arXiv:2606. 13741v1 Announce Type: new Abstract: This paper presents the design, development, and implementation of a specialized forecast-then-optimize algorithmic pricing tool for sales campaigns in fashion e-commerce.
arXiv:2606. 26787v1 Announce Type: cross Abstract: Traditional dynamic pricing models in large-scale e-commerce suffer from limited interpretability, poor utilization of unstructured information, and misalignment with long-term business objectives such as cumulative Gross Merchandise Value (GMV), Return on Investment (ROI) and milestone achievement.
arXiv:2606. 16183v1 Announce Type: cross Abstract: We develop an LLM-powered virtual population model that simulates demand for pricing decisions, in settings where products are described by rich unstructured information, such as text descriptions and images, and where decision makers need not only mean-demand predictions but also uncertainty estimates for counterfactual prices.
arXiv:2607. 13331v1 Announce Type: new Abstract: Retail demand forecasts are reused across replenishment, capacity, labor, and transportation planning cycles.
arXiv:2607. 16354v1 Announce Type: cross Abstract: Retail demand forecasting remains difficult when demand shifts faster than static forecasting models can be retrained, especially in early demand cycles where newly observed labels are sparse.
arXiv:2608. 12674v1 Announce Type: new Abstract: Maintaining price consistency and executing an Every Day Low Price strategy is critical for global retailers.
arXiv:2608. 12680v1 Announce Type: cross Abstract: Item demand forecasting is an integral component of store assortment optimization.
arXiv:2606. 11118v1 Announce Type: new Abstract: We study a dynamic assortment problem on a two-sided service platform with incomplete information and heterogeneous customers in a discrete-time setting.
arXiv:2607. 09956v1 Announce Type: new Abstract: Pricing food products to balance profitability with consumer welfare is a central challenge for retailers.
Large-scale retail and industrial forecasting systems contain many heterogeneous time series whose lifecycle, sparsity, volatility, seasonality, spectral patterns, and contextual sensitivity differ substantially. A single forecasting model rarely performs well across all regimes, while dense ensembles increase inference cost and provide limited insight into expert suitability.
arXiv:2606. 17931v1 Announce Type: new Abstract: In recent years, electronic (E) commerce services have rapidly increased in the daily lives of people, which helpsthem to purchase products online.
arXiv:2607. 16230v1 Announce Type: cross Abstract: Accurate pre-order shipping cost estimation is important in e-commerce because it affects price presentation, margin planning, and conversion.
arXiv:2606. 08896v1 Announce Type: new Abstract: Large-scale retail and industrial forecasting systems contain many heterogeneous time series whose lifecycle, sparsity, volatility, seasonality, spectral patterns, and contextual sensitivity differ substantially.