GHOLAMI, HAMED2026-05-062026-05-062026-05-062026-04-30https://hdl.handle.net/10012/23221Remote Arctic communities rely on ephemeral winter roads for the affordable delivery of essential goods. As climate change destabilizes the physical foundation of these supply chains, policymakers face a complex stochastic allocation problem: how to optimally divide a constrained budget between supply-side infrastructure investments (to extend road duration) and demand-side consumer subsidies (to bolster household purchasing power). In this thesis, we develop a stylized stochastic optimization model to analyze this trade-off, formulating a capacity-budget gap parameter to capture the dual-bottlenecks of physical throughput versus financial liquidity. We prove that the optimal funding strategy, serving as a stochastic hedge, is strictly bounded between the supply-constrained and demand-constrained deterministic solutions. Through comparative statics, we uncover counter-intuitive operational tradeoffs, including a price-affordability tradeoff and a logistics efficiency tradeoff, where improvements in supply chain economics rationally trigger infrastructure divestment due to an underlying income saturation effect. Furthermore, we analyze the compound effect of climate change: a secular decline in mean winter duration combined with rising interannual volatility. We demonstrate that for the most vulnerable communities, this compound shock pushes the system into a dilution state where higher volatility counter-intuitively reduces the optimal investment level. Our findings suggest that as climate uncertainty accelerates and mean operational windows shrink, relying on winter road infrastructure becomes economically unsustainable, necessitating a strategic policy pivot toward direct income support and alternative logistics.enMaster Thesis