Forecast errors and inventory performance under forecast information sharing
Previous research has shown that the forecast accuracy is to be distinguished from the performance of the forecasts when utility measures are employed. This is particularly true in an inventory management context, where the interactions between forecasting and stock control are not yet fully understood. In this paper, the relationship between the forecasting performance and inventory implications is explored under an ARIMA representation of the demand process. Two distinct scenarios are incorporated in our analysis: Forecast Information Sharing (FIS) and No Information Sharing (NIS) in a two-stage supply chain. We approach the problem analytically and by means of simulation. The validity of the theoretical results is assessed on a real sales dataset from a major European superstore. The results indicate that the gain in accuracy from Forecast Information Sharing depends on the demand process. The translation to inventory savings then depends on the magnitude of the forecast accuracy improvement, regardless of the demand process. Insights into pertinent managerial issues are also offered, and our paper concludes with an agenda for further research in this area.
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Volume (Year): 28 (2012)
Issue (Month): 4 ()
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- Hau L. Lee & Kut C. So & Christopher S. Tang, 2000. "The Value of Information Sharing in a Two-Level Supply Chain," Management Science, INFORMS, vol. 46(5), pages 626-643, May.
- Kim, Jeon G. & Chatfield, Dean & Harrison, Terry P. & Hayya, Jack C., 2006. "Quantifying the bullwhip effect in a supply chain with stochastic lead time," European Journal of Operational Research, Elsevier, vol. 173(2), pages 617-636, September.
- 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.
- Zhang, Xiaolong, 2004. "The impact of forecasting methods on the bullwhip effect," International Journal of Production Economics, Elsevier, vol. 88(1), pages 15-27, March.
- Mohammad M. Ali & John E. Boylan, 2010. "The Value of Forecast Information Sharing in Supply Chains," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 18, pages 14-18, Summer.
- John Boylan & Aris Syntetos, 2006. "Accuracy and Accuracy Implication Metrics for Intermittent Demand," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 4, pages 39-42, June.
- Kenneth Gilbert, 2005. "An ARIMA Supply Chain Model," Management Science, INFORMS, vol. 51(2), pages 305-310, February.
- Everette S. Gardner, 1990. "Evaluating Forecast Performance in an Inventory Control System," Management Science, INFORMS, vol. 36(4), pages 490-499, April.
- Strijbosch, L.W.G. & Moors, J.J.A. & de Kok, A.G., 1997. "On the interaction between forecasting and inventory control," Research Memorandum FEW 742, Tilburg University, School of Economics and Management.
- Duc, Truong Ton Hien & Luong, Huynh Trung & Kim, Yeong-Dae, 2008. "A measure of bullwhip effect in supply chains with a mixed autoregressive-moving average demand process," European Journal of Operational Research, Elsevier, vol. 187(1), pages 243-256, May.
- Tonya Boone & Ram Ganeshan, 2008. "The Value of Information Sharing in the Retail Supply Chain: Two Case Studies," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 9, pages 12-17, Spring.
- Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E., 2010. "Judging the judges through accuracy-implication metrics: The case of inventory forecasting," International Journal of Forecasting, Elsevier, vol. 26(1), pages 134-143, January.
- Timmermann, Allan & Granger, Clive W. J., 2004.
"Efficient market hypothesis and forecasting,"
International Journal of Forecasting,
Elsevier, vol. 20(1), pages 15-27.
- Granger, Clive & Timmermann, Allan G, 2002. "Efficient Market Hypothesis and Forecasting," CEPR Discussion Papers 3593, C.E.P.R. Discussion Papers.
- Stephen C. Graves, 1999. "A Single-Item Inventory Model for a Nonstationary Demand Process," Manufacturing & Service Operations Management, INFORMS, vol. 1(1), pages 50-61.
- Paul Goodwin, 2009. "Taking Stock: Assessing the True Cost of Forecast Errors," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 15, pages 8-11, Fall.
- Luong, Huynh Trung & Phien, Nguyen Huu, 2007. "Measure of bullwhip effect in supply chains: The case of high order autoregressive demand process," European Journal of Operational Research, Elsevier, vol. 183(1), pages 197-209, November.
- Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
- 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.
- Lee, TS & Cooper, FW & Adam, EE, 1993. "The effects of forecasting errors on the total cost of operations," Omega, Elsevier, vol. 21(5), pages 541-550, September.
- Stephen C. Graves, 1999. "Addendum to "A Single-Item Inventory Model for a Nonstationary Demand Process"," Manufacturing & Service Operations Management, INFORMS, vol. 1(2), pages 174-174.
- Syntetos, Aris A. & Boylan, John E., 2006. "On the stock control performance of intermittent demand estimators," International Journal of Production Economics, Elsevier, vol. 103(1), pages 36-47, September. Full references (including those not matched with items on IDEAS)
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