Digital Transformation in Industry

A digital twin is one of the most important technological concepts within Industry 4.0. The term is often used in current research and practice on industrial transformation. The article determines the place of a digital twin, highlights its most important characteristics, the technologies used, and evaluates the possibilities of application and effects for the industry. In the author’s opinion, it is important to assess the twin maturity, which allows separating this concept from the means of industrial automation. The complexity studying this object predetermines the need to use the methodology of collecting fragmented data, systematization of scientists’ opinions, and analysis of practical experience. The author identified definitions of the digital twin concept and formulated the necessary features of a digital twin, including a virtual multidisciplinary model of the object, automatic and bi-directional data exchange, and intelligent control capabilities. Maturity criteria were proposed for classifying digital twins; the key digital technologies were distributed on a maturity scale. In terms of the use of a digital twin in industry, the author proposed the structure of the main economic effects in improving the quality of business processes, creating a product, and implementing industrial innovation. An important area of further research is to analyze the economic security of the use of digital twins and data, as well as address the problem of information overload.

Digital twins are a key pillar of the ongoing industrial revolution requiring a strategy tailored for each sector of the economy. However, contributions addressing the sectoral level of analysis are still nascent in the digital twin literature. This paper has a dual research objective of (1) identifying the digital twin potential at a sectoral level of analysis and (2) investigating whether the existent Enterprise Architectures (EA) approaches and languages meet the requirements for the creation of digital twin architectures. A design science research project was conducted in a leading business association representing the Refrigeration and Air Conditioning Sector (RACS). Our findings reveal that RACS digital twins will need to address the grand challenges of climate change and sustainability. Moreover, the digital twin-driven transformation of RACS will be more effective in cooperation between different supply chain segments, increasing the importance of business associations’ role in the definition of reference architectures for their sector. Our results also extend recent research suggesting the use of ArchiMate language for digital twin developments. This contribution is relevant to sectoral digital transformations supported by digital twin technology, providing the foundations for future sectoral enterprise architecture frameworks.

Today, the issue of digitalization can be called the most relevant. Reengineering of business processes and progress in the field of information technology correlate with the relevance of creating innovations in the system between equipment and a human. The focus of attention is payed on the concept of a data transmission network—Internet of Things, technologically equipped physical objects for interacting with each other or with the external environment. One of the most promising new information technologies is the concept of digital twins. With the simulation of production processes using the digital twin concept, it becomes possible to monitor and identify potential failures even before they occur. The active formation of this system by extensive software and hardware complexes and the integration of their solutions are in demand and relevant tools for digitalization of the country's economy and, in particular, the aviation sector. In this article, the authors analyzed various indicators of the state programs of the Russia in the field of digitalization of the aviation industry, mainly representing the results of the involvement of integrated information systems in the activities of enterprises, as well as the impact of digital twins on the efficiency of technological processes.

The energy sector today is undergoing the digital revolution. The Internet of Things (IoT) and its subset, the Internet of Energy (IoE), that comprise, for example, smart meters, artificial intelligence (AI), or virtual reality (VR) with their practical application to the energy sector all together contribute to the enhancement of the smart energy grids of the future. Our paper focuses on the overview of the digital twins’ technology that are increasingly used in the smart grids. We discuss their application and usefulness for the improvement of the safety, security and reliability of the energy networks that include a two-way flow of information and power. Furthermore, we examine various types of digital twins and show use cases related to design, operation, control and safety of systems, testing, regulation, operator training and maintenance planning for energy utilities. Our research provides some innovative examples that might become the inspiration for the policy-makers and stakeholders working in the field of energy economics and policy.

The most important factor in the systemic transformation of the productive sector of the economy is modern information and communication technologies, among which technologies for the formation of digital twins are becoming increasingly important. The article is devoted to studying the application of these technologies in metallurgy, one of the basic industries of the Russian economy. The article aims to identify the existing prerequisites and the most significant limitations of introducing digital twins in Russian metallurgy. The study hypothesizes that the technological level of modern metallurgy allows the use of digital twins as an effective tool of the modern organization of metallurgical production. The information base of the study was the indicators of state programs and industry strategies, industrial statistics data, materials of analytical and consulting firms. The methodological basis of the study consisted of the scientific works on digital and sectoral economics. The use of comparative, structural-logical, and statistical analysis allowed identifying the prerequisites for introducing digital twins in Russian metallurgy and substantiating the validity of considering modern metallurgy as a promising object of digital transformation. The emerging trend of metallurgical production intellectualization has been established. The authors have carried out a review of the best practices of the largest Russian metallurgical companies on the use of digital twins. The study reveals the limitations of the development and application of digital twin technologies in metallurgy. In the research process, it is substantiated that to implement the existing prerequisites for introducing digital twins in Russian metallurgy and removing the identified limitations, it is required to develop special measures to improve the legal and managerial support of this activity.

The paper discusses the possibility of calculating the reaction of the environment in the form of incoming resource flows to the actions of the company using a comprehensive mathematical model of a social system functioning in an active environment. The study focuses on calculating the expected trajectory of the company’s movement for management and the marketing activities. The developed theoretical base allowed us to create an agent-based simulation model of a social system that was applied to compute the dynamics of the system. It can be used to create decision support systems for enterprises’ managers of any scale and area of activity, since the specifics of a particular system is considered by combining the values of phase variables. The novelty lies in the fact that the research shows the possibility to calculate the environment’s reaction, the mechanism for considering the cumulative activeness of agents, as well as the mechanism for converting messages that are invariants of the socio-economic space into information affecting of agents’ behavior. The result of the calculation can be recorded in the digital twin of the social system and used to automate company management.

The article focuses on the issues related to the networking in the platform development of ecosystems based on the analysis of the experimental transformation of network structures in governance following the principles of the new systemic approach. The problem of networking is setting on the basis of platforms and varieties of the organizational structures according to the type of governance. The platform basis of the network structures development in governance has been rationalized from the methodological perspective and exemplified by such kinds of networks as distribution, franchise and outsourcing. The network structures are characterized by efficient performance and appeal for the potential participants willing to be integrated, which explains their expansion and popularity. The digitalization gives new opportunities to the companies which make for the use of the innovative forms of production, consumption and exchange via digital cooperation. New digital structures eliminate barriers between the industries, create potential for cross-functional products and service development. The results of the networking in the platform development of ecosystems confirm the experimental nature of the transformation in the network structures in governance, which makes the ground for further elaboration of the methodology applied for the systemic analysis in the ecosystems’ economy development.

The economic, social, and technological processes accompanying Industry 4.0 and leading to revolutionary changes in society have led to a sharp decrease in the effectiveness of organizational forms of the previous decades. New conditions and the operating environment of enterprises in the industrial segment of the economy, coupled with new technological capabilities, initiate the emergence of new forms of organizations. Methods of scientometric and content analysis were used in the paper to prove that digital ecosystems occupy an important place among such forms. The paper presents a comparative analysis of three core approaches to conceptualizing the category “digital ecosystem”. An analysis of the thematic literature was carried out based on the study of the “Web of Science” database. As a result, it was revealed that most of the research is devoted to the technological component of digital ecosystems. At the same time, the establishment of effective digital ecosystems requires the disclosure of their economic and organizational aspects. The paper defines the main criteria and areas of activity for building a digital ecosystem of an industrial enterprise. It enabled us to give examples of measures of supporting and stimulating industrial digitalization through the transition to digital ecosystems.

The paper briefly reveals the theoretical background of digital platforms in industry, identifies the types of platforms and their features. Challenging the dominant mode of digital platform studies that presume a global example, this paper purposely situates the platforms in regional terms. It confirmed the architecture and functionality of the digital platform in an industrial region. The Urals, the largest industrial territory of Russia, was studied as a research polygon. The purpose of the study was to prove the necessity of creating such a regional digital platform. The authors identified the prerequisites for the platform—geographical proximity of producers and buyers, a significant share of intra-regional trade, common institutional conditions. The paper presents the results of a strategic session with key stakeholders—regional authorities, industrial enterprises, R&D and investors. The authors systematized the stakeholders’ requests in order to offer the functionality of the digital platform. Currently, the project of the Urals’ industry digital platform (UIDP) is in the stage of public discussion.

Management of territorial development is a complex and extremely important process that requires advanced technological solutions and efficient methods of regulating socio-economic systems. The digital twin technology holds enormous potential in this respect although some of its possibilities still remain unexplored and unexploited. This study aims to identify and describe the characteristics of the digital twin of a territory. To this end, the research literature on this problem is analyzed and systematized. A special emphasis is made on the theoretical foundations underlying the concept of digital twin and its main interpretations. The study also discusses the use of digital twins for territorial (urban) development and the features that distinguish city digital twins from their industrial counterparts. The idea of a digital twin of a territory, like digital twins in other spheres, is based on representing a real object (system) in a virtual environment. This virtual replica is created and constantly updated through automated collection and processing of massive amounts of data. Importantly, there should be a two-way flow of data between the real and virtual space. In the case of city projects, however, changes in the virtual environment do not provoke direct responses from its real-life counterpart. Some adjustments in the physical object may, occur, however, if local governments take into account the results of digital twin simulations in their decision-making. Digital twins of territories are sophisticated constructions, elaborated within the interdisciplinary frameworks, and open to the public. These projects are usually highly dependent on socio-economic processes and the degree of civic engagement.

The digitalisation of industry is an urgent aspect to develop regional economic systems, which involves introducing state-of-the art information and communication technologies into the activities of enterprises. Digital transformation is accompanied by a corresponding transformation of the structure of interregional interactions, influencing the depth and degree of regional differentiation, as well as the competitiveness of individual constituent entities of the Russian Federation. In this article, the authors assess the impact of digitalisation on the development of regions of the Russian Federation by determining the depth of digital transformation and the unevenness of digitalisation processes among the constituent entities of the Russian Federation. The purpose of the research is to study the digital transformation processes in a territorial context taking into account its impact on territorial differentiation and the cyclical nature of economic development. As a result of the research, the authors determined that in most constituent entities of the Russian Federation, the second stage of digital transformation is being implemented, while the country’s territory is highly differentiated in terms of digitalisation performance. The authors have proposed several possible scenarios for the implementation of digital transformation processes in Russian regions.

The economic and industrial transformation is currently determined by the success of scientific and technological progress in such knowledge fields as information technology, biotechnology, nano- and microelectronics, robotics, etc. It is worth noting that technology does not develop in isolation. The convergence of technologies leads to a mutual reinforcement of their effectiveness and expands their scope of application. The formation of cross-links between industries and the use of advanced technology by enterprises impacts the industry's structure and the entire economic system. The article deals with cross-industrial innovation as one of the drivers of economic development and a factor in transforming the economic structure. The article deals with the technological transformation of national EU economies in the context of growing global trends of digitalization and green economy. A review of the technological transformation of developed countries’ economies seems appropriate in terms of the continuity of best practices of technological modernization of the economy. Trends in the use of advanced technologies in various economic sectors are analyzed, using the example of EU countries, which can be adapted to emerging markets. The dynamics and structure of using such advanced technologies as new materials, robots, micro-and nanoelectronics, and industrial biotechnology were analyzed. As a result of the study, it is shown that today's competitive technology is the product of a non-linear innovation process. It is concluded that the effective cross-industrial relations of EU enterprises are formed under the development of the cluster form of interaction.

The Portuguese government, through its program for Industry 4.0, Portugal I4.0, has been supporting projects aimed at the digital transformation of the economy by mobilizing European funds and governmental subsidies from the Portugal 2020 Program. The objective of this study is to analyze the best regional practices for digital transformation in the industry 4.0 in this context. The following research questions arise: which are the best practices for digital transformation in Portugal under this Program and what was the impact on the competitiveness of Portuguese industries after the implementation of these technologies through the Incentive Value from 2017 to 2019? The methodological approach is correlational, and it establishes a relationship between the I4.0 Incentive Value and Competitiveness in order to identify the best regional practices for digital trans-formation in the Portuguese industry. The hypothesis of this study is accepted for the period 2017–2019, since the factors that make up the industry 4.0—European Fund—Incentive Value dimension are associated to the degree of competitive-ness, which was measured by a set of related variables. Further studies are necessary for longer periods and with a broader scope, the result shows the relevance of the Program.

Digital transformation (Industry 4.0) is characterized by the large-scale coupling of technologies in industrial production, high operating activities based on cyber-physical systems, and the introduction of digital technologies in business processes, which have already proven their effectiveness in world practice. The study aims to assess structural changes in the industrial complex of Russia in the digital economy. New technologies used in industry are identified as a result of the study based on the concept of Industry 4.0. The analysis of the introduction dynamics of digital technologies in the industrial complex of Russia, which involves the intensification of innovative long-term development, is carried out. The authors present a theoretical model of digitalization of the industrial complex, based on a set of interrelated components from the beginning of the digital design and modeling technology development to further production, through networks of industrial cooperation and subcontracting, including logistics, sales, and subsequent service of digital services, IT services, industrial things from the Internet.

The evolution of digital technologies places companies in front of an expected paradigm shift that allows manufacturing companies to achieve greater interconnection and cooperation between their resources and customers. The aim of this study is to quantify the diffusion of Industry 4.0 technologies in Italy and offering through the use of Strengths Weaknesses Opportunities Threats (SWOT) matrix an assessment of the Italian context in the 4.0 era. This study is based on the processing of data from a survey conducted by the Monitoring Economy Territory (MET). The survey took place between October 2017 and February 2018, and was aimed at quantifying the diffusion of the enabling technologies of Industry 4.0 in Italy. The sample consists of 23,700 companies. The introduction of systems whose implementation is the result of great technological innovations represents a huge opportunity for companies willing to adopt them, which accept to take the risks that being a precursor in this area entails. The costs associated with investments in new technologies are considerable but, if they were to be integrated intelligently, they would allow companies to obtain a huge competitive advantage over competitors who had to introduce the innovations in their production plant at a later time.

Digital technology is widely used in related industries of the national economy and has become a new driving force for economic development. This paper takes 5G as an example to discuss the integration development of the digital economy. As a new type of communication technology, 5G is playing an increasingly important role in modern society. At present, more and more industry fields have developed and used 5G technology. The competition of 5G is not only competition in the communications field but also competition between industries and economies, between countries and regions. It is also a good opportunity to open up various industries and enter the information revolution. The 5G technology will completely change the current operating mode of many industries and bring greater convenience to people. Compared with traditional communication technology, 5G technology has outstanding features in all aspects, such as new network architecture, flexible spectrum sharing technology, fast transmission speed, strong transmission stability, and short delay.

One of the effects of the last Spanish real estate bubble is the combination of an expansive growth of urban areas with a reduction in their density. This has left the municipal corporations that own the public spaces, facilities and infrastructures, mainly green areas and roads, with a legacy that influences and limits their management capacity, due to their duty of conservation and their high operating cost. Given the current situation of the electricity market and the increasingly demanding environmental regulations, the tendency of public administrations is to find a solution to the high emissions of greenhouse gases (GHG) and light pollution, which in turn can reduce maintenance costs and electricity bills. Due to the great potential of LED technologies and electronic equipment for their regulating capacity, telemanagement and long lifespan, a digital transformation of the public lighting of a couple of urban areas in a small coastal city in southern Spain is performed. First, the implementation of measures to remotely manage them for decreasing energy consumption and pollution levels is analyzed. Then, the amortization of necessary investments is studied. Next, compliance with current legislation is justified. Finally, the feasibility and profitability of actions proposed is successfully assessed.

The research analyzes the potential sustainable benefits and barriers to the implementation of Additive Manufacturing in the wood-furniture industry, trying to identify the gaps in perception between “traditional” and “3D companies”, and also to predict which are the main factors that could lead companies to its implementation. It has been administered a questionnaire in 2017, on a sample of 2035 Italian companies in the wood-furniture industry, using simple random sampling, obtaining 234 participants. The Analysis of Variance and binary regression were used to evaluate data collected. The research highlighted how Italian 3D companies are interested for new products and product features showing a propensity to innovation and putting design and made in Italy in the first place. The results underline that the main advantages of using 3D printing are the reduction in time to define technical specifications of products, in time for prototyping and production. For the successful implementation of AM technologies, the decision to adopt them has to be accompanied by a change in jobs and tasks, and thus a change in work practices and structure. The experimental techniques used is the added value of this study: no previous quantitative analysis has been realized on a large sample of furniture companies.

In the era of Industry 4.0, the digital economy is reshaping at an unprecedented rate. Facing the historical opportunities and major challenges brought about by digitizing, industrial enterprises should actively adjust their strategic planning and prepare for corresponding management changes. The article uses the general scientific research methods, such as literature survey, analysis, and synthesis. Through the study of a large number of literature and the analysis of the existing typical cases, the components of the company’s digital strategy are extracted, and the company’s marketing and production are adjusted. Organization, R&D and other management models put forward a digital innovation strategy for the enterprise. Finally, based on the international environment of the world economy’s digital transformation, the countermeasures of industrial enterprises are proposed in order to provide references for enterprises to realize technological transformation, management integration, business model reconstruction, and carry out digital strategic management innovation.

In modern times, increasingly prominent economic, social, and environmental issues threaten the sustainable development of human society while sustainable development has become the common vision and expectation of all humankind. If a company or enterprise wants to maintain its strong core competitiveness and achieve high-quality development, it should embed the mindset of sustainable development into all aspects of management and operation. Through summarizing and combining existing research results, this paper constructs a circular business model framework used to describe the sustainability of a company’s existing business model. The proposed model is based on the integration of the principle of the sustainability triple bottom line and business model innovation so as to evaluate the sustainable development potential and level of the entire industry.

Small and medium-sized enterprises (SMEs) play a fundamental role in the economy of a society. About 90% of the world's economy is made up of small and medium enterprises, which employ about 60–70% of the workforce and generate 55% of the world's Gross Domestic Product (GDP). Despite the important role they play in society, they have been slow to adapt to new technologies and innovation strategies, and in some cases these strategies are even non-existent. This fact has had a negative impact on both economic growth and the performance of these companies. Currently, digitalization and open innovation are two essential strategies for the growth of companies. On the one hand, digitalization aims to increase productivity and efficiency, and on the other hand, open innovation aims to meet the needs of customers more efficiently. Despite the many benefits, these strategies have not been adopted at the desired pace and doubts remain about how they should be applied in SMEs. In this sense, this work aims to investigate the impact of digitalization and open innovation on SMEs’ objectives and develop a model to evaluate the impact of their implementation and support decision making. To this end, a literature review was conducted to identify the strengths, weaknesses, opportunities and threats (SWOT) related to SMEs, digitalization and open innovation. A correlation was then made between SWOTs to identify risk factors that undermine the fundamental objectives of SMEs. This correlation was modeled to define a risk assessment and risk management framework that promotes the implementation of digitization and open innovation in SMEs.

The digital transformation of industry is an objective trend in recent years and a necessary condition for the economic growth of the Russian economy in modern global conditions. However, enterprises of different industries and different sizes have their own characteristics that affect the speed of implementation of digital technologies. Also, this speed is influenced by measures of state policy to support digitalization, which should take into account these features. The aim of the work is to identify the features of digitalization processes at large, medium and small industrial enterprises and to analyze measures of state support for the digital transformation of industrial enterprises in Russia. The article highlights the features of digitalization of enterprises of various sizes, and the predominant types of digital technologies used in the practice of large, medium and small industrial enterprises in Russia and developed countries. We systematize state policy measures aimed at digitalizing the Russian industry, and highlight measures of small and medium-sized enterprises support. The study identifies the external and internal barriers to the digital transformation of industrial enterprises, and offers recommendations for improving measures to support the digital transformation of industry.

The increasing networking of machines and systems in the course of the Internet of Things is changing products, companies, and competitive boundaries. The commoditization of hardware is forcing traditionally product-driven companies to develop digital services and software solutions in order to continue to secure unique selling propositions and competitive advantages. Although many companies have successfully advanced the digitalization of their product portfolios, very few market players also manage to integrate the new solutions profitably and competitively into their business models. New types of performance and services can no longer be forced into the classic business model of pure product sales but require dedicated business models. To help companies break out of their comfort zone, this article deals with the development of a structured procedure for working out business model innovations. For this purpose, business model patterns, which account for 90% of all business model innovations, are taken as a basis and methodically selected. In so doing, a structural approach to business model innovation is developed.

The paper reviews the software tools for visual system analysis of complex production systems in the context of digital industry transformation. The main trends in the visual modeling development of complex systems and the problems of their implementation are outlined. The groups of tools for visual system analysis of complex systems are heterogeneous. There are diagrammatic, iconic, and parametric visual models. The analyzed tools differ in the depth of coverage of the studied processes, their detailing, and the integration of blocks of different levels of expertise into one model. Based on the results of a comparative analysis of individual classes of visual modeling tools, recommendations for their use are given. The market analysis of visual instruments is based on the Interest Index. According to the data, in Russia, there is a growing interest in solutions that focus on the modeling of active systems and opportunities to integrate the modeling of business processes with the modeling of information system components. One of the major trends in the development and implementation of modern visual business process modeling solutions is the use of simulation modeling as an integral component. Based on this, it is concluded that the visual model of the business process in digital transformation should be considered a digital twin. The analysis of the dynamics of the Interest Index allows stating the prevalence of ARIS-based tool solutions in the market. UML-based solutions in demand increased their share, but not significantly, indicating the conservatism and a certain constancy of the potential group of its users.

With the advancement of digital technologies, supply chain management is changing dramatically. However, the practice and application of digital supply chains are complex and challenging. Some studies claim that technology is the core element, while others believe that efficient configuration and collaboration of technical functions assure successful applications. To address this gap, this research conducts a systematic literature review to analyze how digital technologies particularly the Internet of Things (IoT) and Artificial Intelligence (AI) impact supply chain efficiency in Manufacturing Industry. The study also identifies some challenges of digital supply chain (DSC) implementation. Analysis of this study is based on a systematic literature review of 59 studies that were selected using a combination of relevant keywords and specified inclusion and exclusion criteria. The results show that both IoT and AI are the closest technologies related to the autonomy and predictive power of future supply chain expectations. The convergence of the two tech-nologies optimizes all aspects of manufacturing and opens up more possibili-ties for smart factories. This research also explored DSC challenges and problems that take into consideration to expand the approaches to DSC success factors derived from existing literature. Many papers have discussed DSC technology from the perspective of the ap-plication. They demonstrate the positive impact of those digital technologies to successfully achieve digital and intelligent supply chains on firm perfor-mance by improving the efficiency of SCM.

Although the essence and content of chain management concepts by values, demands, and supplies are worked out sufficiently, the problem of their hierarchy and relationships is not solved yet. The article aims to substantiate the options, clarify the structure, and develop the methodology for digitalizing value chain management objects. System analysis, grouping, and classification methods are used as research methods. The article substantiates the value chain management options based on the choice, adaptation, and creation of products and/or services. The management structure of this type is developed, including chain management of formalization, demands, supplies, and consumption. The classification of values is clarified, including the desired value, value prototype, value carrier, and perceived value. The main value types of chain management objects are proposed. The cipher structure of chain management objects is developed, which contains information about the management stage, objects types, stages and options of creating value, forms, and options for solving problems in value chains. The obtained results make it possible to more fully take into account the demands of end consumers; reduce the loss of lost profits when making management decisions; more effectively distribute resources, powers, and responsibilities in chain links.

With the rapid proliferation of the use of artificial intelligence (AI) in organizations over the last decade, certain concerns arise regarding human rights, data security, privacy or other ethical issues that could be at stake due to the uncontrolled use of AI. However, concerns regarding transparency in the use of AI are not yet reflected in any standards for the disclosure of non-financial information, nor in current regulations. Voluntary disclosure of AI, being a novelty, is scarce, implies a lack of standardization and is limited above all to the financial, technology and telecommunications sectors. Therefore, the main objective of this paper is to seek consensus and to propose a set of relevant elements to structure the information on the use of AI by companies, to improve transparency, mitigate risks and demonstrate a real responsibility in its use. For the purposes of this study, a set of disclosure elements had been proposed based on multi stakeholder approach with the collaboration between the New Technologies Commission of AECA and the BIDA Observatory. The final proposal has been validated by online questionnaires and includes a guide to the general information elements (AI governance model; Ethics and responsibility; Strategy) as well as more specific disclosure requirements for each medium–high risk automated decision making (ADM) systems. Thus, this research attempts to contextualize the development of artificial intelligence reporting standards.

The relevance of the paper is due to the digitalization of the economy and the introduction of artificial intelligence in production processes. This paper attempts to assess the effectiveness of artificial intelligence for the automation of production. Thus, the purpose of the work is to evaluate the effect of the introduction of artificial intelligence into automated process control systems. For this, an algorithm for implementing artificial intelligence was developed, i.e., procedures and their sequence were identified when implementing artificial intelligence in automated process control systems. The following procedures were considered: selection of implemented artificial intelligence functions, selection of an artificial intelligence system, selection of hardware implementation and acquisition of artificial intelligence, formation of tests for artificial intelligence training, implementation of artificial intelligence, and evaluation of results of implementing artificial intelligence. When implementing artificial intelligence, one should choose artificial intelligence based on neural networks with deep learning. The ambiguity of the cost estimate existed when selecting hardware due to the lack of data from developed artificial intelligence versions. This complicates the definition of capital expenditures. A formula for calculating costs of implementing artificial intelligence costs in automated process control systems is proposed. The introduction of artificial intelligence into an automated process control system will not provide significant savings. Such conclusions are drawn on the basis of the calculation method.

In today’s unpredictable and disruptive business landscape organizations face challenges that severely threatens their existence. To efficiently respond such challenges organizations must craft strategies to become more data-informed, agile, adaptative, and flexible. Integrating dynamic data analytical models in organizational structures to collect, analyze and interpret business data, is critical to organizations because it enables them to make more data-informed decisions and reduce bias in decision-making. In this work is illustrated the integration of a heuristic project risk-model used to identify project critical success factors into a typical organizational business intelligence architecture. The proposed integration enables organizations to efficiently and in a timely manner identify project collaborative risks by addressing people, environment, and tools, and generate actionable project-related knowledge that helps organizations to efficiently respond business challenges and achieve sustainable competitive advantages.

Modern information and communication technologies are the essential factors in the transformation of the industrial sector of the Russian economy. The purpose of the article is to assess the impact of digital change on labor productivity in the industrial regions of Russia. We hypothesize that in the new reality the digital transformation of industry is becoming an independent factor in labor productivity growth. Scientific works of Russian and foreign researchers in the field of the digital economy, the efficiency of industrial production, factors in labor productivity growth constitute the methodological basis of the study. The authors use the methods of structural-logical and statistical analysis, as well as linear regression modelling. The information base included data from industrial and regional statistics, indicators of government programs and sectoral strategies. The paper reviews modern research in labor productivity and total factor productivity and determines the differentiation of regions and federal districts of Russia in terms of labor productivity. Furthermore, the authors clarify the set of indicators characterizing the total factor productivity, analyze indicators of industrial regions’ digital development and digital expansion. Finally, the study establishes a statistically significant relationship between the most critical hands of industry digitalization in the regions and the level of labor productivity. The study shows that the high rates of digital transformation of industry in modern conditions can solve such fundamental problems as increasing labor productivity and improving the population’s well-being.

Human resources have proven to be a determining factor in the implementation of Industry 4.0. This is because the digital transformation of society critically depends on mental attitudes, behavioral patterns, motivational attitudes, the specifics of different generations, and the qualification and competence of people. In light of this, research shows the mutual influence of Industry 4.0 and human resource development. It has been proven that demographic trends, as well as technological trends in conjunction with trends in the transformation of the labor market under the influence of digitalization, have a significant impact on the search for approaches and methods of human resource development adequate for new conditions. This paper substantiates the importance of taking into account the differentiation of generations to create a new digital reality and adapt to it. Based on the identification of key factors of human resource development, the study identifies methods and development techniques of human resources in the context of Industry 4.0 at the organizational level.

The purpose of the article is to study the transformation of the personnel system in the context of Industry 4.0. The economic and social consequences of Industry 4.0 determined the research methods—historical, critical and comparative analysis. The authors concluded that there is a discrepancy between the training system of IT personnel and the requirements of “digital” workplaces. The study revealed that during the transition to Industry 4.0, the requirements for employee competencies are changing revolutionarily, as well as new forms of connections between demand from new industries and supply from educational and personnel institutions are emerging. The authors proposed a classification of these forms of connections.

Digitalization has a global trend and has become a driver of competitiveness in the enterprise sector. The pandemic has forced governments and businesses around the globe to accelerate the transition to digital technologies. Due to those grand challenges, the labor market landscape and human resources policy priorities have undergone significant changes. New jobs, methods, and innovative practices have appeared under the influence of digitalization. In this research, we test how to apply large datasets of full-text documents (more than 1 million patents and Ph.D. theses) to find possible directions for transformation of working conditions and job-related changes. We have identified promising directions in terms of research and development and economy, which grew in 2020: agriculture machinery, pharmacology, diagnostic tools, logistics, and wireless technologies. Moreover, under those directions we have found some research and production centers, which we can consider potential producers and labour consumers. Russian federal and regional authorities might use results of our research to form personnel policies of regions and federal districts.