Today the process of transition to a new technological order has become evident to everyone, especially in developed countries. One of the most urgent areas for ensuring the long-term competitiveness of industrial enterprises is the development of the Arctic zone. This region has many economic and logistical difficulties, the solution of which may lie in the use of advanced technologies of the new technological order, for example, 3D-printing technologies. The aim of the article is to study the transformation of the cost structure of industrial products as a result of integration of 3D-printing technologies into the production process of industrial enterprise operating in the Arctic zone. It was found that the structure of the main cost elements varies greatly, due to the ambiguity of replacing computer numerical control (CNC) (or other classical shaping technologies) with 3D-printing technologies, as well as the specifics of supply chains, which is quite urgent for the Arctic region. The results of empirical study necessitate the development of tools for predicting the economic viability of integrating 3D-printing technologies into the technological processes of industrial enterprises operating in the Arctic zone. Within the article, the authors substantiated and developed a fuzzy-multiple model for assessing the level of investment attractiveness of integration of 3D-printing technologies into the production process of an industrial enterprise operating the Arctic zone. One of the aims of this model is to answer the question of whether an enterprise should invest in a technological transition to 3D-printing technologies.

No abstract

Today, humanity is on the verge of the fourth industrial revolution. This can result in a radical transformation of all aspects of society. Information technology is the core of the fourth industrial revolution. The application variety of modern information technologies determines the infinite vectors of their use, which ultimately become the overwhelming number of instruments for life simplifing. Professional activity sphere is also being transformed under the influence of information technology development. However, this transformation process is extremely ambiguous. In connection with this specificity, the purpose of this study is a systematic analysis of the influence of the information technology development dynamics on the transformation of the labor market. The hypothesis assumes that there is a relationship between technology development and changes in the labour market. This research examine digitalization impact on unemployment level and the process of gradual extinction of certain professions. As the results authors defined mathematical formalization of the alleged links and formulate the main vectors of labour market transformation under the digital technologies development.

The dynamics of irreversible multidimensional digitalization of production and consumption processes can be described today with a linear-positive or even exponential function. A significant part of the information background of a product, enterprise or brand is formed by their consumers, competitors or partners on the Internet, which considerably increases its accessibility and spread. Such kind of information can be called natural digital information (NDI). Its high market value is counterbalanced by its inhomogeneity and complexity for analysis. The solution to this problem lies in the field of creating automated tools for its subsequent search, aggregation, primary processing, quantification and analysis. The aim of this study is to describe the unique methodological properties of market research based on natural digital information. In order to achieve this aim, this study analyzes the theoretical basis in the field of NDI research, defines the categories of NDI and sources of its formation, describes the key properties of NDI, determines its advantages in comparison with other types of market information, and suggests a basic methodology for conducting typical NDI-based market research. An applied research study was carried out according to the designed methodology to show its advantages, as well as to describe the unique methodological properties of market research based on processing of NDI. The main result of this study is a universal algorithmic model for analyzing NDI in the context of market research, which includes a mechanism for defining and categorizing the digital sources of NDI, a model for forming the key properties of NDI, and basic classes of NDI analytical metrics. The toolkit developed by the authors allows market research to be conducted without direct attraction of research subjects, which results in cost reduction and elimination of the phenomenon of social desirability; this creates the so-called reasoned advertising messages that meet the requests of the target audience, which is proved by the big data that underlie the presented methodology. The developed algorithmic model is universal for analyzing natural digital information, and, with minor adaptations, can be used by any subject conducting market research.

The aim of the article is to investigate the impact of the new coronavirus infection on the Russian labor market and to suppose the actions to be taken to minimize negative economic consequences. The distinctiveness of this study is the differentiation of the impact of the physical and informational spread of COVID-19. The informational spread of coronavirus is measured through the dynamics of news messages related to the topic of “coronavirus” in the largest Russian media. The analysis of the average level of wages by type of economic activity, as well as the demand of employers and the number of vacancies, allow testing the hypothesis that the physical and informational spread of coronavirus caused an increase in the number of unemployed, a decrease in average wages in the studied range of economic activities, an increase in supply on the labor market, and a decrease in demand for employees. Another task of the study is to assess the dynamics of related search queries in Yandex (Russian biggest search engine), which can help to reveal the logic in the behavior of the Russian people during the pandemic as well as to understand if the Russian economy, the labor market, and society were prepared for the changes caused by the pandemic. Using a regression modeling methodology, it was found that the influence of the information environment, namely the informational spread of coronavirus, had an even greater impact on studied parameters than the physical spread. A “delay effect of physical consequences” was discovered. The conclusions obtained showed that in the conditions of wide informatization of society, it is necessary to systematically influence the physical and informational spread of coronavirus to minimize the negative consequences of the pandemic on the labor market.