Implementation of the state policy in the field of innovation

In the Strategy of scientific and technological development of the Russian Federation, the main goal is to ensure the competitiveness and independence of the state by forming an effective system of the most complete application and development of the intellectual potential of the state. The main directions in the work of the Government of the Russian Federation, for the period up to 2024, is the formation of conditions for the entry of the Russian Federation into the top five leading countries in the field of R D, represented by the priorities of scientific and technological development of the state, determined by this Strategy.These areas are represented by the Program, which is the main mechanism for implementing the Strategy. It is aimed at increasing the socio-economic effect of applying the results of scientific research and intellectual activity, significantly increasing the efficiency of using budget funds and extra-budgetary sources to finance R D, by switching to the qualified customer model. The Strategy also provides for measures to develop the level of capitalization of the educational potential of the population to fulfill the tasks of technical modernization of industrial production, development of entrepreneurial structures of all types, attracting talents, social mobility, ensuring the required rates of economic growth, as well as the quality of life of society

Science Intensity of the Business Sector in Russia: An Analysis and Development Proposals

Introduction. In the context of global competition between intellectual industries and building transnational structures that ensure socio-economic development, joining the world’s top 5 most innovative economies is possible only in case of increasing the science intensity of the business sector of the economy. Based on the results of the study conducted, the article gives an analysis of the industry average values of the costs of enterprises for research and development (R&D) in economically developed countries and outlines proposals for achieving a similar level of costs for such work in Russia. Materials and Methods. The study used data from the Organisation for Economic Co-operation and Development international statistical database, those from Rosstat, and reports from companies implementing innovative development programs. The results of the implementation of the programs for innovative development of Russian state corporations were evaluated. The study employed the methods of economic analysis, comparison, generalization, induction, and deduction. Results. On the basis of the study conducted, the authors have proposed recommendations for bringing the R&D costs to the level of the industry average values in economically developed countries. The authors have also proposed to secure the coefficients of the R&D costs corresponding to those in countries leading in innovative development in the programs of innovative development of organizations, taking into account the industry specifics. The authors have recommended introduction of such tools that ensure the achievement of the level of investment expenditures in R&D of economically developed countries, as the “qualified customer” model and the innovation voucher. Discussion and Conclusion. Based on the results of the analysis performed, a conclusion has been drawn that not all state corporations fully implement the assigned tasks. In order to ensure the technological development of the country, a number of federal executive bodies have been implementing a set of measures which lack synchronization. The results of this study can be used by public authorities when making managerial decisions in research and development.

On Creating a “Powerful Scientific and Technological Base” and the Necessity of Strengthening State Support of Scientists and Innovative Business in Russia

The article is a research response to the task of developing the scientific and technological base set by the President of Russia in his message to the Federal Assembly in 2019. The scientific and technological base is revealed as a more comprehensive concept than a concept that includes only material and technical objects, in particular, it accommodates human resources engaged in research and development. The author reveals insufficiency of current measures of state support for researchers and developers, which boil down mainly to competitive financing of scientists and little-demanded tax breaks for innovative business. The paper proves several measures to strengthen the basic support of research personnel and technological business. There is a need not only to implement large scientific and technological infrastructure projects, but also increase the volume of budget (basic) support for researchers and developers through the growth of actual wages at the rate of the full working rate, provide preferential mortgage loans, expand tax incentives for innovative business, as well as develop a “qualified customer” model. The analysis is performed on the basis of studying Russian regulatory legal acts defining the state scientific and technical policy, articles of Russian scientists as well as materials of Russian and international statistical databases. The results of the study may be used by representatives of the executive authorities, as well as a wide range of specialists interested in the problems of science and technology policy in Russia.

Digital advertising as a tool to promote goods or services. Project implementation experience

The article has been devoted to theoretical issues of the digital advertising sphere, its tasks and features. The online advertising market development level has been estimated, based on analytical data. Digital advertising is a complex of analytical, technological and supporting tools, which are interconnected directly. It includes a system of methods and tools, which use digital channels to promote a product or brand, attract and retain customers. The main areas of digital advertising are display advertising, banner advertising, video advertising and contextual advertising. Digital advertising is not limited by the Internet, but it uses other communication resources such as television, radio, telephone, direct sales and direct contact. A key feature of digital advertising is its interactivity and formed on its basis analytical resources (consumers, their preferences, products, channels, etc.), that provide personalization. At its core, personalization is the process of understanding the true intentions, desires and needs of a person, as well as the transfer of relevant, targeted and significant experience for that person. In practical terms, this means building and using a customer model and managing customer experience. The article examines the properties of digital advertising and its implementation as a project. The interdisciplinary properties of digital advertising predetermine the cross-subject nature of the training of specialists in digital advertising: marketing and information technology specialists. To illustrate the given theoretical material a real project of digital advertising company for popular among young people food product has been presented. The project goals and concept, its plan and organization of execution, the tools of digital advertising used have been considered: chat bots, mobile version of the site, landing page, gamification, promo codes, CRM system, bloggers, SMM. It has been shown, how the assessment of digital advertising impact activities of the company and the costs of the project were carried out.

Developing a Customer Model for Targeted Marketing using Association Graph Mining

Data mining is the procedure to find out significant information from large database by applying several mining techniques. Finding out products that are purchased together is a major issue in basket market analysis. So, developing a customer model is important for targeted marketing. The traditional dataset is taken into account because the origin of information which is available from the history of sales repository. While applying the basic techniques on transactional data analysis, it fails when the process has a greater number of transactional information. Also, it is difficult to identify suitable correlation between one product to another. In this paper Market Basket Analysis is extended towards into network level and it recommends a product network consideration it clearly states that the correlation involving products bought together by customer. This research work focuses on product to product network analysis in market basket network. The direct and indirect approach is applied in associated product network from history of retailer data. The major intention of this research work is to find the group of essential products purchase by the customer together. So, it will bring out consumer profile, product blue print, guidance from associated products and provide effective result from large number of customer wholesale outline

Using Agent-Based Customer Modeling for the Evaluation of EV Charging Systems

The development of efficient electric vehicle (EV) charging infrastructure requires a modeling of customer behavior at an appropriate level of detail. Since only limited information about real customers is available, most simulation approaches employ a stochastic approach by combining known or estimated customer features with random variations. A typical example is to model EV charging customers by an arrival and a targeted departure time, plus the requested amount of energy or increased state of charge (SoC), where values are drawn from normal (Gaussian) distributions with mean and variance values derived from user studies of obviously limited sample size. In this work, we compare this basic approach with a more detailed customer model employing a multi-agent simulation (MAS) framework in order to investigate how a customer behavior that responds to external factors (like weather) or historical data (like satisfaction in past charging sessions) impacts the essential key performance indicators of the charging system. Our findings show that small changes in the way customers are modeled can lead to quantitative and qualitative differences in the simulated performance of EV charging systems.