The innovation economy is the main direction for Russian’s regional development. It is important to understand organizations that utilize new technologies will determine the significance of innovations. Innovation is changing under the influence of society—the basis for the development of the society is knowledge transfer, and this is one of the most important tasks of the higher education system. In this regard, universities can be considered a factor in innovative development. In this article, the authors hypothesize a link between regional and university indicators. We assume that universities, as part of the regional innovation system, affects the effectiveness of this system. We believe that it is necessary to single out a system of indicators that can be used for analysis, which allows us to determine the efficiency of the region in terms of contribution of universities to its development—because, at the moment, there is no official methodology. The purpose of this study is to determine which indicators are significant for assessing the efficiency of the region, taking into account the activities of university complexes. We will evaluate the efficiency of regional innovation in the region using a data envelopment analysis (DEA). The research objects, or decision-making units (DMU), will be represented by 85 regions of the Russian Federation. A complex of universities operates in each region, and there is a list of socio-economic statistical indicators based on their performance over the past years. There are similar statistical results on the innovative activity of the regions. Thus, we will use the indicators of the complex of universities in the region as initial resources for analysis (2011), as well as indicators of the innovative development of the region as a result of the introduced resources (2018). A time lag of six years is justified by the end of the crisis, and the many factors affecting the activities of universities and regions. For example, increased funding for scientific activities of universities encourages small innovative enterprises within universities. As a result, we were able to identify the level of efficiency, and identify factors that are of greater importance in the resulting model. The findings of the study highlight the importance of educational organizations in the regional innovation system, and encourages alternative interactions between universities and the region, such as joint research and development, training of qualified personnel, and other channels.

The important role of the intellectual capital in the innovative-digital economy generates an objective necessity in the immersed study of the processes of its creation, formation and application, which will allow making the correct selection of guidelines and directions of further development and will lead to creation of such an economic development strategy in the heart of which is a human being with the accumulated knowledge, skills and ground-breaking ideas. The article covers the peculiarities of the intellectual capital reproduction in the innovative-digital economy environment. The study of the human capital obsolescence processes is also carried out; the cycle, stages and forms of its reproduction are represented; the system of enterprise management is developed, which provides enhancement of production efficiency on the basis of its interspecific resources. The study shows that the objective necessity and peculiarity of the modern stage of the world community development is creation of conditions for generation and development of the human capital intellectual component facilitating the transition to the innovative-digital economy. The results obtained in the course of the study can be used for making managerial decisions on creation of the efficient mechanism of reproduction and control over the intellectual capital relevant to tasks of the social-economic development of the country.

This study provides a framework for the comparative assessment of the key industry aspects of competitiveness among logistics services and the logistics systems of enterprises in the informational environment. Frequently, the relationships between a consumer and a company created by means of the informational environment determine how the enterprise positions itself in the market. For instance, the evaluation of a company’s representation in the information field is an essential aspect of determining the company’s competitiveness. The study suggests a set of special metrics for measuring the representation of digital components and other aspects of an enterprise’s digital image via data gathering and analysis of the most encountered tokens. The proposed automated analysis algorithm allows companies to examine their image in the digital environment and implement effective decisions. The functionality of the algorithm fosters data collection, helping to form the desired image of the company. Tokens of several thematic groups on social media are collected during the process, and the most significant of them that are valuable for the competitiveness of the enterprise are extracted. The outcome can be used for the tracking of the dynamics of key parameters of an enterprise’s image and for conducting a comparative analysis of the digital image of its competitors.

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.