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Impact of Information Exchange on Supplier Forecasting Performance

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Impact of Information Exchange on Supplier Forecasting Performance. / Trapero Arenas, Juan; Kourentzes, Nikolaos; Fildes, Robert.

In: Omega: The International Journal of Management Science, Vol. 40, No. 6, 12.2012, p. 738-747.

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Trapero Arenas, Juan ; Kourentzes, Nikolaos ; Fildes, Robert. / Impact of Information Exchange on Supplier Forecasting Performance. In: Omega: The International Journal of Management Science. 2012 ; Vol. 40, No. 6. pp. 738-747.

Bibtex

@article{9345fc5e31a9476ca7e8f4f434604fec,
title = "Impact of Information Exchange on Supplier Forecasting Performance",
abstract = "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.",
keywords = "Bullwhip effect, Supply chain, Supply chain collaboration, Forecasting, Neural networks",
author = "{Trapero Arenas}, Juan and Nikolaos Kourentzes and Robert Fildes",
note = "The final, definitive version of this article has been published in the Journal, OMEGA 40 (6), 2012, {\textcopyright} ELSEVIER.",
year = "2012",
month = dec,
doi = "10.1016/j.omega.2011.08.009",
language = "English",
volume = "40",
pages = "738--747",
journal = "Omega: The International Journal of Management Science",
issn = "0305-0483",
publisher = "Elsevier BV",
number = "6",

}

RIS

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 -