Financial Risks of Russian Oil Companies in Conditions of Volatility of Global Oil Prices

The development of scientific approaches to assessing and diagnosing the financial risks of oil industry in the Russian Federation becomes a high priority task in conditions of high level of volatility in oil prices in the world energy market and preservation of sanctions regime. The article shows the main threats to financial stability of oil companies in Russia. Using cluster analysis, a system of indicators is proposed that determines the level of financial risk of oil companies in Russia. Based on the method of expert assessments and fuzzy sets, the classification of financial risk levels of oil industry is proposed. The integrated financial risk level of oil industry was calculated and scenarios of its development for 2018–2020 were forecast by means of regression modeling. The system of measures to improve the stability of oil companies and prevent functional financial risks is argued. The practical implementation of research results will be the basis for timely diagnosis of financial risks and qualitative development of preventive measures to neutralize them in the oil industry of Russia. Keywords: Oil Industry, Oil Companies, Financial Risks, Oil Prices, Financial Stability of Oil Industry JEL Classifications: Q43; Q41; G32; L52 DOI: https://doi.org/10.32479/ijeep.735

Optimization Model for the Russian Electric Power Generation Structure to Reduce Energy Intensity of the Economy

In the context of high energy intensity of the country's economy, contributing to a decrease in the industry competitiveness of the Russian Federation, it is relevant to develop scientific approaches to energy efficiency provision. The article is aimed at stimulating the optimal structure of electric power generation in Russia, promoting energy conservation and lowering energy intensity of the economy. The Cobb-Douglas production function was used to determine the dependence of the gross electric output on such production factors as labor costs and capital. Based on the expert evaluation method, the sources of electricity generation were differentiated according to the level of labor intensity. An optimization model has been developed for electric power generation structure in Russia in the context of actual energy generation sources: nuclear power plants; natural gas fired thermal power plants , coal and fuel oil fired power plants; hydropower plants; solar power plants; wind power plants; tidal power plants; and biofuel power plants. The percentage changes in the consumption of energy resources and power generation, ensuring a decrease in the energy intensity of the Russian Gross Domestic Product by 19.1%, are argued. The system of optimization measures has been substantiated; their practical implementation will contribute to the steady decline in energy intensity of the Russian economy, effective energy consumption and the growth of the country's energy potential, with regard to ensuring structural changes in the energy sector. Keywords: Energy Intensity of the Russian Economy, Energy Resources, Optimization Model for Electric Power Generation Structure, Power Industry, Economic Energy Efficiency JEL Classifications: Q4; L16; L52 DOI: https://doi.org/10.32479/ijeep.755

Sustainable Development Adoption in the High-Tech Sector: A Focus on Ecosystem Players and Their Influence

In an era marked by increasing concerns about environmental sustainability, the telecommunications industry faces a pressing need to examine its commitment to sustainable development practices. Therefore, this study investigated the drivers and constraints influencing the adoption of such practices within the industry, with particular emphasis on the roles and interactions of ecosystem players. The research employed structural equation modeling (SEM) in AMOS to test the hypotheses and multilayer perceptron (MLP), which is an artificial neural network model, to assess the importance of each variable in the context of sustainable development adoption (SDA). This study analyzed data obtained from a diverse sample of telecommunications professionals, including telecom operators, device manufacturers, technology providers, and content and service providers. The findings reveal that stakeholder expectations held the highest normalized importance, suggesting their paramount influence in driving sustainable practices within the industry. Competitive advantage emerged as the second most significant factor, contributing to the adoption of sustainable strategies by companies. Conversely, cost and ROI concerns presented a constraint that potentially hindered SDA. This research contributes to the comprehensive understanding of sustainable development in the high-tech sector, aiding industry practitioners and policymakers in fostering a more sustainable future for the telecommunications industry. The implications derived from the sensitivity analysis provide valuable insights into prioritizing efforts and resources to enhance sustainable development adoption in the telecommunications sector