Digitalization, considered in a broad sense as the most important modern trend of social development, is generally accompanied not only by positive consequences for the economy and society, but also by challenges, threats, as well as negative consequences of the implementation of these threats. Digitalization, considered in a narrow sense as the transformation of information of any kind into its digital form and involving the use of digital information, can also be described by challenges, threats, negative consequences and risks. Among the latter, a significant role is played by the risks of violating the security of digital information — cyber risks. Since they can have a negative impact on digitalization, considered both in a broad and narrow sense, there is a problem of allocating cyber risks and managing them in order to reduce possible losses and damage caused by the implementation of these cyber risks. The article defines the interrelationships of the concepts of digitalization, challenge, threat, negative consequence and risk; identifies the role and justifies the high importance of a cyber call as a requirement to ensure the security of digital information; determines the factors of influence on cyber risks; suggests a variant of building a cyber risk management program, the implementation of which will contribute to reducing the possible negative consequences of digitalization caused by a violation of the security of digital information.

The developing international education market requires additional qualitative and detailed information on the comparative characteristics of universities. This study suggests a single synthetic model for describing and assessing universities’ competitiveness at the national level for advanced, emerging, and transitioning economies. The model is based on the same methodology as international university rankings, but employs different techniques for initial clustering and further analysis. We identified four different university clusters in the Russian Ministry of Education and Science database, distinguished by specific development goals. We argue that applying these clear and welldefined criteria as clustering attributes allows us to compare competitiveness in different settings, formulate academic management strategy and recommend policy guidelines tailored precisely for each university’s requirements.

Economic convergence and digitalization are the most important trends of the modern community development. It is their interaction that creates new opportunities for the improvement of competitive capability and performance in the framework of joint business conducted by representatives of the wide variety of segments and sectors of economy. In response to digitalization, an ecosystem becomes the main institutional and organizational form of business in the framework of inter-sectoral economic convergence. The purpose of this article is to define more exactly the concept of an ecosystem as a form of doing joint business in the environment of inter-sectoral economic convergence and digitalization, and to build a classification of ecosystems. The following hypothesis is put forward in the study: an ecosystem as an institutional and organizational form of doing joint business is the result of the concurrent impact of inter-sectoral economic convergence and digitalization thereon, and the "connection of the base product provided to customer by the inter-sectoral economic convergence initiator prior to creating an ecosystem with digital and/or information technology" may be a criterion for classification of economic ecosystems. The novelty of the approach is as follows. The consideration of an ecosystem as a form of doing joint business simultaneously influenced by economic inter- sectoral convergence and digitalization has made it possible to define more exactly the concept of an ecosystem, identify an ecosystem parameter to be applied for classification of ecosystems and the main characteristic thereof the values of which may be used to classify economic ecosystems.

The article contains the study of the experience of operation of the specific Sber financial ecosystem as a new form of entrepreneurial activity in the competitive economic environment which is driven by the impact of digitalization on the economic convergence processes – the modern trend in the social development in general. The study of the experience of the Sber financial ecosystem which is one of the most highly developed ones in Russia is both of theoretical and practical interest. The purpose of the article is to describe the actual experience of Sber ecosystem’s operation. The results of the performed analysis are as follows. Definitely the Sber ecosystem is a form of organization of joint business implemented in the framework of intersectoral convergence driven by digitalization. The impact of intersectoral convergence is manifested in the fact that the creation of the ecosystem was initiated by a financial institution - the largest Russian savings bank; and the participants in this ecosystem are representatives of a wide variety of sectors and segments of the economy. The impact of digitalization shows in the fact that the basis of joint business is a modern digital base which includes IT, IT platforms and networks. The modern mathematical and instrumental methods of data processing and IT startups are not only the digital specifics of the ecosystem functioning, but also effective tools to attract to a joint business – on a voluntary basis only – the partners from various fields of activity, and provide the Sber ecosystem with undoubted competitive advantages.

Higher education is broadly recognized as one of the most significant components of modern social and economic development. The quality of education at a university depends on factors such as how the university is managed, how effective the management decisions are, and what consequences they have for the advancement of society. While the consequences have numerous hardly equitable aspects, this article hypothesizes that it is possible to build a synthetic model for the assessment of university management, that takes into account a full range of existing quantitative and qualitative effects. The study aims to identify the relationship between the quality of management and the performance variables needed to build the model. The research methodology includes the application of econometric analysis for the formation, ranking, and determination of point values of a balanced scorecard (BSC). Finally, the findings of this research led to the creation of a workable model that allows both direct and reverse translation of a quantitative management assessment into a qualitative (verbal) one. Further, the verification using the available empirical data confirmed the model’s validity. We would thus recommend this model for solving a whole range of university management issues, especially in areas with predominant ripple and indirect effects, i.e., in the interaction of higher education entities with regional and local communities.