Dynamic pricing in a dual‐market environment

Abstract

This paper is concerned with the determination of pricing strategies for a firm that in each period of a finite horizon receives replenishment quantities of a single product which it sells in two markets, e.g., a long-distance market and an on-site market. The key difference between the two markets is that the long-distance market provides for a one period delay in demand fulfillment.In contrast, on-site orders must be filled immediately as the customer is at the physical on-site location. We model the demands in consecutive periods as independent random variables and their distributions depend on the item's price in accordance with two general stochastic demand functions: additive or multiplicative. The firm uses a single pool of inventory to fulfill demands from both markets. We investigate properties of the structure of the dynamic pricing strategy that maximizes the total expected discounted profit over the finite time horizon, under fixed or controlled replenishment conditions. Further, we provide conditions under which one market may be the preferred outlet to sale over the other.

A review on competitive pricing in supply chain management problems: models, classification, and applications

“…Chen et al. (2015) determine pricing strategies for a manufacturer in a finite time horizon. They consider two markets, where the first market's demand can be fulfilled by delay but the other market demand should be fulfilled permanently.…”

Fashion retail supply chain management: A review of operational models

“…However, considering that a part of revenue is required to be shared with the e-tailer when accepting the online orders, retailer A always satisfies its own in-store demands with priority. A related work can be found in Chen et al (2015b), where the fashion retailer operates two channels: An on-site physical store and a long distance online store. Different from the physical store where the consumer demand should be fulfilled immediately, the orders from the online store could be delayed for a period.…”

Dynamic pricing and inventory control with delivery flexibility

“…The first well-known supplier uncertainty is all-or-nothing such as [2,10]. In more general case, one way to incorporate the supplier uncertainty into the model is to use a random yield rate [27,8,7],…”

“…In the existing literature, it has been proved that both optimal order quantity and optimal price are decreasing as inventory increases when the retailer faces all-or-nothing supplier and demand uncertainties [8,10]. It also has been shown that the optimal order quantity and optimal order price may not be monotonic in the inventory level when both supplier yield uncertainty and multiplicative demand noise are involved (see for example [32,8,7]). Being different from the existing literature, the supplier's risk is captured by capacity uncertainty instead of yield uncertainty in our paper.…”