Dynamic Sourcing Management with Quality Uncertainty and Consumer Learning

Project: Research

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Description

Sourcing from more than one supplier for the same component is a common practice in supply chains. This introduces more variations in the quality. Even for the same supplier, quality may vary from one batch to another. Quality for one supplier may differ from the quality for another supplier due to differences in process capabilities, production technologies and management philosophies. As customers learn about the quality of the product overtime, such variations of quality among suppliers will affect customers' perception of the product which in turn affects future demand. We will consider a single-item multi-period periodic-review model in which the firm decides not only the total quantity to produce but also the proportion to source from each supplier. In other words, the firm also has to decide the quality-mix of the product. Customers learn about the quality of the product overtime and form an expectation of the product's quality, which affect their decisions on whether to buy or not. Thus, the firm's decision on how much to source from each supplier also affects future demand through customers' expectation of the product quality. In the extensive literature on supply uncertainty, existing literatures mainly focus on quantity uncertainty. While quantity uncertainty is an important issue in procurement management, uncertainty in quality is also negligible as consumers become more concerned with quality. There is significant differences between the quantity uncertainty case and the quality uncertainty case: Demand may not be able to be satisfied in the quantity uncertainty case, but future demand is not affected. In the quality uncertainty case, current demand can be satisfied, but future demand may be affected. While the optimal sourcing strategy for the quantity uncertainty case has been widely studied, there is little known about the quality uncertainty case. The proposed project aims to fill this gap. 

Detail(s)

Project number9042711
Grant typeGRF
StatusActive
Effective start/end date1/01/19 → …