Robust pricing and inventory decisions in ship-from-store omnichannel operations

Abstract

This work studies the deployment of the ship-from-store omnichannel strategy and the pricing and inventory decisions for an online retailer. Robust optimization models are constructed for the online-only and the ship-from-store modes under a budgeted uncertainty set. The ARIMA model is used to predict the parameter values of the budgeted uncertainty set using historical demand data. The closed-form optimal solution for the online-only mode is obtained. The robust counterpart model for the ship-from-store mode is converted to a mixed integer quadratic programming model. Numerical studies are conducted to validate the theoretical results and to verify the effectiveness and practicality of the developed robust optimization solution approach. The results show that adopting a ship-from-store strategy may hurt the retailer's profit if a significant proportion of consumers are time-sensitive with high travel cost. The ship-from-store strategy is optimal if it significantly boosts market growth.