Integrated inventory and markdown strategies for durable goods under uncertainty

A permanent reduction in the price of an item over time is known as a "markdown." Industries like consumer electronics and fashion apparel use markdown strategies to clear their stock over time. These industries are known as markdown industries. We develop stylized mathematical models for markdown industries with a focus on durable goods such as consumer electronics. Owing to continuously shrinking product life cycles, the focus of our research is on shorter horizon models. Our models are suitable for both the retailer selling a short life cycle product and the manufacturer producing/assembling a short life cycle product in a direct to customer environment. We study a single item, periodic review, two-period problem. Our goal is to characterize optimal markdown and inventory policies for the two-period problem that maximize the expected total profit. Most of the research papers in the area of integration of pricing and inventory models assume the population of potential customer to be infinite. We study a model where the size of potential buyers is fixed (may be unknown). That is, there are a finite (possibly unknown) number of potential customers with heterogeneous valuation of the product. If a customer makes the purchase, he is removed from the population of potential customers. The population of potential customers who are willing to buy the product in a period is characterized by the probability distribution of the value customers attach to the product. The customers with high valuation buy the product as soon as the product is launched in the market while customers with low valuation wait till the price decreases below their valuation. In order to capture additional customers the manufacturer/retailer has to reduce the price of the item over time. In our first model we capture the markdown phenomenon for the known customer pool size case and characterize the optimal pricing strategy. We extend our first model to the case where the potential customer pool size is unknown and study the two-period model. We characterize the optimal inventory and pricing strategies for two-period model under uncertainty.