The authors of the article suggest the strategy of forming a platform operating model to increase the level of digital maturity of industrial systems in the changing conditions of reality. They have analyzed the current situation on adapting industrial systems to the changing conditions of reality of 2022: the sanctions restrictions and the COVID-19 pandemic crisis. In analogy with the bionics companies concept the authors introduce the term of «bionic industrial systems» as the aggregate of economic entities which form the closed cycle of producing artificial products by machine and combine new technology with human ability of transforming operations on the basis of digital strategizing, develop the experience, customer relationships and more effective performance, increase the pace of innovation significantly. There is a conclusion that bionic industrial systems are characterized by the presence of digital strategies, high level of digital maturity which should be evaluated according to the index of digital acceleration. The authors suggest four strategies allowing transformation of industrial systems into bionic ones and maximize their value on the basis of digital strategizing. The use of platform operating model is considered to be the key distinctive feature of the bionic industrial systems. The article presents the strategy of forming a platform operating model of bionic industrial systems based on the model of digital transformation of the transactions of the Deloitte company. This is the structure describing the digital path on the basis of defining 10 evolution stages taking into account cybersecurity and digital culture. The digital industrial platform ZIIoT by the Russian IT-company «Tsifra» (Digit) has been studied as the best experience, and the authors present practical cases of its implementation in Gasprom, Lukoil, Novolipetsk Metallurgical Plant. The implementation of the strategy of forming a platform operating model in industrial systems is expected to result in reducing costs due to accelerated implementation of digital scenarios, additional income and opportunities of diversification through digital strategizing, etc. The authors introduce the concept of forming a platform operating model to increase the level of digital maturity of industrial systems.

Industry 5.0 is an integral driving force for industrial development to overcome a resurgent strategic drift. This solution is a perfect tool to ensure a sustainable, human-centered, and resilient industry and encourage man-machine collaboration within intelligent cyber-social systems. A complete shift to Industry 5.0 is only feasible when industrial systems apply digital strategizing to enhance digital development. That would invite technologies and humans to facilitate all operational and customer dealings, significantly increasing the rate of innovation. This research aims to articulate a multi-perspective conceptual framework based on the premises of digital development of industrial systems in the strategic drift to Industry 5.0. The methodology implied in this research rests on an interview with industry experts, a case study of digitalization leaders in 2021, extensive and systematic literature review and scientometric analytical tools, content analysis and foresight. In this paper, the authors reframe the concept of digital strategy and consider it as a notion independent of digitalization strategy and digital transformation strategy that is traditionally based on the formation of digital thinking, implementation of digital behavior patterns, the transformation of mindset, and strategic wisdom. As a result, a brand-new perspective on Industry 5.0 is suggested – Nooindustry 5.0. This digital development framework provides grounds for a digital business strategy to advance and shapes a platform-operating model to nurture the digital maturity of industrial systems. This research identifies key strategies for the transformation of an industrial system into a bionic one to sail through the current strategic drift. Further scientific work has to be carried out in order to assess the impact and effects of digital development of industrial systems while shifting to Industry 5.0.

The essence of the transformation processes currently taking place in all sectors of the economy, including industry, is increasingly described by the ecosystem approach. Industrial ecosystems have proven to be the models with the highest production efficiency. The effective management of industrial ecosystems is possible only if the mechanisms underlying their dynamics are understood. Achieving a high level of maturity for industrial ecosystems in the framework of digital technology implementation is of particular relevance, and this research aims to develop and test a methodology for assessing the maturity level of such industrial ecosystems by relying on principal component analysis and hierarchical agglomerative clustering. A mature industrial ecosystem gets rapidly integrated into the new technological paradigm and global value chains, is able to compete in global markets in the long term, and has increased potential for industrialization and digital transformation. The proposed methodology is based on the environmental, social, and corporate governance (ESG) methodology for determining the levels of interests in the area of sustainable development of an industrial ecosystem. The proposed approach singles out a fourth assessment projection in addition to ESG, namely the digital maturity. All four maturity assessment projections are proven to be positively and significantly correlated. An industrial ecosystem maturity assessment scale has been developed, including six levels (very high; advanced; basic; elementary; zero; and minus one). The methodology has been tested on the national industrial ecosystem and the metallurgy and mining industrial ecosystem of Russia. The results show that the maturity level of the Russian industrial ecosystem as of mid-2021 is

Purpose: the main purpose of this article is to develop a methodology for assessing the digital maturity gaps of industrial enterprises in order to adapt to the digital environment, to take advantage of digital technologies to improve operations and increase competitiveness.Methods: the authors applied general scientific methods (method of synthesis, generalization, content analysis, graphical interpretation of data). In assessing the levels of digital maturity gaps, correlated with the levels of digital maturity, the scaling method was used.Results: the global metamorphoses actualizing the problem of achieving digital maturity by industrial enterprises are described. The concepts of maturity, digital maturity, and digital maturity gaps of industrial enterprises in different sources are investigated. Digital maturity gaps are shown from two perspectives: as the difference between the current and target maturity levels of industrial enterprises; as the gap between awareness and implementation of Industry X.0 solutions in industrial enterprises. The landscape of digital maturity assessment methodologies at different levels is systematized: federal, regional and grassroots level of the economy. The problem and research gap of digital maturity assessment is identified, which is the lack of methodologies for assessing digital gaps. The author proposed a methodology for assessing the digital maturity gaps of industrial enterprises, which includes fourteen stages. The methodology was tested using data from twenty industrial enterprises that are leaders in digitalization in 2021. Visualization of digital maturity indicators and digital maturity gaps was carried out.Сonclusions and Relevance: as a result of testing the methodology for assessing the digital maturity gaps of industrial enterprises, it is concluded that the current state of development of the national industrial ecosystem is characterized by significant heterogeneity in the development of individual industries, unequal development of markets and enterprises. In order to successfully complete the digital transformation and increase the level of digital maturity to the maximum, it is recommended that industrial enterprises integrate digital platform solutions and digital behaviors based on the concept of digital strategizing into their operating model.

The article presents the results of a systematic study of Industry 6.0 which is the future stage of industrial development characterized by intelligent and technological immersive hyperconnection and physical-cognitive-emotional fusion of virtual (superior to digital) twins of humans and machines. The authors carry out a literary review synthesis of the existing defi nitions of Industry 6.0, suggest the authors’ defi nition and concept, systematize key technologies by six research projections: intelligent automation, sustainable development, human-machine interaction, information technologies and cybersecurity, machine learning, human resource management. Special attention is paid to the distinctive features of Industry 6.0 compared to Industries 4.0 and 5.0. Industry 6.0 involves the ubiquitous fusion of virtual twins of humans and machines that allows implementing ultrapersonalized production and create emotionally intelligent ecosystems, often with the help of quantum technologies. The authors discuss the opportunities of implementing Industry 6.0 in Russia basing on the national strategies on the data economics, technological sovereignty and the ‘Technet’ program of the National Technological Initiative. The limitations of the study are connected with the futuristic nature of Industry 6.0 concept, lack of suffi cient empiric base and limited amount of relevant scientifi c publications. The directions of further research may include development of practical models for the integration of intelligent ecosystems of Industry 6.0 into Russian production and technology sectors. Special attention should be paid to the development of the methods for assessment of economic and social effect from the implementation of the key technologies such as multiagent systems, quantum computing and the emotional intelligence of machines as well as to the study of the ways of their adaptation within the national strategies of technological sovereignty and the economics of data.