Study of Operational Efficiency of Large-Scale Publicly Owned Companies in Russia Operational Efficiency of Large-Scale Publicly Owned Companies

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Evgeny Kuzmin
Valentina Guseva
Andrey Vlasov

Abstract

A sustainable economic growth is partly a consequence of the best possible balance between public and private sectors. Reasons for changed government efforts in economy are highly diverse and lie in the area of strategic development goals. A review of evidence-based studies shows that public ownership in a capital of companies influences some characteristics of their operational activities. The specific components, elaborated in the paper, contribute to this. Based on data provided in financial statements of leading publicly owned companies in Russia, the research aims at identification of causal relationships in composition and ownership structure of companies, as well as their impact on economic ratios. Researchers verified the assumptions, put forward in this respect, using the correlation-regression analysis. The basis for the operational efficiency comparison included the return on equity (ROE), return on assets (ROA), return on sales (ROS), equity ratio and current liquidity ratio. Findings show that there are sufficient arguments in favour of the assumption that publicly owned companies are consistently less efficient against the private ones. Obtained data made it possible to conclude that a change in the state’s share in the capital of large-scale companies in Russia significantly influences the return on assets and return on equity only. Other ratios under consideration express poor correlations. The heterogenic impact on adjacent ratios of operational efficiency prevents from concluding in a rigorous manner that publicly owned companies are a priori less efficient. One needs to keep in mind sector affiliation and a capital concentration ratio.

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How to Cite
Kuzmin, E., Guseva, V., & Vlasov, A. (2019). Study of Operational Efficiency of Large-Scale Publicly Owned Companies in Russia. Advances in Systems Science and Applications, 19(3), 23-37. https://doi.org/10.25728/assa.2019.19.3.747
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