В статье рассматриваются подходы к применению методов искусственного интеллекта для решения задач цифровой трансформации экономики в сегменте поддержки и обеспечения традиционных бизнес-процессов промышленных предприятий, в части создания совершенно новых бизнес-моделей и идей для умного правительства. В статье раскрываются новые пути применения технологий искусственного интеллекта в цифровой экономике. Статья включает анализ особенностей технологии искусственного интеллекта с точки зрения их интеграционных возможностей в обработке данных для государственного управления, требуемой цифровой зрелости предприятия и влияния технологий на результаты деятельности компании, вклада к повышению ее ценности и добавленной стоимости в процессе цифровизации. Статья будет интересна участникам процесса цифровизации, сотрудникам компаний, отвечающим за ее проведение, архитекторам и проектировщикам информационных систем.

The article reveals the challenges for the strategic management of the development of the Russian economy in the perspective of advanced personnel training. The main socioeconomic and political factors that threatening the country in this sphere are considered. In the model for situation problems recognition problems by advanced training of engineering personnel in universities based on the linguistic-combinatorial approach, possible alternative network solutions for its solution are presented. The network-centered management and the nature of the digital economy set new requirements for training systems, starting at school level and that of the small innovative enterprises up to the global socio cultural cycle. The article reveals the problems of strategic management of the development of the Russian economy and advanced training of personnel. The main socio-economic and political factors that threatening the country in this sphere are considered. An approach to the recognition of problem situations based on linguistic combinatorial modeling, which can be used in the planning of advanced engineering staff training in universities, is proposed. The network-centered management and the limits of the digital economy set new requirements for training systems, starting at school and small innovative enterprises in the global sociocultural cycle. Constraint of the digital economy is proposed by an analogy with the application of Network-centric warfare in military affairs.

Household incomes, their level and dynamics are one of the factors that ensure the achievement of the Sustainable Development Goals. At the same time, stable development of the banking sector, which is impossible without steady earnings, determines economic growth, which also positively affects reaching the Sustainable Development Goals. The paper examines the impact of household income on the return on assets of the banking sector in Russia using annual time series from 2003 to 2019. The study was conducted using formalized economic and mathematical methods of analysis by linear regression with least squares tests on the significance of the model, with tests for redundancy of insignificant variables (Wald test), Ramsey test on the functionality of the model, White and Breusch Pagan test for heteroscedasticity (heterogeneity of observations) and multicollinearity by method of inflation factors, graphic method. The Multiple Linear Regression (MLR) model was used. The results show that (1) an increase in the growth rate of household income and deposits in the non-financial sector has a positive effect on the return on assets of the banking sector; (2) an increase in the growth rate of the price of Brent crude oil and non-performing loans negatively affect the dependent variable; and (3) the regions that have the greatest (positive and negative) impact on profitability of whole bank sector in Russia were identified. Increasing household incomes and eliminating inequality in the incomes of the population of different regions will have a positive impact not only on social well-being but will also provide the banking sector with the opportunity for profitable operation and create conditions for sustainable growth. Our conclusions are useful for the regulator and individual banks and can be taken into account when developing and implementing policies aimed at sustainable development.

Purpose: it is to determine the most important factors that condition the ability of an enterprise to successfully implement the big data as a new economic resource. Methods: the methodological foundation of this research is the analytical framework of the resource-based view, which is applied to highlight the most important factors of the organizational capacity for the implementation of big data into economic activity. These factors are classified by blocks of internal factors of the organizational capacity in two hierarchical levels (organizational and individual). The study is based on the primary information obtained through a survey in the form of semi-structured interviews of managers and experts of the companies pioneering in implementation of big data. Results: a based on the analysis of scientific publications in accordance with positive and normative approaches to the understanding of big data, the concept of "big data" as an economic resource is developed. Its attributes are identified with emphasis on the heterogeneity of big data which allows filtering information about the subsystems of a complex economic system representing the modern enterprise. This information cannot be obtained from traditional sources of economic data. By systematizing the primary information on the projects of implementation of big data into economic activity by foreign companies by applying the analytical framework of the resource-based view, the key conceptual factors of the organizational capacity for the use of big data and relationship among significant factors have been identified. These key internal factors emerge as a result of the revolution in information technology and represent the necessary condition to ensure the transformation of the analytical procedures for decision making at the corporate level based on big data. The study reveals that sufficient condition represents a system of intangible resources and organizational capabilities, the most important of which is the capability to coordinate data processing and analysis. This capability, in a system with the other key organizational level capabilities, enables the integration of analytical and data processing technologies, on the one hand, and individual competencies of employees, on the other. Conclusions and Relevance: the implications of this study are aimed at researchers studying the problems of the information and networked economy, and practitioners of the Russian companies that are implementing or consider the implementation of the big data into economic activity. In business perspective, the most important implication of this research is that effective implementation of big data is not a technical challenge but an organizational and economic one. The basis of the organizational capacity for the implementation of big data is information resources, human resources and corporate culture and systems (technologies) for data processing and analysis.

В статье анализируется значимость психологии управления для современного бизнеса. Авторы, с помощью новых теорий и тенденций в области психологии и коммуникации (soft skills, эмоциональный интеллект, 4К), отвечают на вопрос: почему руководителю необходимо понимать человеческое поведение для качественного управления командой и принятия решений. Актуальность статьи обуславливается современными тенденциями общества на поиск баланса, гармонии и на отсутствие стресса. Исходя из этого, руководителю необходимо понимать психологию людей, в том числе, для управления конфликтами, что, в перспективе, обеспечивает мотивацию сотрудников и конкурентоспособность бизнеса на рынке. В статье решается актуальная проблема в рамках управленческой парадигмы: как сделать бизнес эффективным и конкурентоспособным за счет качественного управления подчиненными. Статья будет интересна как менеджменту крупных компаний с большим количеством сотрудников, так и для CEO новых компаний, которые хотят сформировать сильную и замотивированную команду.