Dynamic inventory system with pricing adjustment for price‐comparison shoppers

Abstract

AbstractWith numerous price‐comparison websites and applications, consumers today are frequently conducting price‐comparison shopping. As a result, retailers face an increasing challenge in predicting consumer demand and determining the optimal product price and inventory level accordingly. To address this issue, this paper proposes an inventory model with joint decisions of price and inventory to optimize the retailer's long‐run average profit under price‐comparison consumer shopping. We first formulate the demand arrival process for a retailer under price‐comparison shopping to be affected by not only its own price but also its competitors'. Based on this demand arrival process, we then formulate the retailer's long‐run average profit and derive properties of its optimal solution. Our model focuses on capturing the impact of price‐comparison consumers on a retailer's optimal price and inventory decisions. In particular, we allow competitors' prices to affect the retailer's demand via two key factors: the manufacturer's suggested price and the variability of the outside lowest price. According to our results, when the suggested price increases, the retailer should lower its price to obtain more price‐comparison customers from competitors, whereas when the variability of outside lowest price increases, the retailer should raise its price to increase per unit profit from nonprice‐comparison customers.