Forming a Risk Management System Based on the Process Approach in the Conditions of Economic Transformation
Abstract
:1. Introduction
2. Results
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- The working group of the project is determined and powers are distributed;
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- The scope of the risk management processes is planned;
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- The separation of processes, procedures, functions, goals and objectives is carried out;
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- The relationships between all projects of an enterprise are distributed;
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- Methodologies for assessing possible risks are determined;
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- The criteria for assessing the effectiveness of the risk management system are established;
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- The scope and limitations of the planned research and the required resources are determined.
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- Termination of actions related to one or more risks;
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- Finding an opportunity to avoid negative consequences;
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- Implementation of measures to reduce the impact of negative consequences of risk;
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- Measures to reduce damage from possible consequences;
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- Distribution of risk between several parties (Kostyukhin 2021).
3. Discussion
- The presence or absence of the influence of factors Xi on the indicators of Yj and if there are any, the evaluation of the signs of influence. The sign (+) records the fact of an increase in the level of the indicator Yj with an increase in the factor Xi influencing it. The sign (–) records a decrease in Yj with an increase in Xi.
- The duration of the periods of inertia of the identified factor influences.
- The intensity of the influence of the identified factors on the indicators.
- (1)
- The absence of a particular factor influences the indicators in the materials of the collective examination in the absence of references to them in publications (this was assessed by the coincidence of the “white background” and the “0” sign in the matrix cells);
- (2)
- The presence of a particular factor influences the indicators identified by the materials of the collective examination, when they were mentioned in publications (this was determined by the coincidence of the “gray background” and the “+” sign in the matrix cells).
- Project management. This includes an increase in the project implementation time, exceeding the project budget and poor quality.
- Business development. The main risk markers are defined as difficulties in participating in transactions that increase the value of the enterprise, overpayment for a transaction or inaccurate analysis, leading to insufficient return on capital investments.
- Violation of legal and regulatory requirements. This risk includes non-compliance with laws and regulations regarding the prevention of bribery, corruption, money laundering, sanctions, listing rules, and antitrust requirements.
- Management capabilities. The inability of management to attract, retain and develop the professionalism of key managers is considered.
- Organisational development. This arises from inefficient delegation of authority, in which management structures and systems can adversely affect the achievement of strategic goals.
- Liquidity. The risk arises when payment obligations are not fulfilled and the company’s ability to attract financing is reduced, or there is a lack of financial resources to complete projects, as well as business development activities.
- Political risk. This risk arises from strategic and financial losses, as well as personnel losses as a result of macroeconomic and social policies, or events related to political instability on the world stage.
- Productivity. This affected the metallurgical enterprises in many countries following the previous commodity boom in the period of market stagnation.
- Growth of socio-environmental requirements. This risk includes projects whose implementation has been postponed or stopped at the request of the local community and environmental defenders, while enterprises are forced to take into account measures aimed at obtaining and retaining a social license in their strategic development plans.
- Prices. The volatility of metal prices and exchange rates causes uncertainty in the estimates of the market value of the company’s assets, which affect the possibility of transactions.
4. Conclusions
- In order to form a risk management system at the enterprise, key components of the risk management mechanism were identified. They were united by the concept of performance management focused on creating additional enterprise value. Using the data of the analysis of risk management problems in the framework of increasing the potential of the enterprise, one of the main tasks was identified: ensuring the integration of its components of the mechanism. Carrying out structural reform by industry affiliation increased the effectiveness and efficiency of measures to reduce possible risks.
- The use of quantitative indicators of the efficiency of business processes, such as EBITDA, net profit, etc., allowed the optimal ratio between risk and profitability to be controlled across the entire enterprise by reducing the likelihood of risks (Sidorova et al. 2021).
- Using the key components of the risk management mechanism and quantitative indicators of the effectiveness of business processes, a universal risk management system was formed, based on the proposed risk management model to minimize the financial risks of the enterprise.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Aswath, Damodaran, ed. 2011. Damodaran on Valuation: Security Analysis for Investment and Corporate Finance. New York: John Wiley & Sons, 696p. [Google Scholar]
- Barcho, Mariana K., Olga V. Otto, Hafis Ahmed oglu Hajiyev, Vadim O. Samusenkov, Lyudmila N. Korshunova, Natalia O. Vikhrova, and Nikolay N. Nikulin. 2020. Basic directions for forming perspective forms of agricultural integration. Entrepreneurship and Sustainability Issues 8: 960–71. [Google Scholar] [CrossRef]
- Blank, I. A., ed. 2004. Financial Management. Moscow: Finance and Statistics, 656p. [Google Scholar]
- Brinza, V. V., Y. Y. Kostyuchin, M. A. Suslova, and O. N. Perk. 2014. From future to present: Forecast modeling methodology application in value-based management. Ekonomika Promyshlennosti 2: 63–73. Available online: https://elibrary.ru/download/elibrary_21774841_32661721.pdf (accessed on 7 January 2022). [CrossRef]
- Brinza, V. V., Y. Y. Kostyukhin, and I. V. Fadeeva. 2016. Potential of modeling techniques organizational systems with matrix structure and the possibility of expanding their information base. Ekonomika Promyshlennosti [Economics of Industry] 3: 209–22. Available online: https://ideas.repec.org/a/ach/journl/y2017id542.html (accessed on 7 January 2022). [CrossRef] [Green Version]
- Bugrov, D. A. 2003. Metric of efficiency. Bulletin of McKinsey 3: 76–89. [Google Scholar]
- Duke, V. A. 2001. Data Mining. Study Course. Edited by V. A. Duke and A. P. Samoylenko. St. Petersburg: Peter, 368p. [Google Scholar]
- Dyubin, G. N. 1981. Introduction to Applied Game Theory. Edited by G. N. Dyubin and V. G. Suzdal. Moscow: Nauka, 336p. [Google Scholar]
- Filatov, Vladimir V., Natalia A. Zaitseva, Anna A. Larionova, Elena E. Rodina, Vasily I. Eroshenko, Natalia O. Vikhrova, and Oksana V. Takhumova. 2018. Socio-environmental aspects of the waste recycling organization. EurAsian Journal of BioSciences 12: 527–33. [Google Scholar]
- Filatov, Vladimir V., Natalia A. Zaitseva, Anna A. Larionova, Svetlana E. Maykova, Lidia A. Kozlovskikh, Vera Y. Avtonova, and Natalia. O. Vikhrova. 2019. Assessment of the socio-economic impact of the implementation of regional environmental programs for waste management. Ekoloji 28: 267–273. [Google Scholar]
- Gracheva, M. V. 2009. Risk Management of an Investment Project. Edited by M. V. Gracheva and A. B. Sekerin. Moscow: Unity-Dana, 544p. [Google Scholar]
- Hanggraeni, Dewi, Beata Ilusarczyk, LiyuAdhiKasari Sulung, and Athor Subroto. 2019. The Impact of Internal, External and Enterprise Risk Management on the Performance of Micro, Small and Medium Enterprises. Sustainability 11: 2172. [Google Scholar] [CrossRef] [Green Version]
- Iliukhin, V. V., and U. U. Kostiukhin. 2009. The mechanism of an estimation of risks of the metallurgical companies caused by instability and non-uniformity of development of economy. Russian Journal of Industrial Economics 1: 32–38. (In Russian). [Google Scholar] [CrossRef]
- Ivanova, Valentina N., Alexander L. Tatochenko, Gregory V. Jazev, Natalia A. Zaitseva, Anna A. Larionova, and Natalia O. Vikhrova. 2018. The use of regression analysis to estimate the prospects for the food industry development in the Russian Federation. Espacios 39: 5. Available online: http://www.revistaespacios.com/a18v39n22/a18v39n22p05.pdf (accessed on 10 January 2022).
- Kalyanov, G. N., ed. 1992. Modern CASE-Technologies. Moscow: IPU, 115p. [Google Scholar]
- Kini, R. L. 1981. Decision-Making under Many Criteria: Preferences and Substitutions. Edited by R. L. Kini and H. Raifa. Moscow: Radio and Communications, 360p. [Google Scholar]
- Kostygova, L. A., V. Y. Ershova, and L. N. Korshunova. 2020. Financial engineering is a tool for economic evaluation of a complex project for developing a gas field and creating a gas pipeline. Paper presented at the 20th International Multidisciplinary Scientific GeoConference SGEM 2020, Bulgaria, Sofia, August 18–24; pp. 259–66. [Google Scholar] [CrossRef]
- Kostyukhin, Y. Y. 2016. Enhancement of labor efficiency in coal mining industry. GornyiZhurnal 10: 41–44. [Google Scholar] [CrossRef]
- Kostyukhin, Y. Y. 2021. Managing the Progressive Growth of an Industrial Enterprise Based on the Use of Its Potential: Theory, Methodology on the Example of Enterprises of the Metallurgical Complex. Ph.D. thesis, RUDN University, Moscow, Russia; p. 308. [Google Scholar]
- Kostyukhin, Y. Y., D. Y. Savon, A. E. Safronov, and A. V. Zhaglovskaya. 2019. Improvement of industrial safety control in the coal sector. Mining Informational and Analytical Bulletin 6: 184–92. [Google Scholar] [CrossRef]
- Kruzhkova, G. V., Y. Y. Kostyukhin, and I. M. Rozhkov. 2018. Choice procedure for expedient composition of electronic waste. Mining Informational and Analytical Bulletin 9: 47–57. [Google Scholar] [CrossRef]
- Loveridge, D., ed. 2009. Foresigt: The Artand Science of Anticipating the Future. New York: Routledge, 282p. [Google Scholar]
- Malz, Allan M., ed. 2011. Financial Risk Management: Models, History, and Institutions. Hoboken: John Wiley and Sons, 864p. [Google Scholar]
- Muradov, I. V., E. Y. Sidorova, and L. N. Korshunova. 2020. Improving the classification of integration risks on example of the eurasian economic union. Paper presented at the 20th International Multidisciplinary Scientific GeoConference SGEM 2020, Albena, Bulgaria, August 18–24; pp. 293–300. [Google Scholar] [CrossRef]
- Ochaykin, K. D. 2015. Development of the Strategic Management System of Enterprises of the Real Sector of the Economy Based on Risk Management. Ph.D. dissertation, Kazan Federal University, Kazan, Russia. [Google Scholar]
- Philips, D. T. 1984. Methods of Network Analysis. Edited by D. T. Philips and A. Garcia-Diaz. Moscow: Mir, 496p. [Google Scholar]
- Pocheptsov, G. G. 2004. Strategic Analysis for Politics, Business and Military Affairs. Kiev: Dzvin, 333p. [Google Scholar]
- Prodanova, N. A., D. O. Bokov, L. V. Sotnikova, L. N. Korshunova, N. O. Vikhrova, and N. N. Nikulin. 2020. Research on the impact of the COVID-19 pandemic on global economic processes. International Journal of Pharmaceutical Research 12: 3062–70. [Google Scholar]
- Sadovsky, V. N., ed. 1974. Foundations of the General Theory of Systems. Moscow: Nauka, 279p. [Google Scholar]
- Shannon, R., ed. 1978. Simulation Modelingof Systems—Art and Science. Moscow: Mir, 302p. [Google Scholar]
- Sidorova, E. 2019. The main factors and conditions determining the feasibility of production of high-tech products based on the potential of applied research organizations. Paper presented at the 19th International Multidisciplinary Scientific GeoConference SGEM 2019, Albena, Bulgaria, June 28–July 7; pp. 841–47. [Google Scholar] [CrossRef]
- Sidorova, E. Y. 2020. Formation of economically sound tax consequences on purchase and sale of foreign goods (case study on customs procedure of customs warehouse). Finance: Theory and Practice 24: 60–72. [Google Scholar] [CrossRef]
- Sidorova, E. Y., N. N. Nikulin, N. O. Vikhrova, and V. Y. Ershova. 2021. Labour productivity in the metallurgical industries of RussianFederation and the USA in 2010–2018. CIS Iron and Steel Review 21: 92–97. [Google Scholar] [CrossRef]
- Sidorova, E. Y., Y. Y. Kostyukhin, and V. A. Shtansky. 2020. Evaluation of scientific knowledge potential used for the production of high-tech products. Paper presented at the 20th International multidisciplinary scientific Geoconference SGEM 2020 (Ecology, Economics, Education and Legislation), Bulgaria, Sofia, August 8–24; pp. 241–48. [Google Scholar] [CrossRef]
- Sobocka-Szczapa, Halina. 2021. Recruitment of Employees—Assumptions of the Risk Model. Risks 9: 55. [Google Scholar] [CrossRef]
- Sychev, M. I. 2017. Methodology for risk analysis of using the strategic potential of the organization. Innovacionnoerazvitieekonomiki [Innovative Development of the Economy] 4: 199–205. Available online: https://www.elibrary.ru/download/elibrary_30102837_34463479.pdf (accessed on 15 January 2022). (In Russian).
- Tertychnaya, N. V., E. V. Sychev, and M. V. Filonov. 2016. Financial risk management in capacity development. Ekonomika Menedzhment Innovacii [Economy Management Innovations] 2: 47–53. Available online: https://www.elibrary.ru/item.asp?id=29821762 (accessed on 6 February 2022).
- Tolstykh, Tatyana O., Elena V. Shkarupeta, YuriyY. Kostuhin, Anna V. Zhaglovskaya, and Alexander P. Garin. 2020. Scenarios for the Development of Industrial Complexes in the Digital Economy. Lecture Notes in Networks and Systems.Springer Nature 73: 1255–61. [Google Scholar] [CrossRef]
- Trukhaev, R. I., and I. S. Gorshkov. 1985. Factor Analysis in Organizational Systems. Moscow: Radio iSvyaz, 185p. [Google Scholar]
- Vikhrova, N., E. Eliseeva, E. Sidorova, and L. Korshunova. 2020. Economic rationale for the operation of the circulation system of water use in nhermal power plants. Paper presented at the 20th International Multidisciplinary Scientific GeoConference SGEM 2020, Albena, Bulgaria, August 16–25; pp. 203–8. [Google Scholar] [CrossRef]
Preparation Stage | Decision-Making Stage | Implementation Stage |
---|---|---|
Stage 1. Situation analysis | Stage 4. Development of alternatives | Stage 8. Implementation of risk compensation methods |
Stage 2. Problem identification | Stage. 5. Multi-scenario forecasting | Stage 9. Monitoring and control of results |
Stage 3. Defining a selection criteria | Stage 6. Choosing the best alternative | |
Stage 7. Approval of the decision |
Parameter | Features of Modelling Characteristics for the Qualitative Method |
---|---|
Lead times | Obtaining interrelated short-term (3–5 years), medium-term (5–7 years), long-term (7–10 years), and the most very long-term (10–20 years or more) forecasts of system development |
External environment | Considering the relationship of the complex system with environmental factors |
Scale | Achieving multi-level forecasts of systems development (at mega-, macro-, meso-, micro-levels) |
Content | The number of interacting factors of the system taken into account ranges from tens to several hundred |
Reliability | Ensuring maximum objectivity of forecasting results and assessment of their reliability on several independent grounds |
Comparability | Simultaneous consideration and comparability of factors and predicted indicators of different nature (of different dimensions) |
Multiscenarity | Generation of multi-scenario forecasts of the development of the simulated system for the main expected combinations of elements of the external environment |
Risk assessment | Assessment of the consequences of the main risks, conflicts, instability of the external environment |
Key factors | Identification of key factors and “black holes” |
Compositionality | Low cost of rebuilding and combining models |
№ | Factor Number | Factor Name |
---|---|---|
1. | X1 | The degree of managerial influence of the president and top management on the company’s activities |
2. | X2 | The amount of financial resources used to ensure the current activities and development of the enterprise |
3. | X3 | Efficiency of financial and economic activity |
4. | X4 | The scale of the program of strategic and innovative development of the enterprise’s production |
5. | X5 | Quality policy |
6. | X6 | Human resources of the company’s management |
7. | X7 | Automation, informatization, and communication technologies in the company’s activities |
8. | X8 | The level of support for design and construction works |
9. | X9 | Safety service |
10. | X10 | Generalised potential of the production base of the enterprise |
11. | X11 | Activities in the field of environmental protection, labour protection, safety, fire safety |
12. | X12 | The cost of production at enterprises |
13. | X13 | Energy saving efficiency |
14. | X14 | Level of production diversification |
15. | X15 | Completeness of fulfilment of social obligations |
16. | X16 | The level of capitalization of the enterprise |
№ | Nature of Elements Influence | Factor Number | Factor Name |
---|---|---|---|
1. | Direct influence | X17 | The degree of impact on the metallurgical enterpriseby the parent company |
2. | X18 | Sales volumes of products produced by the enterprise to consumers | |
3. | X19 | The company’s relationship with suppliers | |
4. | X20 | Volumes of attracted external financial investments | |
5. | X21 | Activities of competing enterprises | |
6 | Indirect influence | X22 | Dynamics of socio-economic development |
7. | X23 | The level of state support for the enterprise | |
8. | X24 | The global socio-political situation | |
9. | X25 | The extent of international efforts to protect the global environment | |
10. | X26 | Scientific and technical progress in the metallurgical industry | |
11. | X27 | Stability of the world currency and financial markets | |
12. | X28 | The level of the world oil and other energy prices | |
13. | X29 | Demand in the world of metal products containing chromium | |
14. | X30 | The pace of development of the Chinese economy |
Factor Number | Lead Time Years | The Difference between Yj in the Forecast Realizing the Risk of “Project Management” and in the Inertial Forecast | ||||||
---|---|---|---|---|---|---|---|---|
0 | 1 | 2 | 3 | 4 | 5 | 6 | ||
X10-1 | 1.2 | 1.11 | 1.06 | 0.99 | 0.95 | 0.751 | 0.57 | −0.872 |
X10-2 | 1.23 | 1.18 | 1.15 | 1.03 | 0.99 | 0.830 | 0.63 | −0.862 |
X10-3 | 0.9 | 0.86 | 0.83 | 0.73 | 0.72 | 0.581 | 0.45 | −0.568 |
X10-4 | 1.18 | 1.15 | 1.13 | 0.99 | 0.95 | 0.769 | 0.57 | −0.861 |
Factor Number | Lead Time Years | The Difference between Yj in the Forecast Realizing the Risk of “Business Development” and in the Inertial Forecast | ||||||
---|---|---|---|---|---|---|---|---|
0 | 1 | 2 | 3 | 4 | 5 | 6 | ||
X10-1 | 1.2 | 1.16 | 1.12 | 1.09 | 1.09 | 1 | 0.92 | −0.527 |
X10-2 | 1.23 | 1.23 | 1.2 | 1.14 | 1.14 | 1.08 | 0.98 | −0.52 |
X10-3 | 0.9 | 0.86 | 0.83 | 0.78 | 0.79 | 0.72 | 0.66 | −0.359 |
X10-4 | 1.18 | 1.15 | 1.13 | 1.06 | 1.06 | 0.98 | 0.88 | −0.546 |
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Sidorova, E.; Kostyukhin, Y.; Korshunova, L.; Ulyanova, S.; Shinkevich, A.; Ershova, I.; Dyrdonova, A. Forming a Risk Management System Based on the Process Approach in the Conditions of Economic Transformation. Risks 2022, 10, 95. https://doi.org/10.3390/risks10050095
Sidorova E, Kostyukhin Y, Korshunova L, Ulyanova S, Shinkevich A, Ershova I, Dyrdonova A. Forming a Risk Management System Based on the Process Approach in the Conditions of Economic Transformation. Risks. 2022; 10(5):95. https://doi.org/10.3390/risks10050095
Chicago/Turabian StyleSidorova, Elena, Yuri Kostyukhin, Lyudmila Korshunova, Svetlana Ulyanova, Alexey Shinkevich, Irina Ershova, and Alena Dyrdonova. 2022. "Forming a Risk Management System Based on the Process Approach in the Conditions of Economic Transformation" Risks 10, no. 5: 95. https://doi.org/10.3390/risks10050095
APA StyleSidorova, E., Kostyukhin, Y., Korshunova, L., Ulyanova, S., Shinkevich, A., Ershova, I., & Dyrdonova, A. (2022). Forming a Risk Management System Based on the Process Approach in the Conditions of Economic Transformation. Risks, 10(5), 95. https://doi.org/10.3390/risks10050095