DIGITAL TWIN–BASED DECISION SUPPORT FOR COST OPTIMIZATION AND RISK MANAGEMENT IN INFRASTRUCTURE SYSTEMS

Nelyufar Umarovna Dadabayeva

GREEN ECONOMY AND DEVELOPMENT, 2026, vol. 4, issue 2

Abstract: Infrastructure systems face increasing challenges related to cost overruns, operational uncertainty, and riskexposure throughout their lifecycle. Digital twin technology offers new opportunities to support data-driven decisionmakingand improve infrastructure performance. This study aims to develop and evaluate a digital twin-based decisionsupport framework for cost optimization and risk management in infrastructure systems. The methodology integratessystem modeling, real-time data synchronization, and scenario-based simulation within a digital twin environment.Quantitative methods, including lifecycle cost analysis and risk assessment indicators, are applied to compare alternativeinfrastructure management strategies. A case study of infrastructure assets in Eastern Uzbekistan is used to validate theproposed framework. The results indicate that the digital twin-based approach enables a reduction in projected lifecyclecosts by 15-22% and a decrease in risk exposure by up to 18% compared to conventional management methods.Sensitivity analysis confirms the robustness of the framework under varying levels of uncertainty. The practical value ofthis research lies in providing infrastructure managers and policymakers with a scalable decision-support tool to improveinvestment planning, operational efficiency, and risk-informed decision-making

Keywords: digital twin; infrastructure systems; cost optimization; risk management; decision support; asset management (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:teu:ged000:v:4:y:2026:i:2:id:9056

DOI: 10.5281/zenodo.18512647

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