The northern territories of Russia need high-quality strategic digital changes in the structure of the regional economy. Digitalization and the introduction of digital technologies in the medium term will be able to transform economic relations in the old industrial and raw materials regions of the North, improve the quality of life of local communities. The growth of digital inequality among the regions under study leads to disproportions in their socio-economic development. The purpose of this study is to develop and test a methodology for assessing the level of development of the digital infrastructure of the Russian northern regions, including classification of an indicators system for each level of digital infrastructure, calculation of an integral index and typology of the territories under study. The objects of the study were 13 northern regions of the Russian Federation, the entire territory of which is classified as regions of the Extreme North and equivalent areas. The methodology made it possible to determine the level of technical, technological and personnel readiness of the northern regions for digitalization, to identify regions with the best solutions at each level of digital infrastructure development. The analysis of the results in dynamics helped to assess the effectiveness of regional policy for managing digitalization processes. As a result, the authors came to the conclusion that increasing the competitiveness of northern regions in the era of rapid digitalization is possible through investments in human capital and the creation of a network of scientific and technological clusters. The presented approach to assessing the development of individual levels and elements of digital infrastructure will allow for the diagnosis of priority needs of territories under study in the field of digitalization. The results of the study can form the basis for regional policy in the field of sustainable digital development of Russia.

The holding of soccer events has an important impact on modern urban activities, which is conducive to the economic development, social harmony, cultural integration and regional integration of cities. However, massive energy is consumed during the event preparation and infrastructure construction, resulting in an increase in the city’s carbon emissions. For the sustainable development of cities, it is important to explore the theoretical mechanism and practical effectiveness of the relationship between soccer events and urban carbon emissions, and to adopt appropriate policy management measures to control carbon emissions of soccer events. With the development of green technology, digitalization, and public transportation, the preparation and management methods of soccer events are diversified, and the possibility of carbon reduction of the event is further increased. This paper selects 17 cities in China from 2011 to 2019 and explores the complex impact of soccer events on urban carbon emissions by using green technology innovation, digitalization level and public transportation as threshold variables. The results show that: (1) Hosting soccer events increases carbon emissions with an impact coefficient of 0.021; (2) There is a negative single-threshold effect of green innovation technology, digitalization level and public transportation on the impact of soccer events on carbon emissions, with the impact coefficients of soccer events decreasing by 0.008, 0.01 and 0.06, respectively, when the threshold variable crosses the threshold. These findings will enhance the attention of city managers to the management of carbon emissions from soccer events and provide guidance for reducing carbon emissions from soccer events through green technology innovation, digital means and optimization of public transportation.

The purpose of the work is to study the transformation processes of constructing professional identity under the influence of new information technologies and to consider the evolution of views on the processes of scientific and practical understanding of new media resources in the context of the development of convergent journalism as a phenomenon of the modern information society. It was established based on the conducted research that the values and beliefs of journalists, reflecting the process of professional self-identification, are forming in the process of choosing certain options among a variety of alternatives and transforming further under the current conditions of the information and communication environment. In the process of the study, the article identifies the features, content, and main trends in the transformational processes of professional identity and professional culture of journalists in the context of technological changes in the media industry. The dynamics of the development of media convergence are shown from the point of view of the mutual influence of traditional and new media and the tendency of improving their technological and dialogue features and capabilities in content creation and broadcasting. An assessment is made of the degree of adaptation of regional media to modern conditions of the information and communication environment in the context of organizational, professional, and communicative convergence.

This paper discusses the use of workforce ecosystems to manage human intellectual capital. The need for work ecosystems has emerged in the digital age because of the rapid growth in the number of engaged partners and freelancers in the digitalization of enterprises. It is shown that this growth is directly related to the use of agile management systems in design and development: agile, DevOps, microservice architecture, turquoise practices, etc. The information systems needed to manage workforce ecosystems should have competency-based metrics to link business needs, recruitment and training, and finding new partners. At the same time, training should be prioritized over recruitment and the search for new partners in the context of staff shortages. When automating workforce ecosystems, a platform approach should be used to integrate both corporate HR, time and business process management systems, and similar systems from partners.

More and more scholars are paying attention to the economic and environmental responsibilities undertaken by firms. Firm sustainability has become a hot topic in current research. This article aims to analyze the impact of various dimensions of digital green technology innovation on firm sustainability. The “digital green technology innovation” in this research is a new variable explored based on previous research, and the five dimensions of the variable are created based on the POLE theory. This research uses authoritative Chinese databases to collect data on various dimensions of digital green technology innovation and sustainable development of companies, and uses a fixed effects model for regression analysis. The results indicate that the implementation of various dimensions of digital green technology innovation will promote the firm sustainability. Moreover, in firms with strong profitability, this performance is significantly better than in those with weak profitability.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.