Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/26690
Title: Quick response policy with Bayesian information updates
Authors: Choi, TM 
Li, D
Yan, H
Issue Date: 2006
Source: European journal of operational research, 2006, v. 170, no. 3, p. 788-808
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.
Keywords: Bayesian information updates
Inventory
Quick response policy
Supply chain management
Publisher: Elsevier
Journal: European journal of operational research 
ISSN: 0377-2217
EISSN: 1872-6860
DOI: 10.1016/j.ejor.2004.07.049
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