Corresponding author: Tatiana A. Burtseva (

Academic editor: Yury Korovin

The depletion of traditional organic energy sources and aggravated environmental problems are the reasons why the level of energy efficiency is an important factor in the competitiveness of the national economy. Russia ranks third in the world in terms of total energy consumption and its economy is distinguished by a high level of energy intensity (amount of energy per unit of GDP). In 2019, this figure was 9.62 tons of oil equivalent (toe) per 1 million rubles, which is 40% higher than the world average.

The low energy efficiency of the Russian economy is a widely recognized problem. A special decree of the Government of Russia in 2018 sets the task of increasing the level of energy efficiency of the Russian economy by 23% by 2030. One of the ways to solve this problem is the development of nuclear energy, and increasing the competitiveness of nuclear energy is one of the key issues for the national economy. In this connection, solving the problem of assessing the competitiveness of the nuclear industry and its leading companies occupies a key place among the practical scientific problems, the solution of which is facilitated by the results presented by the authors in this article.

Rosenergoatom Concern JSC is the leading energy generating company in the Russian nuclear industry. The results of the study of the competitiveness of Rosenergoatom Concern JSC were obtained on the basis of the authors’ methodology for assessing the competitiveness of an energy generating company. The novelty of the presented methodology lies in the developed normative and evaluative model and the coefficients of competitiveness of an energy generating company.

The advantages of the authors’ model are that it allows (1) obtaining integral assessments of the competitiveness of a power generating company at short time intervals for a large number of indicators and (2) quantitatively measuring the effects of different factors on the competitiveness of a power generating company, provided that the grouping of indicators of competitiveness of a power generating company is justified by influencing factors. The two factors considered by the authors were: the general market factor and the industry factor.

According to the results of the study, it was found that Rosenergoatom Concern JSC demonstrates positive increase of the competitiveness indicator mainly due to the industry factor. With this regard, it was concluded that, within the framework of state policy, it is advisable to strengthen support for the Russian nuclear industry by creating additional conditions and opportunities for its energy generating companies on the domestic energy market.

Russia is one of the leaders on the world energy market utilizing different forms of energy generation. One of the main forms is nuclear power generation producing about 20% of electric power in the general energy balance of the country. At present in Russia 38 nuclear power units are in operation in Russia on 11 NPPs. Contribution of nuclear power generation is important in the European part of Russia and, especially, in the north-west where power generation by NPPs reaches 42% (

The objective of the present study is to perform dynamic assessment of competitiveness of Rosenergoatom Concern JSC on the domestic market. This objective is achieved using statistical factor methods, dynamics analysis, dynamic normal, which allowed applying both conventional and newly introduced indicators of competitiveness of a business entity reflecting industry specifics of Rosenergoatom Concern JSC.

Competitiveness of an energy generating company is the ability of the company to use both its own and natural resources with higher efficiency ensuring more beneficial competitive positions.

Normative and evaluative model of competitiveness of energy generating company was developed of the basis of the concept of the system of balanced indicators and the dynamic normal method for conducting diagnostics of competitiveness of Rosenergoatom Concern JSC.

The systems and models of indicators as the instruments for assessment of competitiveness and results of operations of business entities are in application already for almost 100 years. One of the first attempts was the Dupont model (1920), which found widespread application by large corporations.

Dynamic normal method became the new approach to the assessment of enterprise management in a state-planned economy. The method for the first time treated the enterprise as the economic system including not only material and technical assets, but the management system as well. The basis of the dynamic normal method is the procedure of selection of economic indicators and their systematization. The idea of systematization of dynamic indicators for economic systems belongs to I.M. Syroezhkin (

The list of indicators (dynamic normal) structured according to the growth rates (indices) was defined for constructing the model. Correlations between basic indicators (structuring principles) are shaped on the basis of coefficients characterizing competitiveness of an energy generating company suggested by the authors. The assessment demonstrating the fraction of realized correlations between the rates (indices) of growth of factual values of dynamic normal indicators in the normative and evaluative model of competitiveness of the energy generating company is the integral indicator of competitiveness 22]. The obtained value of the integral characteristic is found within the interval [0, 1]. The closer is the value of the integral estimation to unity the higher is the level of competitiveness of the energy generating company.

The following indicators are included in the dynamic normal.

Fixed assets according to their depreciated value include the assets involved in the economic operations of the company and operated during more than one year taking into account their depreciation. These assets generate revenues for the company because the value of such assets is transferred on the ready products portionwise. Assessment of value of fixed assets takes into account their wear, i.e., duration of their operation, which is extremely important for the comparative assessment of competitiveness of energy generating companies utilizing different energy sources.

Current assets: the assets involved in the economic operations of the company consumed during one year.

Revenues: the aggregate earnings from the company’s economic operations.

Profit: the difference between the aggregate earnings and expenditures resulting from company’s operations.

Installed capacity: the aggregate rated electric power of electrical machines of the same type.

Total generated energy: the total quantity of electric energy generated during one year (Khvorostyannikov 2020).

Yearly annual number of employees: the number of people employed by the enterprise during one year.

Cost of electricity generation: the indicator characterizing operation of the energy generating company which is the aggregate of all costs in the process of generation, transfer and distribution of electricity in electric grids expressed in monetary terms (RUR/kW×hour).

The above dynamic normal indicators are divided into two groups as follows: universal indicators (applicable in the analysis of competitiveness of any company) and unique indicators (can be applied only in the examination of competitiveness of energy generating companies), which allows quantitative measurement of the effects of the conventional (general market) factor and the industry factor taken separately on the competitiveness of the energy generating company (Fig.

Factors and indicators of competitiveness of an energy generating company.

Paired comparison method and competitiveness coefficients suggested by the authors, as well as preset targeted limits for their variation (Columns 1 and 2 in Table

Coefficients of competitiveness of the energy generating company (developed by the authors)

Coefficient | Targeted objective | Economic meaning |
---|---|---|

1 | 2 | 3 |

Return on FA | Growth | Increased volume of profit due to the annual average balance of the company |

Return on CA | Growth | Increased volume of profit due to the increase of the CA volume |

Return on sales | Growth | Financial efficiency of sales of EG on the market |

Return on IC | Growth | Large number of IC generates larger profit |

Return on DC | Growth | The more efficiently is the use of fixed assets the higher is the profit |

Capital to labor ratio | Growth | Efficiency of use of fixed assets |

CA turnover | Growth | With increasing intensity of CA use their turnover increases |

Efficiency of labor | Growth | Increased efficiency of labor reduces operating costs and increases profit |

Return on labor | Growth | Operating costs must not exceed the profit |

CEG per 1 kWhr | Reduction | DC 1 kWh reduces with increasing VEG |

Correlation of EG volume with FA | Growth | Increase of FA results in the increase of VEG |

Correlation of CEG with FA | Reduction | CEG decreases with reduction of DC of the FA |

Correlation of VEG with FA | Growth | Increasing FA results in the increase of VEG |

Correlation of CEG with CA | Reduction | Cost of electricity generation reduces with decreasing CA |

Correlation of revenues with IC | Growth | Efficiency of use of the IC |

Correlation of revenues with VEG | Growth | Revenues increase with growing VEG |

Correlation of revenues with yearly average NE | Growth | Revenues increase with growing NE |

Correlation of CEG with revenues | Reduction | CES decreases with growing revenues |

VEG profitability | Growth | Higher VEG generates larger profit |

Return on CEG | Growth | Reduction of CEG generates higher profit |

Correlation of VEG with IC | Growth | Increasing IC increases the VEG |

Correlation of VEG with NE | Growth | Increased NE increases the VEG |

Correlation of CEG with IC | Reduction | Cost of generation reduces with increasing IC |

Correlation of CEG with NE | Reduction | CEG reduces with reduction of NE |

Comments: ВА – fixed assets; EG – electricity generation; CA – capital assets; VEG – EG volume; DC – depreciated cost; CEG – cost of electricity generation; IC – installed capacity; NE – number of employees

The normative and evaluative model is formalized as the _{ij}_{n}_{×}_{n}

where _{i}_{j}_{i}_{j}_{i}_{j}

The matrix

The formula for calculating the quantitative level of the integral estimation

where

In the above expressions _{ij}_{ij}_{n}_{×}_{n}_{ij}_{ij}_{ij}_{n}_{×}_{n}

where _{i}_{j}

Effects from each of the indicators on the growth of the estimation is determined according to the following formula:

where Δ_{i}^{о}_{ij}^{б}_{ij} are the elements of the matrix of coincidences of the factual and the standard correlations between the growth rates of indicators for the reporting and the base periods, respectively. Application of the suggested methodology is discussed in more details in (

Normative and evaluative model of competitiveness of an energy generating company (developed by the authors)

Index _{ij} |
Indicator of the dynamic normal _{ij} |
Index _{ij} |
|||||||
---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ||

1 | Depreciated value of fixed assets | 0 | 0 | –1 | –1 | 0 | –1 | 1 | 1 |

2 | Capital assets | 0 | 0 | –1 | –1 | 0 | –1 | 0 | 1 |

3 | Revenues | 1 | 1 | 0 | –1 | 1 | 1 | 1 | 1 |

4 | Profit | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 |

5 | Installed capacity | 0 | 0 | –1 | –1 | 0 | –1 | 1 | 1 |

6 | Volume of energy generation | 1 | 1 | –1 | –1 | 1 | 0 | 1 | 1 |

7 | Yearly average number of employees | –1 | 0 | –1 | –1 | –1 | –1 | 0 | 1 |

8 | Cost of electricity generation | –1 | –1 | –1 | –1 | –1 | –1 | –1 | 0 |

Calculated indices of growth of indicator values for Rosenergoatom Concern JSC for years 2018 and 2019 (Table

The obtained matrices of factual coincidences for years 2018 and 2019 for Rosenergoatom Concern JSC are presented in Tables

The integral estimations of competitiveness obtained, as the result, using formula (2) for Rosenergoatom Concern JSC for 2018 and 2019 are following:

_{2018} = 0.541667;

_{2019} = 0.91667.

Based on the obtained results the statement can be made that competitiveness of Rosenergoatom Concern JSC for 2019 increased by Δ

Factorization of the increments of the assessed competitiveness of Rosenergoatom Concern JSC (See (5)) on the basis of which the effects of the conventional and the industry factors were investigated, is presented in Table

The conclusion can be drawn according to the data in Table

As it has been mentioned above, the conventional factor of competitiveness is characterized by the following five indicators:

Discounted value of fixed assets;

Capital assets;

Revenues;

Profit;

Yearly average number of employees.

The industry factor is characterized by the following three indicators:

Installed capacity;

Volume of electricity generation;

Cost of electricity generation.

Effects of each indicator on the increment of assessed competitiveness of Rosenergoatom Concern JSC for 2018–2019 were estimated by summing up the increments for these indicators in Table

Indices of growth of indicators for Rosenergoatom Concern JSC for years 2018 and 2019 (developed by the authors)

Indicators in the dynamic normal | 2018 | 2019 |
---|---|---|

1. Discounted value of fixed assets | 1.04 | 1.02 |

2. Capital assets | 1.20 | 1.41 |

3. Revenues | 1.08 | 1.17 |

4. Profit | 0.86 | 2.55 |

5. Installed capacity | 1.08 | 1 |

6. Volume of electricity generation | 1.01 | 1.02 |

7. Yearly average number of employees | 0.95 | 0.96 |

8. Cost of electricity generation | 0.94 | 0.82 |

Matrix of factual correlations between the indicators of competitiveness in the dynamic normal for Rosenergoatom Concern JSC for 2018 (developed by the authors)

Index _{ij} |
Indicator in the dynamic normal _{ij} |
Index _{ij} |
|||||||
---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ||

1 | Discounted value of fixed assets | 0 | –1 | –1 | 1 | –1 | 1 | 1 | 1 |

2 | Capital assets | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 |

3 | Revenues | 1 | –1 | 0 | 1 | 0 | 1 | 1 | 1 |

4 | Profit | –1 | –1 | –1 | 0 | –1 | –1 | –1 | –1 |

5 | Installed capacity | 1 | –1 | 0 | 1 | 0 | 1 | 1 | 1 |

6 | Volume of electricity generation | –1 | –1 | –1 | 1 | –1 | 0 | 1 | 1 |

7 | Yearly average number of employees | –1 | –1 | –1 | 1 | –1 | –1 | 0 | 1 |

8 | Cost of electricity generation | –1 | –1 | –1 | 1 | –1 | –1 | –1 | 0 |

Matrix of factual correlations between the indicators of competitiveness in the dynamic normal for Rosenergoatom Concern JSC for 2019 (developed by the authors)

Index _{ij} |
Indicator in the dynamic normal _{ij} |
Index _{ij} |
|||||||
---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 1 | 5 | 6 | 1 | 8 | ||

1 | Discounted value of fixed assets | 0 | –1 | –1 | –1 | 1 | 0 | 1 | 1 |

2 | Capital assets | 1 | 0 | 1 | –1 | 1 | 1 | 1 | 1 |

3 | Revenues | 1 | –1 | 0 | –1 | 1 | 1 | 1 | 1 |

4 | Profit | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 |

5 | Installed capacity | –1 | –1 | –1 | –1 | 0 | –1 | 1 | 1 |

6 | Volume of electricity generation | 0 | –1 | –1 | –1 | 1 | 0 | 1 | 1 |

7 | Yearly average number of employees | –1 | –1 | –1 | –1 | –1 | –1 | 0 | 1 |

8 | Cost of electricity generation | –1 | –1 | –1 | –1 | –1 | –1 | –1 | 0 |

Matrix of coincidences for 2018 (developed by the authors)

Index _{ij} |
Indicator in the dynamic normal _{ij} |
Index _{ij} |
|||||||
---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 1 | 5 | 6 | 1 | 8 | ||

1 | Discounted value of fixed assets | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 |

2 | Capital assets | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |

3 | Revenues | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 1 |

4 | Profit | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |

5 | Installed capacity | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 |

6 | Volume of electricity generation | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 |

7 | Yearly average number of employees | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 1 |

8 | Cost of electricity generation | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 |

Matrix of coincidences for 2019 (developed by the authors)

Index _{ij} |
Indicator in the dynamic normal _{ij} |
Index _{ij} |
|||||||
---|---|---|---|---|---|---|---|---|---|

1 | 2 | 3 | 1 | 5 | 6 | 1 | 8 | ||

1 | Discounted value of fixed assets | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 1 |

2 | Capital assets | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 |

3 | Revenues | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 |

4 | Profit | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 |

5 | Installed capacity | 0 | 0 | 1 | 1 | 0 | 1 | 1 | 1 |

6 | Volume of electricity generation | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 1 |

7 | Yearly average number of employees | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 1 |

8 | Cost of electricity generation | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 |

Factorization of the increment of the assessment by indicators in the dynamic normal for Rosenergoatom Concern JSC (developed by the authors)

Indicator in the dynamic normal | Δ_{i} |
---|---|

1. Discounted value of fixed assets | 0.041667 |

2. Capital assets | 0.020833 |

3. Revenues | 0.020833 |

4. Profit | 0.145833 |

5. Installed capacity | 0.041667 |

6. Volume of electricity generation | 0.062500 |

7. Yearly average number of employees | 0.020833 |

8. Cost of electricity generation | 0.020833 |

^{-th}All-Russian Scientific Conference of Young Scientists “Reforms in Russia and Management Problems". Moscow. April 17–18, 2019. State University of Management Publ., Moscow, 165–167. [in Russian]

* Russian text published: Izvestiya vuzov. Yadernaya Energetika (ISSN 0204-3327), 2021, n. 3, pp. 121–133.