Quick response policy with Bayesian information updates
Journal
European Journal of Operational Research
Journal Volume
170
Journal Issue
3
Pages
788-808
Date Issued
2006
Author(s)
Abstract
In this paper we investigate the quick response (QR) policy with different Bayesian models. Under QR policy, a retailer can collect market information from the sales of a pre-seasonal product whose demand is closely related to a seasonal product's demand. This information is then used to update the distribution for the seasonal product's demand by a Bayesian approach. We study two information update models: one with the revision of an unknown mean, and the other with the revision of both an unknown mean and an unknown variance. The impacts of the information updates under both models are compared and discussed. We also identify the features of the pre-seasonal product which can bring more significant profit improvement. We conclude that an effective QR policy depends on a precise information update model as well as a selection of an appropriate pre-seasonal product as the observation target. ? 2004 Elsevier B.V. All rights reserved.
Subjects
Bayesian information updates; Inventory; Quick response policy; Supply chain management
Other Subjects
Information analysis; Information use; Mathematical models; Sales; Bayesian models; Observation targets; QR policy; Operations research
Type
journal article