Share This Article:

Impact of Forecast Errors in CPFR Collaboration Strategy

Abstract Full-Text HTML Download Download as PDF (Size:151KB) PP. 389-394
DOI: 10.4236/ajibm.2013.34046    4,871 Downloads   7,286 Views   Citations
Author(s)    Leave a comment

ABSTRACT

The primary objective of this research is to investigate the impact of random forecast error and bias forecast error in Collaborative Planning, Forecasting and Replenishment (CPFR) strategy on the cost of inventory management for both the manufacturer and retailer. Discrete-event simulation is used to develop a CPFR collaboration model where forecast, sales and inventory level information is shared between a retailer and a manufacturer. Based on the results of this study, we conclude that the higher random forecast error and negative bias forecast error increases the cost of inventory management for both the manufacturer and the retailer. When demand variability is high, a bias forecast error has a bigger impact on inventory management cost compared to a random forecast error for both the manufacturer and retailer. Also, a positive bias forecast error is more beneficial than a negative bias forecast error to gain maximum benefits of CPFR strategy.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Kamalapur, R. (2013) Impact of Forecast Errors in CPFR Collaboration Strategy. American Journal of Industrial and Business Management, 3, 389-394. doi: 10.4236/ajibm.2013.34046.

References

[1] T. Lewis, “Electronic Warehouses,” Datamation, Vol. 44 No. 1, 1998, pp. 17-18.
[2] R. Wilson, “17th Annual Logistics Report,” Council of Supply Chain Management Professionals, Lombard, 2006.
[3] J. Baljko, “VMI Study Shows Cost Disparity among Partners,” Electronic Buyer’s News, 7 April 2003.
[4] J. Cooke, “VMI: Very Mixed Impact,” Logistics Management and Distribution Report, Vol. 37, No. 12, 1998, pp. 51-53.
[5] G. Cachon and M. Fisher, “Supply Chain Inventory Management and the Value of Shared Information,” Management Science, Vol. 46, No. 8, 2000, pp. 1032-1048. doi:10.1287/mnsc.46.8.1032.12029
[6] H. Lee, K. So and C. Tang, “The Value of Information Sharing in a Two Level Supply Chain,” Management Science, Vol. 46, No. 5, 2000, pp. 626-643. doi:10.1287/mnsc.46.5.626.12047
[7] Z. Yu, H. Yan and T. Cheng, “Benefits of Information Sharing with Supply Chain Partnerships,” Industrial Management & Data Systems, Vol. 101, No. 3, 2001, pp. 114-119. doi:10.1108/02635570110386625
[8] X. D. Zhao, et al., “The Impact of Forecast Errors on Early Order Commitment in the Supply Chain,” Decision Sciences, Vol. 33, No. 2, 2002, pp. 251-280. doi:10.1111/j.1540-5915.2002.tb01644.x
[9] S. Axsater and K. Rosling, “Installation vs. Echelon Stock Policies for Multilevel Inventory Control,” Management Science, Vol. 39, No 10, 1993, pp. 1274-1280. doi:10.1287/mnsc.39.10.1274
[10] A. Law and W. Kelton, “Simulation Modeling and Analysis,” 3rd Edition, McGraw Hill, New York, 2000.

  
comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.