Valeriia Arteeva

With the transition to a post-industrial economy, knowledge has emerged as a critical driver of economic activity. Consequently, the accumulated intellectual capital of a consulting company is the main factor determining its market position and operational effectiveness. Amid the growing influence of intellectual capital on the profitability of consulting companies and its essential role in creating sustainable competitive advantages within the knowledge economy, developing a methodology for assessing the relationship between intellectual capital efficiency and profitability in Russian consulting firms has become increasingly relevant. The study proposes a methodology based on the application of an econometric modeling apparatus using a multiple regression model. The simulation analysis utilizes a dataset including 730 observations for the period from 2015 to 2021 for Russian consulting companies. The dependent variable is net return on sales, while intellectual capital efficiency is measured by the coefficient of added value of intellectual capital and its components: human capital efficiency, structural capital efficiency and capital employed efficiency. The model also includes control variables that reflect company-specific and region-specific differences. The simulation was carried out using a fixed-effects model. The results reveal that there is a positive relationship between the coefficient of added value of intellectual capital and the coefficient of net return on sales. Additionally, the human capital efficiency indicator exhibits a predominantly positive but gradually decreasing marginal effect of on the net return on sales. It was noted that there is a positive relationship between the efficiency ratio of capital employed and the coefficient of net return on sales. The findings highlight the importance for managers of Russian consulting companies to pay attention to knowledge management practices in order to enhance the effective utilization of intellectual capital and improve financial performance.

Subject. The article discusses economic crime as one of internal threats to Russia’s security. Objectives. The aim is to determine the main directions of fight against economic crimes, analyze the impact of some parameters on the level of criminalization of the economy. Methods. The study employs econometric modeling methods. Results. The study confirmed hypotheses about direct impact of the number of unemployed population and the volume of investments in fixed assets on the number of registered economic crimes in regions, and about inverse impact of the average per capita monetary income. Conclusions. The proposed model can be used in further research to assess the level of economic security in the region. Strategies and measures to increase employment, stimulate the growth of the average per capita income of the population, the development and implementation of effective mechanisms to identify unofficial income and shadow transactions can act as the main tools to reduce the level of economic crime.

The relevance of this study is due to the growing attention to the development of green economy and its potential impact on employment. The purpose is to evaluate how green economic development affects employment in Russia, using panel data from 82 regions spanning the period from 2016 to 2020. To analyze the data, we use generalized linear regression models such as OLS, random effects, and fixed effects models. The final fixed effects model explains about 25% of the total variation in unemployment rates across different regions. However, evidence of cross-sectional dependence in the residuals suggests potential challenges, such as the omission of relevant variables that capture unobserved heterogeneity and inadequate consideration of spatial clustering within specific regions. The main results show that expenditure on environmental protection and maintenance of protected areas are positively linked with unemployment. This suggests that these expenditures may not directly lead to job creation. There could be several reasons for that: administrative costs, the delayed effect of environmental investments, or regional disparities in infrastructure and skilled labor availability.

There is an escalating demand for highly skilled professionals in digital analysis in Russia heightened by the COVID-19 pandemic and the onset of the special military operation in 2022. This study aims to identify the precise competencies that employers seek for big data analytics (BDA) professions with the focus on data analyst (DA) and business analyst (BA). It also aims to examine the dynamics and evolving skillset structures of these two roles. Our sample size comprises 2,357 vacancies that were analysed in 2020 and 2023. Our multimethod approach involves four stages: data collection of job postings, data processing, identification of the skills structures, and statistical analysis and data visualisation. We also used various techniques such as web-scrapping, data parsing, tokenisation, n-gram extraction, and social network analysis. Our results indicate a shift in Russia, where DAs require to have a solid understanding of business concepts, familiarity with non-STEM fields, and soft skills such as management, communication, and teamwork. BAs must possess technical skills related to BDA, including tool use, programming, and data analytics. The emphasis on interpersonal skills, like creativity and empathy, is crucial for effective collaboration in the interdisciplinary BDA field. This research clarifies the specific competencies required for DA and BA roles, emphasising their interdisciplinary nature in the Russian context. It offers practical insights for educational institutions, organizations, and policymakers to align curricula, training, and policies with market demands, and provides guidance for job seekers to enhance their skills and employability.

The tourism industry is a powerful tool for developing the country's economy, as it contributes to creating new jobs and capital inflow. Tourism development is closely linked to the development of infrastructure, as well as to the rapid introduction of information and communication technologies (ICT) and extensive digitalization. The authors assessed the impact of digitalization factors and infrastructure development on domestic tourism in Russia. Two final models were described as a result of the econometric analysis. The number of tourists in the region was chosen as a dependent variable, and the infrastructure development index (IDI) /transport development index (TDI), the costs of implementing and using digital technologies, and the number of hotels proved to be significant explanatory. Our analysis shows a 1% increase in the ?osts of introduction and use of digital technologies in the first model corresponds to the rise in the number of tourists in the region by 0.15%, and by 0.13% in the second model. The results indicate that 1 unit rise in the TDI leads to an increase in tourists by 20.2%, and the IDI growth by 1 unit implies to an expansion of tourist flow by 70.5%, which is due to a reasonably low spread of these indices. Thus, the development of domestic tourism is closely related to the spread of digital technologies in the regions and infrastructure development.

Subject. The article assesses the effectiveness of investments in higher education. Objectives. The aim is to assess the performance of investments in higher education for a Master’s student at the Peter the Great St. Petersburg Polytechnic University, in the field of Economics, Business Analyst Specialty. Methods. The methodology, presented in the study, includes three stages. The first assesses the demand for skills, the second assesses how the supply of skills match the demand, and the third – the effectiveness of investments in higher education, based on the developed mathematical model, scenario analysis, and decision tree. Results. We revealed that for a business analyst, the most important categories of skills are project management, decision-making, organizational competencies, communication, and knowledge of corporate software. The most required skills in these categories are the knowledge of business processes, project documentation, systems thinking, teamwork, communication, and well-bred speech. The analysis of correspondence between the competencies required by employers and those acquired in the training process showed that Master’s graduates meet the demand for the position of a business analyst in the labor market by 69%. Conclusions. The evaluation of the effectiveness of investment in higher education for a Master’s student of the Peter the Great St. Petersburg Polytechnic University, in the field of Economics, Business Analyst Specialty, shows that it is more profitable for a Bachelor graduate to continue studying for a Master's degree, rather than go straight to work.