Scenario Modeling in Demand-Constrained Semiconductor Supply Chains

Semiconductor supply chains operate within highly complex, globally distributed networks that are often constrained by volatile demand, limited capacity, and technological dependencies. Scenario modeling serves as a critical decision-support tool for navigating these uncertainties, enabling stakeholders to simulate and evaluate alternative strategies across various constraints. This review paper examines a comprehensive range of modeling approaches including capacity planning simulations, inventory optimization frameworks, behavioral modeling, and technoeconomic assessments, all applied within demand-constrained semiconductor environments. Drawing on ten significant academic sources, the paper emphasizes how scenario-based analysis aids in enhancing responsiveness, resilience, and strategic alignment in supply networks. Particular attention is paid to allocation strategies, imperfect quality impacts, sense-and-respond systems, and discrete-event simulation. Through the integration of financial, operational, and behavioral variables, scenario modeling emerges as an essential framework for managing uncertainty and improving supply chain performance in the semiconductor industry.