Digital Transformation in Industry

Industry 4.0 is a trendy concept that everyone is talking about. However, there are several concepts and technologies attached to Industry 4.0. The concept is considered as the most recent industrial revolution and takes us to the domains of automation, digitalization, information, etc. The concept is gaining in popularity, but sometimes firms and employees are not able to follow new trends. The paper summarizes a research on the concepts of Industry 4.0 and 9 technologies commonly associated with the Industry 4.0 umbrella. Most of the literature recognizes it as something that can bring several benefits to firms. However, it is also pointed out that the adoption of these technologies relies on several factors. The current study focuses on the human factors. A group of 260 respondents participated in a questionnaire and were asked about their perceptions of Industry 4.0 and its technologies. The main purpose was to find different responses to Industry 4.0 technologies, according to age, education level, gender or field of studies. In general, all the individuals present a similar approach. The Main differences were found on Big Data, Augmented Reality and Simulation technologies.

The latest technological and globalization trends have entailed a sharp increase in various regulatory functions, which enhances the content and significance of state industrial policy. Amid these conditions, it is becoming increasingly important to identify the key features of a new reality that determine the necessity for industrial policy to be adjusted under digital transformation. We hypothesize that the transformation of the priorities, goals and economic content of industrial policy is due to a new reality affected by changing core factors of technological development, the influence of recent globalization trends, and the growing importance of human capital. The fourth industrial revolution, globalization and human capital are believed to be the major drivers of today’s economic development, despite the differences in their institutional nature. Their combined impact provides a new direction for the development of industrial policy and encourages the formation of a system of public instruments for supporting priority industrial areas. The driving force of today’s economy is not only technology or the production sector, but also sophisticated organizational-economic models and advanced mechanisms for coordinating manufacturers based on a cross-platform network business model. Addressing the experience of developed and developing countries, we demonstrate the changing importance of production factors transforming industrial policy. The study substantiates the need for a proactive industrial policy that takes into account economic and social interests.

Assessment of the value of information technology (IT) is one of the most challenging priorities for modern organizations. The topic has been studied for decades but the continuous nature of digital transformation in industry (DTI) has added a new dimension to the problem. This paper presents a framework to capture IT value over time, supporting industries in (1) monitoring the outcomes of their digital transformation and (2) evaluating the need for new investments. The framework is inspired in the literature of IT value and extended to the dynamic, integrated and boundary spanning logic of Industry 4.0. The difficulty to prove the holistic value of IT investments is an obstacle to the necessary developments in industry. Moreover, similarly to DTI, IT value assessment is multidimensional and should be the result of an ongoing evaluation supported by evidence. Our proposal offers a starting point to create new tools to assist C-level managers steer their investments and make visible the inevitability of digitalization to compete.

The article explores transformation processes of the economy and industry in the context of the digital technology introduction. It substantiates the methodological basis of the research, including the process, technological and sector-specific approaches. The study formulates the fundamental hypothesis about the possibility to integrate the three approaches and form an ecosystem based on the platform organization of the economy and industry. The authors propose a definition of the concept of digital platform, distinguish the types of digital industrial platforms and justify the effects of the platform organization of the economy.

The paper studies the issues of modeling the digital transformation of the regional industrial sector. The polystructural nature of the research object requires the use of a methodological toolkit capable of adequately simulating comprehensive socio-economic systems. To simulate the digital transformation of a regional industrial sector, an agent-based approach is applied. When developing a model, the study proposes to take into account the elements of the irrational behavior of firms when making a strategic decision on digitalization, considering the formed opinion of managers and the general level of digitalization in the region. In the author’s opinion, these factors are of a psychological nature and can be assessed using a multidisciplinary approach. As a result of developing the model, the author proposed 4 classes of agents, their parameters, strategies used, possible states, estimated assets, and liabilities. In the model, an enterprise’s choice of a digitalization strategy and an operational decision on starting digital transformation are separated. The transition to a digitalization strategy is based on the actions of other industrial enterprises and the probability of a positive decision of the CEO identified as a result of the survey. The decision to start a digitalization program is determined by a strategic decision, the current financial capabilities of a particular enterprise, and the level of subsidies for the digitalization of the industry by regional authorities. The results of the study enrich the methodological toolkit for modeling the digitalization of the industrial sector, expand the ideas about the rational choice of an enterprise’s digitalization strategy, and make it possible to use the opinions of CEOs in an agent-based model.

The paper offers a visual method for multi-factor assessment of digital transformation components of the industry. The authors consider the aspects of its application in assessing the implementation of digital information systems in the electronic industry and give recommendations for analyzing the existing business processes at an enterprise. The study proposes an approach to the implementation of the electronic digital space system in the enterprise’s information structure, which allows increasing the efficiency of enterprise management processes and simplifying the system for monitoring the state of its activities. The article briefly discussed the main factors of efficiency of introduction and modernization of the enterprise’s digital information space and shows the main difficulties of implementation and the planning principles for the transition to digital transformation in the enterprise. The authors recommend on the development of visual diagrams for multi-factor assessment of digital transformation components taking into account the needs of a particular enterprise.

The relevance of the article is associated with the increasing influence of digitalization on the development of the real sector of the economy. The paper aims to determine the key factors in the development of digital technologies at industrial enterprises and to identify, on their basis, the dependencies between these indicators, which will allow the list of key drivers of digitalization of the industrial sector in the short and medium term to be codified. The following research methods were used: the description method for analyzing the dynamics of changes in the digitalization indicators of enterprises in the real sector of the economy; correlation analysis; and regression analysis. Among the key drivers of digitalization of the real sector of the economy based on modeling, the authors have identified the following: the share of organizations using customer relationship management systems in the total number of organizations surveyed; the share of organizations that placed orders for goods (work, services) on the Internet in the total number of organizations surveyed; the share of organizations that had special software for managing the procurement of goods (works, services) in the total number of organizations surveyed.

The research is based on analysis of the scientific literature, world-class reports, analysis and processing of statistical data on the research topic. The subject of the research is the process of digitalization of industrial enterprises. The purpose of the study is to develop a model for managing digital services in order to improve the efficiency of industrial enterprises. The hypothesis is that digital services management determines the vector of competitiveness of industrial enterprises’ products. The main research methods were comparison, a systemic approach, the decomposition method, economic and mathematical modeling, and forecasting. The use of the methods allowed us to achieve new scientific results: a decomposition diagram of the process of digitalization of industrial enterprises, economic and mathematical models that reflect the contribution of digital services to the development of industry, a predictive model of the development of industrial enterprises taking into account acquisition of digital services that complement the existing approaches to assessing the effect of digitalization. Managers of industrial enterprises can take into account the presented findings when implementing the corporate development strategy along the digital transformation vector.

The complexity of production processes substantiates the need for a joint industrial activity for developing innovative products. According to the common practice, the major source of breakthrough innovative solutions is small and medium-sized enterprises (SME). The intra-corporate transfer of such solutions can significantly reduce the time needed to establish new production facilities and become a key factor in the competitive struggle in the market. The formation of SMEs cooperation networks falls within the framework of industrial cooperation research. Using the case study of Russia, we address the issue of an effective production network of cooperation between SMEs and large companies. The research sample comprised 14 enterprises distributed according to the industries dominating in the Russian economy. The data obtained show that large enterprises partially owned by the state and acting as cooperation centers are assigned a specific “anchor” role. Anchor companies tend to lower the level of production localization. However, this does not have a significant effect on increasing their financial performance and does not depend on the share of state participation. Russia’s experience clearly highlights the weakness of cooperation, albeit with trends towards positive change. In 2015–2019, there was an increase in the share of orders placed by large manufacturers with SMEs. The share of SMEs within the production chains is substantially differentiated and varies between 5.5 and 79.5% for the enterprises under consideration.

The following paper aims to explain to the reader the existing interconnection between the paradigms of sustainability and digitization. In detail, the study will focus on Smart Working, analyzing this tool for its possible improvement of the sustainable performance of companies, and its benefits on the environment, making use of the perceptions that people have about this new way of working. Through the use of a questionnaire, it has been analyzed the perception that people have about this new way of working, which has characterized their lives for about two months during the lockdown period in Italy, caused by the Covid-19 pandemic, considering the time period from 9th March to 1st June 2020. The questionnaire was developed using Google Forms, and it was administered using Computer Assisted Web Interviewing (CAWI) using social networks, primarily Facebook and LinkedIn; 352 workers participated in the survey. The results show that the sample under review is satisfied with this new way of working, both in terms of reducing expenses and increasing the time that can be dedicated to personal activities, and from the point of view of improving the environmental impact. Despite this, a state of skepticism reigns which is characteristic of great changes, since the Covid-19 pandemic we are facing, as a country and globe, forces us to change our habits established over time.

New manufacturing technology can provide useful competitive advantages for enterprises to deal with fierce competition, and help them look for a better solution to production and operation management improving the quality of product services. New technology can also promote enterprises to obtain sustained economic, social and environmental benefits. This study, therefore, focuses on investigating the impact of technology on the sustainability of supply chains in small and medium enterprises (SMEs) in the Pearl River Delta region of China. The findings are based on 100 valid survey responses from SMEs in the region. The study identifies a set of enablers and barriers to new technology implementation in manufacturing SMEs. Our findings show that the economic factors occupy the central position whereas the market pressures from home and abroad; the vision of the enterprise’s development; and the apparent advantages of new technologies were identified as other key enablers. On the contrary, the driving force from the government was found to be insufficient, whether it is a relatively free market regulatory environment or tax-free welfare policies for small businesses to promote the use of new technologies. The high production cost appears to be the most critical barrier followed by vicious competition among enterprises in the industry and lack of technical personnel. Our findings also show that enablers and barriers of new technology implementations are significantly correlated with sustainability performance measures (economic, social and environmental performance). Our study hence adds to the limited empirical literature focused on investigating the new technology and sustainability relationship.

Digitalization of management objects allows using digital technologies to improve the efficiency of enterprises as links of supply chains. It is particularly difficult to establish communications between various objects of supply chain management—flows, systems, processes, and relationships—as well as to maintain their right combination for solving tasks in the most rational way. The research aims to develop a code of combinations of management objects that can solve the above problem. The research hypothesis assumes the possibility of using a universal code formed by a set of classification features of these objects, each of which is characterized by a binary code. System analysis, grouping, and classification research methods are used. The result is a code that provides digital information processing and increases the efficiency of supply chain management. The scientific contribution is to create a methodological basis for digitalization of management objects. The research results can be used in the development and application of computer software for supply chain management.

Supply chain risks have been regarded as one of the most significant threats to business continuity. Digital technology is considered to reform human production and manufacturing methods. In the recent wake of COVID-19, disruptive digital technologies have emerged as a key tool to manage supply chain risks. Therefore, exploring the impact of digital technology on supply chain risks is considered an important topic in the supply chain management domain. The paper reviews different digital technologies such as 3D printing, IoT, Blockchains, RFID and Big Data Analytics used in supply chains. This exploratory study is based on a survey response from 176 supply chain professionals in China. The findings show the role of digital technologies in managing supply chain risks. The study highlights the current level of implementation of digital technologies in supply chain functions and emphasizes the importance of training. Moreover, the study underlines the significance of supply chain data analysis capabilities for supply chain risk management. The study adds to the limited literature exploring the importance of digital technologies in supply chain risk management.

This paper explores the information on Artificial Intelligence (AI) that Spanish IBEX 35 listed companies are including in their annual/sustainability reports. The study mainly focuses on the AI systems that companies indicate they are using or developing, the projects they are tackling and the extent to which they follow some principles or ethical guidelines when using AI-based technologies. The study analyses, both from a qualitative and quantitative perspective, the content of the reports of IBEX 35 companies for 2018 and 2019. The findings suggest that although AI reporting is growing because of the interest in these technologies, it is growing in a non-structured way, and that the adoption of ethical approaches to AI is at a very preliminary stage. The paper analyzes some evidence about a part of non-financial disclosure, AI disclosure, which has not been explored yet. It may serve as a starting point for researchers and companies interested in developing clear guidelines on what kind of information is relevant and mandatory for companies to report, what ethical principles or regulations AI applications must follow and how it has to be disclosed.

The paper aims to systematize economic effects of using artificial intelligence. The study deals with various approaches to defining the concept of artificial intelligence and identifies their major advantages and disadvantages. Having performed an in-depth analysis, the author gives a broader interpretation of the concept of artificial intelligence. The research results allow framing the concept of artificial intelligence economics, which gives a new avenue for research into the impact of artificial intelligence on the economy. The research focuses on the economic effects of artificial intelligence, discusses the prospects for the use of artificial intelligence and its impact on the global economy, and identifies the negative factors that governments and business leaders should minimize. The theoretical analysis of literature shows that the problem is gaining in popularity. At the same time, there is lack of attention to a number of methodological issues related to the modification of artificial intelligence models that require further research.

The paper aims to study the impact of systemic digitalization, reflected in the Industry 4.0 trend, on the creation of intellectual capital and value added in the regions of Russia. The methodology is based on regression analysis and comparison of statistical data to assess the regional impact of Industry 4.0-specific intellectual capital on the gross regional product and wages in Russian companies. The authors used official data from Rosstat and Higher School of Economics statistical databases on human capital and digitalization. The results of the study show that, on the one hand, digitalization in general and the components of Industry 4.0-specific intellectual capital make a moderate and significant contribution to the value added and revenue of manufacturing and service companies in Russian regions. On the other hand, the authors did not find a significant contribution of Industry 4.0 and digitalization in general to the differentiation of wages of Russian employees in comparison with traditional elements of human capital, such as education and work experience. The originality of the study lies in the fact that the authors developed a theory of Industry 4.0-specific intellectual capital, which can explain the creation of value added and returns from human capital at the level of regional enterprise ecosystems. The authors also propose models that support the assessment of the relationship between the implementation and development of such intellectual capital and the performance of companies.

The article considers cross-functional teams as an alternative to the traditional team-building approach in industrial digital transformation. Based on the contextual analysis of the reasons for creating cross-functional teams, their polyphonic nature and exclusivity signs are revealed. The paper demonstrates particular importance of knowledge sharing in cross-functional teams for efficient work. Knowledge sharing among employees serves as a source for obtaining necessary and useful information and a condition for the successful functioning of cross-functional teams. The purpose of the study was to perform a comparative analysis of the influence of organizational and managerial factors on knowledge sharing in cross-functional teams. The academic environment of two universities in Russia and Germany was used as an example to determine the obstacles and conditions of this process. In the study, two groups of employees from Russian (Ekaterinburg) and German (Brandenburg an der Havel) universities were examined. The paper determines the degree of influence of various organizational and managerial factors on the intensity of knowledge sharing in cross-functional teams under the national context.

The paper considers the possibilities for using digital technologies in talent management, presents approaches to defining the concept of talent management, and substantiates the relevance of the subject under study. The authors identify and discuss the main activities in the area of talent management. In the present research, the methods of human resource management associated with the development of digital technologies are specified: robotization, digitalization, systematization of enterprise resource planning, and neuro tools.

In the context of training in engineering and technology in the Industry 4.0 era, project competences’ acquisition must start from the trainer’s perspective as a counselor, facilitator, and sponsor of trainees’ learning. This means minimizing master classes to promote their autonomy and collaborative work, not being possible to ensure their development through traditional evaluations. In a recession context (Spain, Andalusia, and Cadiz) with low growth and high youth unemployment rate, it is intended to promote future engineers’ entrepreneurship, creativity and innovation. Within this framework, the study reviews the models that highlight the ways of teaching and learning in project management subjects in the engineering degrees of the industrial branch (chemistry, electricity, electronics, industrial design and product development, mechanics, and industrial technology) offered by the University of Cadiz (UCA). This selects project-based learning (PBL), in which learners are the main characters, who evolve through experimentation. This research consists of three stages. In a first phase, education in entrepreneurship is encouraged. Next, culture of innovative entrepreneurship is promoted, propitiating the conditions for the (simulated) creation of innovative companies. Finally, those proposals that potentially contribute to Cadiz improving its business deficit in technological sectors are selected.

The article examines the content and transformation of the project space in the digital economy. It presents a review of the state of the issue in academic sources, clarifies the content of the concept of project space in the digital economy, identifies the prerequisites for its study, and reveals its structure. The project space is considered as a specialized component of the economic space. The research results show that the formation and transformation of the project space in the digital economy require an appropriate institutional environment, system conditions, and infrastructure. The aspects considered in the paper make it possible to expand the scope of possibilities for solving an important problem for the modern economy: the formation of a theoretical and methodological basis for the study of the project space in the digital economy, increasing its role and significance in the processes of socio-economic development of regions and states.

The formation of stable and effective cluster-network connections inevitably increases with the digitalization of all socio-economic relations. The oil sector is one of the key ones in the Russian economy, affecting the determining pace and path of the state socio-economic development, and is subject to the government's greatest regulation as compared to most other industries. Oil companies in Russia are striving to take a dominant role in the global market. The international expansion allows oil companies to diversify state risks and opens up new opportunities. Amid global digitalization, the issue of optimizing big data using new approaches that could be based on classical fundamental knowledge is becoming increasingly critical. One of the methods proposed in the article for working with a broad array of regional indicators in dynamics is neural networks. The paper considers a neural network efficiency model of the cluster-network policy process in the oil sector. The analysis of classical mathematical models allows characterizing the influence of cluster-network connections on the oil and gas industry in the first approximation. The article considers the industry structure and analyzes the Volga Federal District's regions for indicators that characterize the economic state of the regions.

The study aims to identify the determinants that affect the efficiency of production processes and personnel development as a key component of modernization transformations and the dominant factor of production in Industry 4.0. To solve this problem, a strategy for developing a lean organizational structure to manage a petrochemical enterprise is modeled using the production function proposed by Cobb and Douglas. The results of the analysis show that taking into account the achievement of total indicators for the petrochemical industry as a cumulative result, the efficiency of innovation activity expressed in the calculation of the shipment of innovative products per highly productive workplace will increase from 0.7 million rubles on average per petrochemical enterprise to 1.6 million rubles by 2024. The proposed methodology can be used not only at the industry level when designing lean management structures in the petrochemical industry but also at the micro-level for individual enterprises in the industry.

A review of literature related to frozen ground engineering showed that the number of publications and datasets has been increasing in the last five years. Based on the North Siberian crude oil pipeline that crosses continuous, discontinuous, sporadic, and non-permafrost areas, an exploratory data analysis of soil condition is conducted to investigate the influence of pipelines on the freezing and thawing of frozen soil around the pipeline and thermal stability of permafrost. The contribution of the study is the hypothesis concerning the possibility of clustering water-saturated and frozen layers along with the right-of-way areas.

The digital transformation of industry poses new challenges for related industrial fields, in particular for education. Universities must transform accordingly and provide the digital economy with qualified personal. Online technologies, including online learning, play an important role in digital transformation, opening up new opportunities and posing challenges that the education system has never faced before. The problem of making justified decisions on the selection and assessment of the quality of online courses and their control materials is one of these challenges. Data mining and machine learning analytics tools that work with learners’ digital footprint data can be used to solve this problem. To do so, this work uses the methods of information theory. The indicator of the informativeness of control materials provides differentiation of standalone checkpoints and online courses in general and minimizes the subjective factor present when using existing assessment methods. Another indicator that assesses the mutual informativeness of checkpoints allows determining how much information about the final test results can be obtained by monitoring current academic performance. This indicator is applicable both to individual checkpoints and their series (assembled by type—test assignments, homework assignments, etc.; or by the chronology of the course—¼, ½, etc. of the course length). With its help, it is possible to evaluate the course checkpoints and make a decision on how to improve the course materials. In addition, this indicator can be useful for assessing the marginal accuracy of the prediction of the test results according to the current academic performance of a student. The proposed methods have been tested on online courses of the Ural Federal University with positive approbation results.

In the context of the lack of financial resources in the real sector of the economy and enterprises of various economic activities, low budgetary security of territorial systems to solve acute problems of socio-economic development and implementation of spatial strategies, bank capital becomes an important strategic resource. The wide range of investment instruments available to banks and credit institutions improves financial security economic actors, to form the financial potential of the progressive development of territorial systems. The main purpose of the work is to justify the role of the banking sector of the economy and its investment resources in shaping the financial potential of progressive socio-economic development of territorial systems. To achieve this goal, the study proposes the use of methods of statistical and multiple regression analysis on the method of the smallest squares based on panel data on subjects of the Russian Federation for the period 2008–2016, as well as methods of spatial analysis. The study found that the progressive socio-economic development of territorial systems depends not only on the volume of investment resources of enterprises of the real sector of the economy, incoming foreign direct investment, but also on investments of the banking sector of the economy in government and corporate debt securities and shares, the volume of lending to financial and non-financial institutions, households. The study showed that the banking sector has a strong investment potential, its volume of investments during the period 2008–2016 it significantly exceeded the volume of investments in the fixed capital of enterprises and the volume of foreign investment, and since 2014 it has exceeded the size of the GDP of the Russian Federation. Comparison of GRP of Russian entities and the amount of investment resources concentrated in them allowed to identify the regions where bank investments are most in demand.

The paper is devoted to the urgent problem of the growth of the regional industrial sector and the development of a methodological toolkit for assessing the level of digitalization of Russia’s regions as compared with the industrial production output. The study examines the aspects of sustainable economic development of industry, considering the development of digital technologies. The industry is a backbone sector of the economy. A drop in the level of industrial production in industrially developed regions of Russia was recorded in 2020. Given the good rates of economic growth of the country in recent years, the current crisis, which is based on non-economic reasons, poses a threat to the development of manufacturing industries. In conditions of instability, support for a digital transformation of the backbone industry of the Russian economy becomes a matter of ensuring its national security. For the progressive and uniform development of digitalization in the real sector, it is necessary to enhance innovation activity in the regional industrial sector. At the same time, the government should share the risks of introducing fundamentally new technology and high technologies with industrial enterprises. In this regard, questions arise about the value that technological innovation brings both to the industrial sector and society as a whole.