Modeling Market Adaptation and Regulatory Flexibility for Fuel Supply Resilience

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 lossneutral 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 decisionsupport frameworks for critical supply chains.

Keywords: Bounded rationality, loss aversion, supply chain resilience, behavioral economics, fuel markets, agentbased modeling.