Pricing Strategy with Reference Prices

Abstract

Price and inventory decisions are key levers of profit for firms. A manager needs to understand the impacts of pricing, ordering and stocking decisions not only on today's operations but also on future demand. In this dissertation we investigate these intertwining decisions by incorporating inter-temporal effects of pricing decisions through reference prices. We introduce three significant extensions to reference price models to provide more meaningful insight into pricing, inventory and ordering decisions. We first present a threshold reference model. The threshold model incorporates zones of insensitivity around expected price that moderate the reference impacts on demand. This provides a rigourous model that is flexible enough to handle different pricing strategies such as single everyday low pricing (EDLP), high-low pricing (HiLo) and other general price cycles. We develop two solution approaches and provide computational results. We next introduce a reference model with stochastic demand. There is considerable previous research supporting the consideration of variability in pricing and inventory decisions and this is especially true in the context of inter-temporal demand interactions based on pricing decisions. We find that the introduction of stochastic elements can actually increase or decrease the length of the price cycle for some consumers in a reference model depending on the parameters of the model. This extends the stochastic demand model and bridges to reference models for improved managerial insight. The final model presented is the dynamic lot sizing model. When prices and production decisions or order quantities are determined simultaneously the interactions need to be considered to optimize profits. The reference model incorporates the inter-temporal price effects to provide a clearer picture of the optimal decision. The inclusion of reference effects does change the optimal decision.