Pricing and inventory control for a product with time-varying cost and demand

本文以某平板电视经销商所面临的问题为背景，考虑了短生命周期（耐用）产品的补货和定价决策问题。具体来说，我们考虑了库存系统中的联合定价和库存控制，其中采购成本可能是时变的，需求可能取决于过去的累积销售。产品的采购成本与生产成本密切相关，生产成本可能由于学习效应而随着时间的推移而降低，也可能由于原材料和人工成本的增加而增加。虽然这种现象普遍存在，但在一般的文献中并没有得到很好的研究。我们首先着重于确定采购成本随时间变化时的库存控制结构。第二部分我们拟研究的重点是寿命周期短的耐用产品，如手机、电视和电脑。在营销文献中，创新（耐用）产品的扩散已经得到了很好的研究。理论模型和经验证据都支持产品生命周期内的销售额随时间而变化，并且依赖于过去的累计销售额。研究了这种环境下的最优定价和库存控制问题；这扩展了现有文献通常假设当前需求不依赖于过去的销售。然后，我们考虑上述两种模型的混合模型，其中需求依赖于过去的累计销售，采购成本是时间敏感的。最后，对上述模型进行实证验证。

Motivated by a problem faced by a flat panel television distributor, we consider product replenishment and pricing decision making problem for the (durable) product with short life cycle. Specifically, we consider joint pricing and inventory control in an inventory system where the procurement cost may be time-varying and the demand may depend on the cumulative past sales. The procurement cost of a product is closely related to the production cost which may reduce over time due to learning effect or increase due to increased raw material and labor cost. While such phenomena are pervasive, they have not been well-studied in the literature in general. We first focus on identifying the structure of the inventory control when the procurement cost varies over time. The second part of our proposed research focuses on the durable product with short life cycles such as cell phones, TVs and computers. It has been well-studied in the marketing literature on the diffusion of the innovative (durable) product. Both theoretical model and empirical evidence supports that the sales during the product life cycle change over time and are dependent on cumulative past sales. We study optimal pricing and inventory control in such environment; this extends the existing literature that usually assumes the current demand does not depend on past sales. Then, we consider a hybrid of the above two models, where the demand is dependent on past cumulative sales, and the procurement cost is time-sensitive. Finally, we propose an empirical validation for the above models.