Investigation of the impact of corporate social responsibility (CSR) and environmental responsibility on the economic performance over the past decades has shown that the implementation of CSR is one of the key drivers of value creation. Disclosure of social policy is one of the key CSR areas, it reduces information asymmetry and also contributes to the company’s reputation, decreasing uncertainty and risk in the assessment of the internal environment. This study shows that the disclosure of CSR information is able to increase the investment attractiveness of companies, and reduce the cost of equity. In the last decade, Russian industry has accumulated considerable positive experience in the implementing and positioning of corporate social responsibility (CSR) technologies, which has yet to be assessed. In this paper, we used the sample of social reports of 18 Russian companies in the period from 2004 to 2014. The authors provided content-analysis of information disclosure dimensions including staff training, social policy, charity and environmental responsibility. In contrast to other studies, the results show a comparatively moderate impact of disclosure on the cost of equity capital. Also, we found that different dimensions of the disclosure have an ambiguous impact on the investment attractiveness of companies. Our results allow formulating practical recommendations for the management of metallurgical, oil and gas Russian companies to increase their investment attractiveness, in particular, a prudent choice of CSR information for disclosure. The study is unique for the Russian practice of evaluating the effectiveness of CSR, as it is based on a sample of the largest industrial enterprises.

This article discusses peculiarities of the labour market functioning in the context of the digital economy development. It determines the main directions in the management of processes related to the accumulation and use of human capital as the production’s main factor in the context of digitalization. Our goal was to develop a multi-factor model of human capital efficiency in the digital economy. We used the materials of the Boston Consulting Group, the World Development Bank, and data from The Russia Longitudinal Monitoring Survey — Higher School of Economics (RLMS-HSE) as the study’s empirical base. As a research methodology, we chose a regression analysis based on the initial sample of data from RLMS 25, wave 2016, “Data on IBM SPSS individuals”. For the study of factors, we utilized the traditional J. Mincer equation, supplemented by quantitative and qualitative variables. We proved that expanding the range of parameters increases the coefficient of determination and the statistical significance of the parameters. On the basis of the empirical material, we confirmed a number of hypotheses on the determinants of the effective use of human capital in the digital economy. Particularly, the hypothesis about the impact of production experience on wages as an indicator of returns to human capital, previously put forward and supported by J. Mincer and his followers, is not confirmed for the digital economy. Digital technologies, replacing the old working methods, render the previous skills and organizational approaches irrelevant. Transformations caused by the environment’s automation and digitalization change the working activities from clearly defined work responsibilities to design work. The development of skills in digital knowledge application is an essential factor for the effective use of human capital in the digital economy. These skills enable workers’ adaptation to changing work processes and the employers’ requirements. The study’s results show that the correct interpretation of the determinants that affect the efficiency of the human capital use allow choosing the right targeting tools for managing human capital as a factor of economic growth.

Mining and metallurgical industry, as well as clusters based on it, historically occupy an important place in the economic structure of the Urals. Given that the Ural mining and metallurgical clusters are export-oriented, the problem of global competitiveness remains relevant. A large segment of the Russian academic literature is focused on studying cluster competitiveness. These studies are mainly based on traditional methods of efficiency analysis, including the analysis of sales activities and financial situation of enterprises. At the same time, in the world mining and metallurgical industry, a method of cash cost is actively used for analysing competitiveness. Russian academic literature, however, lacks works examining the use of cash costs for studying the competitiveness of mining and metallurgical clusters. This study suggests and tests a new approach to assessing the international competitiveness of the Ural mining and metallurgical clusters, based on the method of the cash cost calculation. The paper discusses the methodological aspects of calculating the cash cost indicator. Cash costs were calculated for the enterprises constituting the core of the Ural mining and metallurgical cluster. We compared the obtained value with the cash cost indicator of one of the world’s largest copper producers Codelco, as well as with the maximum price cost for this industry achieved in 2018. The calculation results have shown that the Ural mining and metallurgical clusters are commercially viable in the world. This fact indicates the presence of various competitive advantages in the world market, including a relatively great amount of useful components in the producing fields. The main competitive disadvantages are the widespread use of a more expensive underground mining method and the gradual exhaustion of the existing rich deposits.