An Adaptive Model Selection Framework for Demand Forecasting under Horizon-Induced Degradation to Support Business Strategy and Operations

arXiv:2602.13939v3 Announce Type: replace-cross Abstract: Business environments characterized by intermittent demand, high variability, and multi-step planning horizons require forecasting policies that support consistent operational decisions across heterogeneous SKU portfolios. Because no forecasting model is universally dominant, and model rankings vary across error metrics, demand regimes, and forecast horizons, forecasting model assignment is a nontrivial decision problem in inventory plann