Modeling market adaptation and regulatory flexibility for fuel supply resilience
Farias Duque, Jardel and Moura, Raphael and Patelli, Edoardo; (2026) Modeling market adaptation and regulatory flexibility for fuel supply resilience. In: Proceedings of the 36th European Safety and Reliability Conference. Research Publishing Services, PRT. (In Press)
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Abstract
Fuel supply chains are critical infrastructures exposed to disruptions, price volatility, and regulatory constraints. While computational models are increasingly used to assess supply chain resilience, most assume fully rational agents. This paper relaxes that assumption by incorporating loss aversion — a core feature of bounded rationality — into a three-echelon spatial competition model of a fuel supply chain. Buyers evaluate supplier choices through a reference-dependent utility function in which losses weigh more heavily than equivalent gains, parameterized by a loss aversion coefficient λ. Using agent-based simulation across multiple λ values, we analyze how behavioral preferences affect equilibrium prices, convergence dynamics, and system response to price shocks. Results show that higher loss aversion increases equilibrium landed costs and accelerates convergence under baseline conditions. However, under large perturbations, loss-averse markets exhibit persistent oscillations not observed in the loss-neutral benchmark. The study contributes a methodological extension to supply chain resilience modeling by demonstrating that bounded rationality is not a marginal refinement but a structural determinant of system behavior. Incorporating behavioral realism is therefore an option for developing more credible stress-testing tools and decision-support frameworks for critical supply chains.
ORCID iDs
Farias Duque, Jardel
ORCID: https://orcid.org/0009-0008-1686-0677, Moura, Raphael and Patelli, Edoardo
ORCID: https://orcid.org/0000-0002-5007-7247;
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Item type: Book Section ID code: 96221 Dates: DateEvent2 April 2026Published2 April 2026AcceptedSubjects: Technology > Engineering (General). Civil engineering (General)
Social Sciences > Economic Theory > Methodology > Mathematical economics. Quantitative methodsDepartment: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 11 May 2026 11:57 Last modified: 03 Jun 2026 10:54 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/96221
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