Modeling Investments in Technical Renewal and Growth of EsG Rating of Companies
https://doi.org/10.26794/1999-849X-2024-17-3-106-114
Abstract
The subject of the study is the accelerated technical and economic development of Russia in order to achieve national goals, which requires the creation of a special mechanism for the formation and implementation of investment projects within the framework of public administration. Simultaneously with technical, technological and economic development, the requirements of the green economy must be fulfilled, which are specified using ESG criteria. The aim of the work is to improve the rating of companies through effective investments while simultaneously implementing projects aimed at technical infrastructure renovation.
The result of the work was the creation of an economic and mathematical model that allows you to choose projects aimed at increasing the ESG rating of companies and implementing technical updates, including import substitution with domestic analogues or the implementation of technical and technological innovations. Based on an overview of a wide range of methods and algorithms for finding solutions to an optimal set of projects within the framework of a mathematical programming model with Boolean variables, it is proposed to use a modification of the Faure and Malgrange method, the algorithm of which is given in the text of the article.
The conclusions are drawn that the generated model and the given algorithm are a flexible tool that allows you to obtain a set of projects that require minimal investment within the limits of restrictions on the indicators of technical renewal of the company and the values of ESG criteria for different companies and using a different number of criteria.
About the Authors
I. Yu. NovoselovaRussian Federation
Irina Yu. Novoselova — Dr. Sci. (Econ.), Prof. of Department of Industry Markets, Chief Researcher of the Institute of Financial and Industrial Policy of the Faculty of Economics and Business, Faculty of Economics and Business.
Moscow
A. L. Novoselov
Russian Federation
Andrey L. Novoselov — Dr. Sci. (Econ.), Prof. of Department of Oil and Gas Industry Economics.
Moscow
References
1. Danilina M. V., Saveleva E. Yu. Analysis of foreign practice of ESG rating. Ekonomika: vchera, segodnya, zavtra = Economics: Yesterday, Today and Tomorrow. 2023;13(7А):198–213. (In Russ.). DOI: 10.34670/AR.2023.23.83.020
2. Khachatryan H.V. Divergence of ESG Ratings: foreign regulatory trends. Finansovyy zhurnal = Financial Journal. 2022;14(5):89–104. (In Russ.). DOI: 10.31107/2075–1990–2022–5–89–104
3. Volodina A. S., Chukhnenko I. A., Adamovich M. Development of ESG principles in the Russian economy. Biznes i dizayn revyu = Business and design review. 2023;30(2):17–24. (In Russ.).
4. Khvorostyanaya A.S. ESG-strategizing of industrial companies: domestic and foreign experience. Еkonomika promyshlennosti = Economics of industry. 2022;15(3):334–343. (In Russ.). DOI: 10.17073/2072–1633–2022–3–334–343
5. Divaeva E. A. Conditions for the transformation of ESG principles: economic and social aspects. Innovatsii i investitsii= Innovation and investment.2022;(1):65–70. (In Russ.).
6. Shigapova A. A. Considering ESG factors in the management of innovative projects. Vestnik Povolzhskogo gosudarstvennogo tekhnologicheskogo universiteta. Seriya: Ekonomika i upravleniye = Bulletin of the Volga State Technological University. Series: Economics and management. 2022;55(4):110–117. (In Russ.).
7. Shadrunova I. V., Zelinskaya E. V., Orekhova N. N., Gorlova O. E., Chekushina T. V. ESG-transformation in processing of man-made mineral raw materials. Gornaya promyshlennost’ = Mining Industry. 2023;(1):71–78. (In Russ.). DOI: 10.30686/1609–9192–2023–1–71–78
8. Wen H., Ho K. C., Gao J., Yu Li. The fundamental effects of ESG disclosure quality in boosting the growth of ESG investing. Journal of International Financial Markets, Institutions & Money. 2022;81:101655. DOI: 10.1016/j.intfin.2022.101655
9. Baibakova T.V., Ovchinnikova A. A., Rudenko O.V., Cherepanova A. D. Analysis of Russian ESG ratings and approaches to assessing sustainable development. Dnevnik nauki = Diary of Science. 202311(83). (In Russ.). DOI: 10.51691/2541–8327_2023_11_17
10. Antamoshkin A. N., Masich I. S. Search algorithms for conditional pseudo-Boolean optimization. Sistemy upravleniya, svyazi i bezopasnosti = Control, communication, and security systems. 2016;(1):103–145. (In Russ.).
11. Zheng Zhu, Chao Fang, Helmut G. Katzgraber A generalized global update algorithm for Boolean optimization problems. Optimization Letters. 2020;14:2495–2514.
12. Shushi T. The optimal solution of ESG portfolio selection models that are based on the average ESG score. Operations Research Letters. 2022;50(5):513–516. DOI: 10.1016/j.orl.2022.07.008
13. Potravny I., Novoselov A., Novoselova I. The development of technogenic deposits as a factor of overcoming resource limitations and ensuring sustainability (case of erdenet mining corporation SOE in Mongolia). Sustainability. 2023;15(22):15807. DOI: 10.3390/su152215807
14. Petrov I.V., Novoselova I. Yu., Novoselov A. L. Modeling the corporate social responsibility program of coal companies in the Arctic region. Ugol’ = Coal. 2022;1152(3):53–58. (In Russ.). DOI: 10.18796/0041–5790–2022–3–53–58
15. Novoselov A., Potravny I., Novoselova I., Gassiy V. Social investing modeling for sustainable development of the Russian arctic. Sustainability. 2022;14(2):933. DOI: 10.3390/su14020933
Review
For citations:
Novoselova I.Yu., Novoselov A.L. Modeling Investments in Technical Renewal and Growth of EsG Rating of Companies. Economics, taxes & law. 2024;17(3):106-114. (In Russ.) https://doi.org/10.26794/1999-849X-2024-17-3-106-114