Managing Organizational Risks in Russia’s Oil and Gas Enterprises Based on Expert Assessment
https://doi.org/10.26794/2304-022X-2025-15-4-172-188
Abstract
The Comprehensive Security System (CSS) is designed to prevent the emergence and development of risks – technical, organizational-technical, and purely organizational – at enterprises within Russia’s oil and gas sector. This study focuses on reducing losses by assessing and managing organizational risks that arise from insufficient actions or shortcomings on the part of personnel responsible for ensuring the effective operation of the CSS. The aim of the research is to identify an approach
that makes it possible to convert qualitative indicators of organizational risks into quantitative terms (a measurable negative impact). In the course of the study, the author substantiates the use of an expert-based method (priority ranking) to evaluate risks associated with inadequate actions by management bodies that oversee subordinate personnel. This method has advantages and introduces elements of novelty compared with current solutions used in practice. When applied together with the functionality of the Gaussian probability distribution, it allows experts to determine specific safety areas in which organizational risks arise due to insufficient control measures. In real organizational systems, having reliable information with weighted values for all identified risks makes it possible to construct a ranked list, determine priorities, and develop a set of preventive measures. The article provides an example illustrating how personnel in various safety areas influence the overall state of the CSS, and it justifies the feasibility of applying the priority-ranking method in practice to obtain quantitative results for organizational risks.
About the Author
E. V. Gvozdev
Moscow State University of Civil Engineering
Russian Federation
Russian Federation
Evgeny V. Gvozdev – Cand. Sci. (Tech.), Assoc. Prof. of the Department of Mechanization, Automation and Robotics in Construction
Moscow
References
1. Gvozdev E. V. Methodology of risk assessment in the system of integrated safety designed to prevent accidents and fires at explosion and fire hazardous enterprises. Pozharovzryvobezopasnost’ = Fire and Explosion Safety. 2025;34(1):59–69. (In Russ.). DOI: 10.22227/0869-7493.2025.34.01.59-69
2. Mkrtchyan L., Straub U., Giachino M., Kocher T., Sansavini G. Insurability risk assessment of oil refineries using Bayesian Belief Networks. Journal of Loss Prevention in the Process Industries. 2022;74:104673. DOI: 10.1016/j.jlp.2021.104673
3. Makhutov N. A., Matvienko Yu.G., Romanov A. N., et al. Problems of strength, technogenic safety and structural materials science. Moscow: Lenand; 2018. 720 p. (In Russ.).
4. Grazhdankin A. I. Hazard analysis and risk assessment of major accidents in the oil, gas and coal industries. Doct. techn. sci. diss. Moscow: STC “Industrial Safety”; 2017; 340 p. (In Russ.).
5. Shargatov V. A., Sumskoi S. I., Pecherkin A. S. Simulation of gas release from pipelines using a new numerical method based on the Godunov approach. Journal of Physics: Conference Series. 2019;1205:012050. DOI: 10.1088/1742–6596/1205/1/012050
6. Oksman V. S., Tkachenko V. M., Fomintsova A. V., Grazhdankin A. I. On the methodological support for improvement of the state supervision over industrial safety conditions at objects of mining, metallurgical productions, and explosives in use. Bezopasnost’ truda v promyshlennosti = Occupational Safety in Industry. 2024;(5):26–35. (In Russ.). DOI: 10.24000/0409-2961-2024-5-26-35
7. Poroshin A. A., Udavtsova E. Yu., Bobrinev E. V., et al. Assessment of fire hazard level of industrial objects based on the statistical methods. Bezopasnost’ truda v promyshlennosti = Occupational Safety in Industry. 2020;(3):12–17. (In Russ.). DOI: 10.24000/0409-2961-2020-3-12-17
8. Vishnevsky V. P., Matyushin A. V., Stel’makhova N. V. Tax regulation of economic growth in the context of postcrisis recovery: Problems and prospects. Studies on Russian Economic Development. 2025;36(1):66–76. DOI: 10.1134/S1075700724700539 (In Russ.: Problemy prognozirovaniya. 2025;(1):109–123. DOI: 10.47711/0868-6351-208-109-123).
9. Denisov A. N., Poroshin A. A., Danilov M. M., et al. The genesis of development, modern realities of scientific, methodological and normative legal substantiation of the concepts of “large fire”, “complex (protracted) fire”. Pozharovzryvobezopasnost’ = Fire and Explosion Safety. 2025;34(2):5–19. (In Russ.). DOI: 10.22227/0869–7493.2025.34.02.5–19
10. Akimov V., Bedilo M., Derendiaeva O., Ivanova E., Oltyan I. Forecast of natural emergency situations with modern methods. Reliability: Theory & Applications. 2022;17(4):71–77. DOI: 10.24412/1932-2321-2022-470-71-77
11. Akimov V., Ivanova E., Oltyan I. S. Statistical models for forecasting emergency situations of a biological and social character. Reliability: Theory & Applications. 2023;18(4):41–45. DOI: 10.24412/1932-2321-2023-476-41-45
12. Cheng J., Greiner R., Kelly J., Bell D., Liu W. Learning Bayesian networks from data: An information-theory based approach. Artificial Intelligence. 2002:137(1–2):43–90. DOI: 10.1016/S 0004–3702(02)00191–1
13. Bochkov A. Reflections on dual nature of risk. Toward a formalism Reliability: Theory & Applications. 2023;18(S 5):44–74. DOI: 10.24412/1932-2321-2023-575-44-74
14. Gvozdev E. V. Intersystem interaction and relationships in the integrated safety system designed to prevent accidents and fires at explosion-and fire-hazardous enterprises. Bezopasnost’ truda v promyshlennosti = Occupational Safety in Industry. 2024;(12):40–46. (In Russ.). DOI: 10.24000/0409-2961-2024-12-40-46
15. Blumberg V. A., Glushchenko V. F. Which solution is better? The method of prioritization. Leningrad: Lenizdat; 1982. 160 p. (In Russ.).
16. Saaty T. L. Decision making for leaders: The analytical hierarchy process for decisions in a complex world. Maastricht: Lifetime Learning; 1982. 291 p. (Russ. ed.: Saaty T. Prinyatie reshenii. Metod analiza ierarkhii. Moscow: Radio i svyaz’; 1993. 320 p.).
17. Bellman R. E. Introduction to matrix analysis. New York, NY.: McGraw-Hill, Inc.; 1966. 360 p. (Russ. ed.: Bellman R. Vvedenie v teoriyu matrits. Moscow: Nauka; 1976. 352 p.).
18. Belikov A. B., Simonyan V. V. Mathematical processing of geodetic measurement results. Moscow: Moscow State University of Civil Engineering; 2016. 432 p. (In Russ.).
19. Alamdari A. M., Jabarzadeh Y., Adams B., Samson D., Khanmohammadi S. An analytic network process model to prioritize supply chain risks in green residential megaprojects. Operations Management Research. 2023;16(1):141–163. DOI: 10.1007/s12063-022-00288-2
20. Anokhin A. M., Glotov V. A., Paveliev V. V., Cherkashin A. M. Methods for determining coefficients of criteria importance. Avtomatika i telemekhanika = Automation and Remote Control. 1997;(8):3–35. (In Russ.).
21. Gvozdev E. V. The development of assessment model of personnel’s influence on the condition of the integrated safety system established at production plants. Bezopasnost’ truda v promyshlennosti = Occupational Safety in Industry. 2024;(2):7–15. (In Russ.). DOI: 10.24000/0409-2961-2024-2-7-15
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For citations:
Gvozdev E.V. Managing Organizational Risks in Russia’s Oil and Gas Enterprises Based on Expert Assessment. Management Sciences. 2025;15(4):172-188. (In Russ.) https://doi.org/10.26794/2304-022X-2025-15-4-172-188
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