Modeling the Benefits of Sharing Future Demand Information

Kaijie Zhu () and Ulrich W. Thonemann ()
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Kaijie Zhu: Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Ulrich W. Thonemann: Institute of Supply Chain Management, University of Münster, D-48143 Münster, Germany

Operations Research, 2004, vol. 52, issue 1, 136-147

Abstract: We analyze how sharing of future demand information (FDI) can help companies to lower cost. FDI is imperfect information on the customer demands of the upcoming period. We consider a supply chain with a single retailer and multiple customers, where customer demands are normally distributed and correlated. The retailer faces two decisions: With which customers should information be shared and how much should be ordered? We model the problem as a two-stage dynamic program, develop an optimal solution approach, and provide structural insights into the optimal extent of FDI sharing. We show that information cost and demand correlation are important factors for determining the optimal extent of FDI sharing. For a simplified version of the problem where only a single customer is contacted, we analyze how the optimal solution is affected by nonidentically distributed or nonuniformly correlated demands.

Keywords: Forecasting; Inventory/production; Information systems (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (20)

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