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doi:10.1016/S0377-2217(01)00300-9    
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Copyright © 2002 Elsevier Science B.V. All rights reserved.

Production, Manufacturing and Logistics

The impact of forecasting model selection on the value of information sharing in a supply chain

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Xiande ZhaoCorresponding Author Contact Information, E-mail The Corresponding Author, a, Jinxing XieE-mail The Corresponding Author, b, 1 and Janny LeungE-mail The Corresponding Author, c, 2

a Department of Decision Sciences and Managerial Economics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

b Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China

c Department of Systems Engineering and Engineering Management, Chinese University of Hong Kong, Shatin, N.T., Hong Kong


Received 14 December 1999; 
accepted 21 March 2001. 
Available online 9 October 2001.

Abstract

This paper presents a study on the impact of forecasting model selection on the value of information sharing in a supply chain with one capacitated supplier and multiple retailers. Using a computer simulation model, this study examines demand forecasting and inventory replenishment decisions by the retailers, and production decisions by the supplier under different demand patterns and capacity tightness. Analyses of the simulation output indicate that the selection of the forecasting model significantly influences the performance of the supply chain and the value of information sharing. Furthermore, demand patterns faced by retailers and capacity tightness faced by the supplier also significantly influence the value of information sharing. The result also shows that substantial cost savings can be realized through information sharing and thus help to motivate trading partners to share information in the supply chain. The findings can also help supply chain managers select suitable forecasting models to improve supply chain performance.

Author Keywords: Supply chain management; Simulation; Forecasting; Information sharing

Article Outline

1. Introduction
2. Literature review
3. The simulation model and procedures
3.1. Basic assumptions
3.2. Phase I: Generation of demand and capacity
3.3. Phase II: Retailers' ordering decisions
3.4. Phase III: Supplier's production and delivery decisions
3.5. Verification and validation
4. Experimental design and research hypotheses
4.1. Independent variables
4.2. Dependent variables
4.3. Research hypotheses
5. Results
5.1. The impact of FM on supply chain performance and the value of IS
5.2. The interaction between DP, FM and IS
5.3. The interaction between CT, FM and IS
6. Conclusions
Acknowledgements
References

1 Tel.: +86-10-62787812; fax: +86-10-62781785.

2 Tel.: +852-2609-8454; fax.: +852-2603-5505.

Corresponding Author Contact Information Corresponding author. Tel.: +852-26097650; fax: +852-26035104; email: xiande@baf.msmail.cuhk.edu.hk


 
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