Impact of information exchange on supplier forecasting performance
Forecasts of demand are crucial to drive supply chains and enterprise resource planning systems. Usually, well-known univariate methods that work automatically such as exponential smoothing are employed to accomplish such forecasts. The traditional Supply Chain relies on a decentralized system where each member feeds its own Forecasting Support System (FSS) with incoming orders from direct customers. Nevertheless, other collaboration schemes are also possible, for instance, the Information Exchange framework allows demand information to be shared between the supplier and the retailer. Current theoretical models have shown the limited circumstances where retailer information is valuable to the supplier. However, there has been very little empirical work carried out. Considering a serially linked two-level supply chain, this work assesses the role of sharing market sales information obtained by the retailer on the supplier forecasting accuracy. Weekly data from a manufacturer and a major UK grocery retailer have been analyzed to show the circumstances where information sharing leads to improved forecasting accuracy. Without resorting to unrealistic assumptions, we find significant evidence of benefits through information sharing with substantial improvements in forecast accuracy.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 40 (2012)
Issue (Month): 6 ()
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Geary, S. & Disney, S.M. & Towill, D.R., 2006. "On bullwhip in supply chains--historical review, present practice and expected future impact," International Journal of Production Economics, Elsevier, vol. 101(1), pages 2-18, May.
- Zhang, Cheng & Tan, Gek-Woo & Robb, David J. & Zheng, Xin, 2006. "Sharing shipment quantity information in the supply chain," Omega, Elsevier, vol. 34(5), pages 427-438, October.
- Srinivasan Raghunathan, 2001. "Information Sharing in a Supply Chain: A Note on its Value when Demand Is Nonstationary," Management Science, INFORMS, vol. 47(4), pages 605-610, April.
- Byrne, P.J. & Heavey, Cathal, 2006. "The impact of information sharing and forecasting in capacitated industrial supply chains: A case study," International Journal of Production Economics, Elsevier, vol. 103(1), pages 420-437, September.
- Hyndman, Rob J. & Koehler, Anne B. & Snyder, Ralph D. & Grose, Simone, 2002.
"A state space framework for automatic forecasting using exponential smoothing methods,"
International Journal of Forecasting,
Elsevier, vol. 18(3), pages 439-454.
- Hyndman, R.J. & Koehler, A.B. & Snyder, R.D. & Grose, S., 2000. "A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods," Monash Econometrics and Business Statistics Working Papers 9/00, Monash University, Department of Econometrics and Business Statistics.
- Philip Hans Franses & Rianne Legerstee, 2010. "Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 331-340.
- Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
- Carbonneau, Real & Laframboise, Kevin & Vahidov, Rustam, 2008. "Application of machine learning techniques for supply chain demand forecasting," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1140-1154, February.
- Dejonckheere, J. & Disney, S. M. & Lambrecht, M. R. & Towill, D. R., 2003. "Measuring and avoiding the bullwhip effect: A control theoretic approach," European Journal of Operational Research, Elsevier, vol. 147(3), pages 567-590, June.
- Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
- Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
- Fang, Yue, 2003. "Forecasting combination and encompassing tests," International Journal of Forecasting, Elsevier, vol. 19(1), pages 87-94.
- Kyu Kim, Kyung & Yul Ryoo, Sung & Dug Jung, Myung, 2011. "Inter-organizational information systems visibility in buyer-supplier relationships: The case of telecommunication equipment component manufacturing industry," Omega, Elsevier, vol. 39(6), pages 667-676, December.
- Sanders, Nada R. & Graman, Gregory A., 2009. "Quantifying costs of forecast errors: A case study of the warehouse environment," Omega, Elsevier, vol. 37(1), pages 116-125, February.
- Hosoda, Takamichi & Disney, Stephen M., 2006. "On variance amplification in a three-echelon supply chain with minimum mean square error forecasting," Omega, Elsevier, vol. 34(4), pages 344-358, August.
- Fiala, P., 2005. "Information sharing in supply chains," Omega, Elsevier, vol. 33(5), pages 419-423, October.
- Bacchetti, Andrea & Saccani, Nicola, 2012. "Spare parts classification and demand forecasting for stock control: Investigating the gap between research and practice," Omega, Elsevier, vol. 40(6), pages 722-737.
- Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
- Goodwin, Paul, 2002. "Integrating management judgment and statistical methods to improve short-term forecasts," Omega, Elsevier, vol. 30(2), pages 127-135, April.
- Holweg, Matthias & Disney, Stephen & Holmström, Jan & Småros, Johanna, 2005. "Supply Chain Collaboration:: Making Sense of the Strategy Continuum," European Management Journal, Elsevier, vol. 23(2), pages 170-181, April.
When requesting a correction, please mention this item's handle: RePEc:eee:jomega:v:40:y:2012:i:6:p:738-747. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.