustering in terms of innovation activity was identified in certain areas of the Siberian Federal District (Novosibirsk and Tomsk oblasts). By 2013, this trend only increased due to the inclusion of Omsk oblast in this group of territories. Moreover, in the same year the signs of regional clustering in terms of innovation activity caused by spatial effects were discovered in the territories of the Volga Federal District. They appeared due to similar processes occurring in the special industries for these regions, such as petrochemistry and engineering. In 2018, the noted trends continued, while in Sverdlovsk and Chelyabinsk oblasts the spatial effects (calculated based on a single innovation activity factor) were not discovered. Legislative and executive authorities can use the research findings for shaping and updating drafts of State programs and strategies of spatial development of the entities of the Russian Federation.