An integrated model for online product placement and inventory control problem in a drop-shipping optional environment

Abstract

Abstract The growth of the Internet has revolutionized how retailers operate. Proper management of product display on product listing pages and inventory control not only increases profit but also decreases cost. Online retailers typically sell their products by using the following inventory strategies: drop-shipping, in-house, and hybrid (a combination of drop-shipping and in-house) strategies. This paper addresses the problem of retailers selling various items of the same product category by displaying a product in an array format over multiple pages. It is assumed that the visual stimuli of the image size and display position significantly affect product demand. In addition, the substitution effect of the items on product demand is considered. A continuous-review order quantity reorder point (Q, r) inventory model with a visual-attention-dependent demand rate is developed for solving the product placement and inventory control problem in a drop-shipping environment that allows retailers to use the hybrid strategy if a shortage occurs during lead time. A genetic algorithm (GA) is then proposed for deriving a solution to the model. The validity of the proposed model is illustrated using numerical examples. Furthermore, the effects of the model parameters on the solution for the model are examined.