This grant provides funding for research on the operational challenges faced by direct-to-consumer manufacturers who generate the bulk of their sales through catalogs. The business of such manufacturers is characterized by a high season during which peak demands occur. During the high season, as the demand unfolds and as some products emerge as fast-moving ones while the sales of others are dragging, the manufacturer must balance demand and supply so as to avoid significant shortages and overages. In overcoming this challenge, the manufacturer has two levers at their disposal. Firstly, they can schedule additional production for fast-moving items during the high season. Secondly, they can offer discounts on slow-moving products. The research will analyze, through a mathematical-model, how such a manufacturer should make production planning and markdown pricing decisions during the high season. In particular, the analysis will focus on how the manufacturer can optimally allocate its capacity among multiple fast-moving products, and how they can optimally decide which products to markdown, when and to what extent. In addition, quick solution methods will be devised, and the performance of these solution methods will be compared to the optimal solution.
If successfully implemented, the results of this research will enable direct-to-consumer manufacturers to make better decisions on production planning and markdown pricing. Furthermore, efficient discounting and production planning practices should lead to a better match between demand and supply, which is good for the consumer population as well. In addition, this research will contribute to the academic literature on dynamic pricing by analyzing a case where multiple products compete for both production resources and customer demand.
