The manufacturing industry makes a significant contribution to Russia’s GDP and exports, but it faces problems that hinder its development. The aim of this study is to estimate the relationship between intellectual capital and performance indicators of Russian manufacturing companies. The study analysed a sample of 23,494 observations of Russian manufacturing companies for the 2017–2020 period. The value-added intellectual coefficient (VAIC) and its components were used to evaluate the impact of intellectual capital on firm performance using polled ordinary least squares, fixed, and random effects models. Intellectual capital significantly and positively affects the performance of companies in both structural and human terms—both through the integrated coefficient VAIC and in the context of individual components of intellectual capital. However, the impact of structural and human capital on performance indicators is significantly lower than the impact of capital employed. There is a distinct focus of enterprises on making profit through the use of company assets, while in the case of Russian manufacturing companies, the potential for profit generation from structural and human capital remains unfulfilled.

Subject. The article addresses relationship between intellectual capital and operating efficiency of IT companies. Objectives. Our aim is to conduct econometric analysis of the impact of intellectual capital and its individual elements on the profit margin of Russian IT companies. Methods. We employ methods of econometric analysis. The sample comprised 323 IT companies operating in Russia from 2016 to 2020. Results. We built two blocks of linear regression models with random and fixed annual and panel effects. For models of the first block, were selected indicators of structural (SCE), human (HCE), relational (RCE) capital efficiency and capital employed efficiency (CEE) as exogenous variables. The regression analysis showed that CEE and SCE have a significant positive effect on profit marginality. For models of the second block, we used a complex indicator, combining SCE, HCE, and RCE. We established that intellectual capital in general is positively associated with gross profit marginality of Russian IT companies. Conclusions. The study revealed that Russian IT companies effectively use the supporting intangible infrastructure and total assets. However, human capital, being the most significant resource of this industry, is used inefficiently and provides no potential for profit. Relationships with counterparties (consumers, suppliers, and other stakeholders), expressed in RCE, did not show a significant relationship with profitability either. Practical application of the findings may help improve business processes and management of intangible resources of IT companies.

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.