A probabilistic framework to design the financing scheme for resilience enhancement of infrastructure systems

Nima Moghimi and Hamed Kashani

Reliability Engineering and System Safety, 2025, vol. 262, issue C

Abstract: Financing resilience enhancement initiatives, such as seismic retrofits, can be challenging due to the lack of a tangible project return. This study investigates the taxation of the sectors that benefit from the resilience enhancement of the infrastructure systems to finance the said initiatives. It presents an analytical framework comprising multiple probabilistic modules, which examine how various resilience strategies can reduce the losses that the community sustains when components of an infrastructure system are damaged and the downstream businesses experience interruptions due to the loss of service. The framework quantifies the impact of various strategies and feeds this information into a simulation-based optimization model to determine the optimal allocation of funds for resilience enhancement of infrastructure components. It then evaluates how different downstream sectors benefit from the optimal strategy to design a taxation scheme that supports financing these interventions. The contribution of each sector is determined based on its expected avoided losses, ensuring a fair and efficient funding mechanism. To illustrate the capabilities of the proposed framework, it is applied to the case of enhancing the seismic resilience of the oil infrastructure in Iran. The results indicate that the increase in avoided production losses across downstream industries significantly outweighs the costs of retrofitting. By taxing these sectors based on their avoided losses, a stable and indirect revenue stream can be established to finance resilience enhancement projects effectively.

Keywords: Resilience enhancement; Business interruption; Network infrastructure systems; Simulation-based optimization; Cost-benefit analysis; Taxation; Probabilistic analysis; Project finance (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025003801

DOI: 10.1016/j.ress.2025.111179

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