Rights statement: The final, definitive version of this article has been published in the Journal, OMEGA 40 (6), 2012, © ELSEVIER.
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Impact of Information Exchange on Supplier Forecasting Performance
AU - Trapero Arenas, Juan
AU - Kourentzes, Nikolaos
AU - Fildes, Robert
N1 - The final, definitive version of this article has been published in the Journal, OMEGA 40 (6), 2012, © ELSEVIER.
PY - 2012/12
Y1 - 2012/12
N2 - 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 InformationExchange 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 supplierforecasting 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.
AB - 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 InformationExchange 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 supplierforecasting 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.
KW - Bullwhip effect
KW - Supply chain
KW - Supply chain collaboration
KW - Forecasting
KW - Neural networks
U2 - 10.1016/j.omega.2011.08.009
DO - 10.1016/j.omega.2011.08.009
M3 - Journal article
VL - 40
SP - 738
EP - 747
JO - Omega: The International Journal of Management Science
JF - Omega: The International Journal of Management Science
SN - 0305-0483
IS - 6
ER -