Modeling Economic Risks in Megacities

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Abstract

At the megacity level, in contrast to the regional or national level, economic risks are multidimensional and interconnected, necessitating the application of mathematical modeling for their identification and assessment. The sustainable development of megacities is impossible without a comprehensive analysis of threats. This article systematizes the main groups of megacity risks: financial-economic, socio-economic, infrastructural and spatial, environmental, resource-related, technological, and digital. Risks do not exist in isolation but form a network of mutual influence; the materialization of one risk increases the probability of others. To formalize the analysis, a probabilistic model based on the Kolmogorov axiomatics is employed to estimate the probability of an event occurrence and the magnitude of its impact. A network-based dynamic model is constructed to describe the mutual influence of risks and their evolution over time, thereby accounting for cascade effects and enabling more accurate forecasting of consequences. The proposed models can be utilized by government bodies and business entities for strategic planning, enhancing investment attractiveness, and minimizing the negative impacts of crisis situations.

About the authors

A. A. Kurkin

Nizhny Novgorod State Technical University n. a. R. E. Alekseev

Email: aakurkin@nntu.ru
SPIN-code: 1390-3940
Advanced Doctor of Physics and Mathematics, Professor, Vice-Rector for Research 24 Minina ulitsa, Nizhniy Novgorod, 603155, Russia

References

  1. Akimov V. A., Porfiriev B. N. Crises and Risk: on the Issue of the Concepts' Interrelationship. Issues of Risk Analysis, 2004, no. 1, pp. 38-49. (In Russ.).
  2. Borodushko I. V., Maksimov Yu. A. Economical Risks in Modern Society: Concept, Types, Assessment Methods. Petersburg Economic Journal, 2017, no. 3, pp. 24-32. URL: https://cyberleninka.ru/article/n/ekonomicheskie-riski-v-sovremennom-obschestve-ponyatie-vidy-metody-otsenki (accessed: 25.08.2025). (In Russ.).
  3. Gluschenko V. M., Shamin R. V. The Mathematics of City Management. MMGU Herald, 2024, no. 4, pp. 30-35. (In Russ.).
  4. Isakov D. A., Nikolaev V. A. Sovershenstvovanie Sistemy Upravleniya Riskami v Munitsipalʼnykh Ekonomicheskikh Sistemakh [Improving the Risk Management System in Municipal Economic Systems]. Moscow: MAX Press, 2008. 51 p. (In Russ.).
  5. Covello V. T., Merkhofer M. W. Risk Assessment Methods, Plenum Press. New York; London, 1993. 318 p.
  6. United Nations. New Urban Agenda. Habitat III. Quito. 17-20 October 2016. Habitat III Secretariat, 2017. Available at: https://habitat3.org/wp-content/uploads/NUA-English.pdf (accessed: 26.07.2025).
  7. Rinaldi S. M., Peerenboom J. P., Kelly T. K. Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Systems Magazine, 2002, vol. 21, no. 6, pp. 11-25. doi: 10.1109/37.969131.

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