Dynamic infrastructure risk management: real-world implementation and validation of the IRMM at Mastergaz

Yuri Chernenko; Olena Bielova; Oleksandr Bielov

doi:10.26906/EiR.2025.2(97).3797

Authors

Yuri Chernenko International University of Business and Law https://orcid.org/0000-0002-7008-7274
Olena Bielova University of Economics and Law “KROK” https://orcid.org/0000-0001-9359-6947
Oleksandr Bielov University of Economics and Law “KROK” https://orcid.org/0000-0002-4976-5501

DOI:

https://doi.org/10.26906/EiR.2025.2(97).3797

Keywords:

infrastructure risk management, infrastructure risk index, dynamic assessment, preventive planning, real-time data, project management, Mastergaz

Abstract

This study introduces and evaluates the Infrastructure Risk Management Method (IRMM), with particular emphasis on the Infrastructure Risk Index (IRI) as a quantitative measure to identify and mitigate risks in infrastructure projects. A two-year case study was conducted at Mastergaz, a leading infrastructure firm, involving fifty projects. Data were collected through structured interviews and surveys administered to project managers and field technicians. The IRI was calculated by integrating criticality, vulnerability, and external influences, and then analyzed in conjunction with historical performance metrics. The findings demonstrate a strong correlation between IRI values and observed failure rates, highlighting the IRMM’s predictive capability. Dynamic assessments allowed continuous monitoring and informed preventive strategies, such as maintenance schedules and contingency plans, thereby reducing infrastructure failures. Scalability was also evident, suggesting broader applicability in sectors like transportation and energy. By integrating real-time data and aligning with existing project management frameworks, the IRMM advances infrastructure risk management practices. This dynamic, proactive approach fosters improved decision-making and resilience in evolving operational environments, offering a valuable foundation for further research and practical implementation.

Author Biographies

Yuri Chernenko, International University of Business and Law

Doctoral Candidate of the Department of Management

Olena Bielova, University of Economics and Law “KROK”

PhD in Economics, Associate Professor of the Department of Marketing and Behavioral Economics

Oleksandr Bielov, University of Economics and Law “KROK”

PhD Student of the Department of Managerial Technologies

References

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28. Basri E. I., Kamaruddin S., Ab-Samat H., Abdul Razak I. H. (2017) Preventive maintenance (PM) planning: A review. Journal of Quality in Maintenance Engineering, no. 23(2), pp. 114–143. DOI: https://doi.org/10.1108/jqme-04-2016-0014

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2. Cavalieri F., Franchin P. Seismic risk of infrastructure systems with treatment of and sensitivity to epistemic uncertainty. Infrastructures. 2020. Vol. 5. No. 11. DOI: https://doi.org/10.3390/infrastructures5110103 DOI: https://doi.org/10.3390/infrastructures5110103

3. Kabir S., Papadopoulos Y. Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review. Safety Science. 2019. Vol. 115. P. 154–175. DOI: https://doi.org/10.1016/j.ssci.2019.02.009 DOI: https://doi.org/10.1016/j.ssci.2019.02.009

4. Cheimonidis P., Rantos K. Dynamic risk assessment in cybersecurity: A systematic literature review. Future Internet. 2023. Vol. 15. No. 10. DOI: https://doi.org/10.3390/fi15100324 DOI: https://doi.org/10.3390/fi15100324

5. Villa V., Paltrinieri N., Khan F., Cozzani V. Towards dynamic risk analysis: A review of the risk assessment approach and its limitations in the chemical process industry. Safety Science. 2016. Vol. 89. P. 77–93. DOI: https://doi.org/10.1016/j.ssci.2016.06.002 DOI: https://doi.org/10.1016/j.ssci.2016.06.002

6. De Felice F., Petrillo A., Baffo I. Critical infrastructures overview: Past, present and future. Sustainability. 2022. Vol. 14. No. 4. DOI: https://doi.org/10.3390/su14042233 DOI: https://doi.org/10.3390/su14042233

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8. Mottahedi A., Barabadi A., Ataei M., Nouri Qarahasanlou A., Sereshki F. The resilience of critical infrastructure systems: A systematic literature review. Energies. 2021. Vol. 14. No. 6. DOI: https://doi.org/10.3390/en14061571 DOI: https://doi.org/10.3390/en14061571

9. Rasheed N., Shahzad W., Khalfan M., Rotimi J. Risk identification, assessment, and allocation in PPP projects: A systematic review. Buildings. 2022. Vol. 12. No. 8. DOI: https://doi.org/10.3390/buildings12081109 DOI: https://doi.org/10.3390/buildings12081109

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12. Wang Y., Gong E., Zhang Y., Yao Y., Zhou X. Risk assessment of infrastructure REITs projects based on cloud model: A case study of China. Engineering, Construction and Architectural Management. 2023. Vol. 31. No. 11. P. 4330–4352. DOI: https://doi.org/10.1108/ecam-12-2022-1142 DOI: https://doi.org/10.1108/ECAM-12-2022-1142

13. Ward E. J. Mega infrastructure and strategic risk mitigation: Planning, management and outcomes. Journal of Mega Infrastructure & Sustainable Development. 2020. Vol. 2. P. 5–31. DOI: https://doi.org/10.1080/24724718.2022.2035553 DOI: https://doi.org/10.1080/24724718.2022.2035553

14. Li W., Yuan J., Ji C., Wei S., Li Q. Agent-based simulation model for investigating the evolution of social risk in infrastructure projects in China: A social network perspective. Sustainable Cities and Society. 2021. Vol. 73. DOI: https://doi.org/10.1016/j.scs.2021.103112 DOI: https://doi.org/10.1016/j.scs.2021.103112

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18. Pasino A., Clematis A., Ottonello D., De Angeli S., Battista U. A review of single and multi-hazard risk assessment approaches for critical infrastructures protection. International Journal of Safety and Security Engineering. 2021. Vol. 11. No. 4. P. 305–318. DOI: https://doi.org/10.18280/ijsse.110403 DOI: https://doi.org/10.18280/ijsse.110403

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21. Senić A., Stojadinović Z., Dobrodolac M. Development of risk quantification models in road infrastructure projects. Sustainability. 2024. Vol. 16. No. 17. DOI: https://doi.org/10.3390/su16177694 DOI: https://doi.org/10.3390/su16177694

22. Nabawy M., Khodeir L. M. Achieving efficiency in quantitative risk analysis process – Application on infrastructure projects. Ain Shams Engineering Journal. 2020. Vol. 12. No. 2. P. 2303–2311. DOI: https://doi.org/10.1016/j.asej.2020.07.032 DOI: https://doi.org/10.1016/j.asej.2020.07.032

23. Nguyen M. D., Nguyen H. B., Tran P. Q. An application of analytic network process (ANP) to assess critical risks of bridge projects in the Mekong Delta Region. Engineering, Technology & Applied Science Research. 2023. Vol. 13. No. 3. P. 10622–10629. DOI: https://doi.org/10.48084/etasr.5802 DOI: https://doi.org/10.48084/etasr.5802

24. Di Bona G., Forcina A., Falcone D., Silvestri L. Critical risks method (CRM): A new safety allocation approach for a critical infrastructure. Sustainability. 2020. Vol. 12. No. 12. DOI: https://doi.org/10.3390/su12124949 DOI: https://doi.org/10.3390/su12124949

25. Umar M., Akande D., Okwandu A. Innovations in project monitoring tools for large-scale infrastructure projects. International Journal of Management & Entrepreneurship Research. 2024. Vol. 6. No. 7. P. 2275–2291. DOI: https://doi.org/10.51594/ijmer.v6i7.1294 DOI: https://doi.org/10.51594/ijmer.v6i7.1294

26. Larsson A., Große C. Data use and data needs in critical infrastructure risk analysis. Journal of Risk Research. 2023. Vol. 26. No. 5. P. 524–546. DOI: https://doi.org/10.1080/13669877.2023.2181858 DOI: https://doi.org/10.1080/13669877.2023.2181858

27. Papadaki E., Kotsiantis S., Vrahatis A. G. Exploring innovative approaches to synthetic tabular data generation. Electronics. 2024. Vol. 13. No. 10. DOI: https://doi.org/10.3390/electronics13101965 DOI: https://doi.org/10.3390/electronics13101965

28. Basri E. I., Kamaruddin S., Ab-Samat H., Abdul Razak I. H. Preventive maintenance (PM) planning: A review. Journal of Quality in Maintenance Engineering. 2017. Vol. 23. No. 2. P. 114–143. DOI: https://doi.org/10.1108/jqme-04-2016-0014 DOI: https://doi.org/10.1108/JQME-04-2016-0014

29. Wu S., Zuo M. J. Linear and nonlinear preventive maintenance models. IEEE Transactions on Reliability. 2010. Vol. 59. No. 1. P. 242–249. DOI: https://doi.org/10.1109/tr.2010.2041972 DOI: https://doi.org/10.1109/TR.2010.2041972

30. Babayeju O., Ekemezie I., Sofoluwe O., Adefemi A. Advancements in predictive maintenance for aging oil and gas infrastructure. World Journal of Advanced Research and Reviews. 2024. Vol. 22. No. 3. P. 252–266. DOI: https://doi.org/10.30574/wjarr.2024.22.3.1669 DOI: https://doi.org/10.30574/wjarr.2024.22.3.1669

31. Figueredo G., Owa K., John R. Multi-objective optimization for time-based preventive maintenance within the transport network: A review. Preprint on ResearchGate. 2020. DOI: https://doi.org/10.13140/rg.2.2.36132.01929

32. Abdullah E. M. E., Abdullah M. H. S. B., Yakob R. A comprehensive review of enterprise risk management on higher education institutions performance. Asia Proceedings of Social Sciences. 2024. Vol. 12. No. 1. P. 20–24. DOI: https://doi.org/10.31580/rf6td074 DOI: https://doi.org/10.31580/rf6td074

33. Solano M. C., Cruz J. C. Integrating analytics in enterprise systems: A systematic literature review of impacts and innovations. Administrative Sciences. 2024. Vol. 14. No. 7. DOI: https://doi.org/10.3390/admsci14070138 DOI: https://doi.org/10.3390/admsci14070138

34. Wijesinghe S., Pathirana R., Nanayakkara I., Wickramarachchi R., Fernando I. Impact of IoT integration on enterprise resource planning (ERP) systems: A comprehensive literature analysis. Proceedings of the 2024 International Research Conference on Smart Computing and Systems Engineering (SCSE). 2024. P. 1–5. DOI: https://doi.org/10.1109/scse61872.2024.10550684 DOI: https://doi.org/10.1109/SCSE61872.2024.10550684

35. Samad M. A., Uddin S. M., Sabbir M. M., Rahman M. Enhancing organizational performance in Bangladeshi industries: The role of enterprise resource planning (ERP) systems. Asian Review of Mechanical Engineering. 2023. Vol. 12. No. 2. P. 19–27. DOI: https://doi.org/10.70112/arme-2023.12.2.4224 DOI: https://doi.org/10.70112/arme-2023.12.2.4224