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Demand forecast sharing in a dual-channel supply chain

  • Xiaohang Yue
  • , John Liu

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

We assess the benefits of sharing demand forecast information in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel. The demand is a linear function of price with a Gaussian primary demand (i.e., zero-price market potential). Both the manufacturer and the retailer set their price based on their forecast of the primary demand. In this setting, we investigate the value of sharing demand forecasts. We analyze the 'make-to-order' scenario, in which prices are set before and production takes place after the primary demand is known, and the 'make-to-stock' scenario, in which production takes place and prices are set before the primary demand is known. We also compare the supply chain performance with and without the direct channel under some assumptions (production cost is zero, and each demand function has the same slope of price). We find that the direct channel has a negative impact on the retailer's performance, and, under some conditions, the manufacturer and the whole supply chain are better off. Our research extends and complements prior research that has investigated only the inventory and replenishment-related benefits of information sharing. © 2005 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)646-667
JournalEuropean Journal of Operational Research
Volume174
Issue number1
DOIs
Publication statusPublished - 1 Oct 2006
Externally publishedYes

Research Keywords

  • Direct channel
  • Information sharing
  • Supply chain management
  • Uncertainty modeling

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