Reduction of the value of information sharing as demand becomes strongly auto-correlated

M.Z. Babai; J.E. Boylan; A.A. Syntetos; Mohammad M. Ali

doi:10.1016/j.ijpe.2015.05.005

Reduction of the value of information sharing as demand becomes strongly auto-correlated

M.Z. Babai, J.E. Boylan, A.A. Syntetos, Mohammad M. Ali

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28 Citations (Scopus)

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Abstract

Information sharing has been identified, in the academic literature, as one of the most important levers to mitigate the bullwhip effect in supply chains. A highly-cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain, when the downstream demand is autoregressive of order one, is an increasing function of the autoregressive parameter of the demand. In this paper we show that this is true only for a certain range of the autoregressive parameter and there is a maximum value beyond which the bullwhip ratio at the upstream stage is reduced and the percentage inventory reduction resulting from information sharing decreases towards zero. We also show that this maximum value of the autoregressive parameter can be as high as 0.7 which represents a common value that may be encountered in many practical contexts. This means that large benefits of information sharing cannot be assumed for those Stock Keeping Units (SKUs) with highly positively auto-correlated demand. Instead, equally careful analysis is needed for these items as for those SKUs with less strongly auto-correlated demand.

Original language	English
Pages (from-to)	130-135
Journal	International Journal of Production Economics
Volume	181
Issue number	A
Early online date	12 May 2015
DOIs	https://doi.org/10.1016/j.ijpe.2015.05.005
Publication status	Published - Nov 2016

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Production Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Production Economics, [VOL 181, ISSUE A, (2015)] DOI: 10.1016/j.ijpe.2015.05.005

© 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

Supply chain
Bullwhip effect
Information sharing
Autoregressive demand

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10.1016/j.ijpe.2015.05.005

1-s2

Cite this

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title = "Reduction of the value of information sharing as demand becomes strongly auto-correlated",

abstract = "Information sharing has been identified, in the academic literature, as one of the most important levers to mitigate the bullwhip effect in supply chains. A highly-cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain, when the downstream demand is autoregressive of order one, is an increasing function of the autoregressive parameter of the demand. In this paper we show that this is true only for a certain range of the autoregressive parameter and there is a maximum value beyond which the bullwhip ratio at the upstream stage is reduced and the percentage inventory reduction resulting from information sharing decreases towards zero. We also show that this maximum value of the autoregressive parameter can be as high as 0.7 which represents a common value that may be encountered in many practical contexts. This means that large benefits of information sharing cannot be assumed for those Stock Keeping Units (SKUs) with highly positively auto-correlated demand. Instead, equally careful analysis is needed for these items as for those SKUs with less strongly auto-correlated demand. ",

keywords = "Supply chain, Bullwhip effect, Information sharing, Autoregressive demand",

author = "M.Z. Babai and J.E. Boylan and A.A. Syntetos and Ali, {Mohammad M.}",

note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in International Journal of Production Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Production Economics, [VOL 181, ISSUE A, (2015)] DOI: 10.1016/j.ijpe.2015.05.005 {\textcopyright} 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/",

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N1 - NOTICE: this is the author’s version of a work that was accepted for publication in International Journal of Production Economics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Production Economics, [VOL 181, ISSUE A, (2015)] DOI: 10.1016/j.ijpe.2015.05.005 © 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

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N2 - Information sharing has been identified, in the academic literature, as one of the most important levers to mitigate the bullwhip effect in supply chains. A highly-cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain, when the downstream demand is autoregressive of order one, is an increasing function of the autoregressive parameter of the demand. In this paper we show that this is true only for a certain range of the autoregressive parameter and there is a maximum value beyond which the bullwhip ratio at the upstream stage is reduced and the percentage inventory reduction resulting from information sharing decreases towards zero. We also show that this maximum value of the autoregressive parameter can be as high as 0.7 which represents a common value that may be encountered in many practical contexts. This means that large benefits of information sharing cannot be assumed for those Stock Keeping Units (SKUs) with highly positively auto-correlated demand. Instead, equally careful analysis is needed for these items as for those SKUs with less strongly auto-correlated demand.

AB - Information sharing has been identified, in the academic literature, as one of the most important levers to mitigate the bullwhip effect in supply chains. A highly-cited article on the bullwhip effect has claimed that the percentage inventory reduction resulting from information sharing in a two level supply chain, when the downstream demand is autoregressive of order one, is an increasing function of the autoregressive parameter of the demand. In this paper we show that this is true only for a certain range of the autoregressive parameter and there is a maximum value beyond which the bullwhip ratio at the upstream stage is reduced and the percentage inventory reduction resulting from information sharing decreases towards zero. We also show that this maximum value of the autoregressive parameter can be as high as 0.7 which represents a common value that may be encountered in many practical contexts. This means that large benefits of information sharing cannot be assumed for those Stock Keeping Units (SKUs) with highly positively auto-correlated demand. Instead, equally careful analysis is needed for these items as for those SKUs with less strongly auto-correlated demand.

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JO - International Journal of Production Economics

JF - International Journal of Production Economics

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ER -

Reduction of the value of information sharing as demand becomes strongly auto-correlated

Abstract

Bibliographical note

Keywords

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