One of the main generally accepted indicators of enterprise performance is profitability. It is of interest to owners of the enterprise and investors as an indicator of the increase in business value and income generation, for managers of the enterprise in terms of the development of the enterprise and its technical modernization, and for the state insofar as the profit is subject to taxation. As the main indicator of the enterprise's activity, it is influenced by many factors that reflect both the production efficiency within the company and the influence of the resource and good markets. We can assume the influence of two groups of factors affecting profitability:
PurposeThe paper analyzes the effects of the capital structure on company performance (return on assets). The analysis is conducted in a large sample of high-tech manufacturing and service companies in the transition economy (Russian Federation). In addition to the aggregated analysis, separate investigations are conducted to scrutinize the impact of company age, size and location factors (the effects of agglomerations). This research postulates the existence and variability of the optimal capital structure and its dependence on economic crisis.Design/methodology/approachWe utilized a large sample that includes 1,826 enterprises over the period from 2013 to 2017. The estimation was performed using the panel-corrected standard error estimation technique (Prais–Winsten regression) to account for the panel nature and distributional properties of our data. The existence of the optimal capital structure was assessed based on a curvilinear (quadratic) function.FindingsThe results are consistent with the Static Trade-off Theory and show that this theory is applicable to countries with transition economy. They demonstrate that effective management of the capital structure can increase return on assets by 16–22%. The optimal share of borrowed capital is higher for small businesses compared to larger ones and for enterprises located in agglomerations compared to those located in other regions. A greater increase in profitability can be achieved by larger firm companies compared to smaller ones. High share of borrowed capital leads to negative profitability, i.e. to losses by enterprises. No significant differences in profitability growth were identified between young and mature enterprises. The optimal share of borrowed capital that maximizes return on assets is in the range of 0–21%.Research limitations/implicationsDue to the SPARK policies, our access to the data has been limited to a five-year window, which imposed certain limitations on the choice of econometric methods we could have employed and somewhat limited our ability to contrast the effect of the crisis period with the period of stability. In this sense, although our results pertaining to the effect of the crisis could be treated as conservative, future research should consider extending the panel to include more years into consideration.Practical implicationsWe identified significant differences between optimal capital structures and actual capital structures for high-tech enterprises. The contribution of this study is that the calculations were made for a country with a transition economy under crisis conditions. Countries with transition economies and developing countries tend to be characterized by a high level of interest rates on loans and a high proportion of borrowed capital in total assets. This poses difficulties for companies relying on borrowed capital to finance their operations. At the same time, our results demonstrate that in transition economies, enterprises in high-tech industries do have an optimal capital structure that allows maximizing firm performance. That is, Static Trade-off Theory is applicable to transition economies characterized by high interest rates on loans.Originality/valueThe novelty of this study lies in the detailed analysis of high-tech industries in Russian Federation. This analysis makes use of sophisticated econometric techniques for the first time in this context.
Research background: Innovative development of industries and regions in Russia during the period 2005–2011 has not brought significant positive results. Innovative activity of regions and industries remained at a low level. After a relatively stable 2012–2013, the Russian economy faced the geopolitical crisis and economic sanctions in 2014–2015. Purpose of the article: The primary purpose of this study is to investigate the innovative development patterns of industrial sectors in selected Russian regions in the years 2012–2015, which include the period of negative external environment (2014–2015) for the national economy. Methods: The study enhances the analysis of statistical data and applies quantitative analysis methods (variance analysis). The research focuses on 14 regions of Russia, members of the Association of Innovative Regions of Russia (AIRR) and 2 specific industries: section D «Manufacturing» and subsection DL «Manufacture of electrical and optical equipment» which usually manifest high level of innovative economic activity. Findings & Value added: The research results show that the crisis period of 2014–2015 has not stimulated the increased innovative activities for both industries. The innovative sector (section D) grew faster than the non-innovative one in 2013, but this advantage became insignificant in 2014–2015. Some signs of revival for innovative enterprises in subsection DL were observed during the crises beginning in 2014, but this trend was not retained in 2015. The analysis of structural indicators (proportions) of the innovative sector shows that only a few AIRR regions have values comparable to the leading European countries. Most of the AIRR regions lag behind the leading foreign countries specifically on the «Share of enterprises engaged in technological innovation» and «Share of new or significantly improved products» Indicators. The study did not reveal the statistically significant positive dynamics of these indicators in the AIRR regions over the period 2013–2015.
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