A Model for Strategic Adaptation of Supply Chains and Recommendations for Their Development and Adaptation in Conditions of Economic Uncertainty

The relevance of research in the field of supply chain resilience has increased dramatically due to global crises such as the COVID-19 pandemic, geopolitical tensions and climate change. The article examines specific aspects of practical application of the methodology for quantitative assessment of the fault tolerance of supply chains, taking into account transport and logistics activities. A strategic adaptation model has been developed, which logically completes the development of a comprehensive QSCR methodology, transforming it from a passive analysis tool into an active tool for proactive management. It allows companies to quantify and compare various scenarios for the development of their supply chains; economically justify investments in improving reliability and digitalization; and move from a “firefighting” mode to systematic risk management, which is a factor in survival and competitiveness in the new economic reality. The implementation of this approach at the level of enterprises in the Republic of Belarus and the EAEU will improve the resilience of their business models, reduce their dependence on external shocks, and strengthen their position in regional and global value chains. Practical recommendations have been developed, grouped into three levels: corporate, industry (within the EAEU), and national.

1. Efimova E. G., Pinoniemi K. (2014) Political Factors in the Formation of Modern International Transport Infrastructure. St. Petersburg University Journal of Economic Studies (SUJES), (2), 32–55 (in Russian).

2. Nikitina E. I. (2018) International Logistics. Minsk, International Institute of Labor and Social Relations. 331 (in Russian).

3. Bowersox D. J., Closs D. J., Cooper M. B (2013). Supply Chain Logistics Management. McGraw-Hill. 484 (in Russian).

4. Brykalov S. M., Trifonov V. Yu., Netronin I. V., Smetanina E. A. (2024) Development of Risk and Opportunity Management Systems for the Company. Problemy Analiza Riska = Issues of Risk Analysis, 21 (1), 66–77 (in Russian).

5. Kosheleva T. N., Ksenofontova T. Yu., Gulyaeva O. A. (2024) Distribution Management of Interregio-nal Supply Chains within the Framework of Interaction with Artificial Intelligence Technologies. Bulletin of Scientific Research Results, (1), 97–106 (in Russian). https://doi.org/10.20295/2223-9987-2024-01-97-106

6. Krylatkov P. P., Prilutskaya M. A. (compiled) (2018) Supply Chain Management (SCM). Ekaterinburg, Publishing House of the Ural University. 140 (in Russian).

7. Podolskaya T. V., Sotnikov A. G. (2024) Implementation of Advanced Digital Technologies in the Transport and Logistics Sector in Modern Conditions. Voprosy Innovatsionnoy Ekonomiki = Russian Journal of Innovation Economics, 14 (4), 1479–1496. https://doi.org/10.18334/vinec.14.4.121649

8. Malikova Yu. A. (2024) Digital Transformation of Transport and Logistics Supply Systems. Vestnik Rostovskogo Gosudarstvennogo Universiteta (RINKh) = Vestnik of Rostov state University (RINH), (1), 37–44. https://doi.org/10.54220/v.rsue.1991-0533.2024.1.85.005

9. Khoroshilova T. N. (2025) Methods for Optimizing Supply Chains Using Digital Technologies. Modern Economy Success, (1), 397–410. https://doi.org/10.58224/2500-3747-2025-1-397-410

10. Lychkina N. N. (2011) Simulation Modeling of Economic Processes. Moscow, INFRA-M Publ. 254 (in Russian).

11. Butor L. V., Mironenko A. V., Kovalev B. O. (2023) Solution of Logistic Problems of a Warehouse Complex Using Simulation Modeling. Razvitie sovremennoi nauki i tekhnologii v usloviyakh transformatsionnykh protsessov: sb. materialov XV Mezhdunar. nauch.-prakt. konf., Moskva, 27 oktyabrya 2023 g. [Development of Modern Science and Technology in the Context of Transformation Processes: Collection of Materials of the 15th International Scientific-Practical Conference, Moscow, October 27, 2023]. Saint Petersburg, Pechatny Dvor Publ., 170–175 (in Russian).

12. Koroleva A. A. (2022) Mathematical Tools for Analyzing the Development of Transport Logistics in Belarus. Minsk, Publishing Center of the Belarusian State University. 279 (in Russian).

13. Larin O. N., Kapsky D. V., Kapsky P. D. (2024) State Model of a Resilient Supply Chain. Transport: science, equipment, management. Scientific Information Collection, (9), 3–7 (in Russian). https://doi.org/10.36535/0236-1914-2024-09-1

14. Larin O. N., Kapsky D. V., Kapsky P. D. (2025) Supply Chain Reliability Modeling. Transport: science, equipment, management. Scientific In-formation Collection, (1), 9–14 (in Russian). https://doi.org/10.36535/0236-1914-2025-01-2