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Analysis of the bullwhip effect with order batching in multi‐echelon supply chains

Analysis of the bullwhip effect with order batching in multi‐echelon supply chains Purpose – The purpose of this paper is to understand the effect of batching on bullwhip effect in a model of multi‐echelon supply chain with information sharing. Design/methodology/approach – The model uses the system dynamics and control theoretic concepts of variables, flows and feedback processes and is implemented using iThink ® software. Findings – It has been seen that the relationship between batch size and demand amplification is non‐monotonic. Large batch sizes, that when combined in integer multiples can produce order rates that are close to the actual demand, produce little demand amplification, i.e. it is the size of the remainder of the quotient that is the determinant. It is further noted that the value of information sharing is greatest for smaller batch sizes, for which there is a much greater improvement in the amplification ratio. Research limitations/implications – Batching is associated with the inventory holding and backlog cost. Therefore, future work should investigate the cost implications of order batching in multi‐echelon supply chains. Practical implications – This is a contribution to the continuing research into the bullwhip effect, giving supply chain operations managers and designers a practical way into controlling the bullwhip produced by batching across multi‐echelon supply chains. Originality/value – Previous similar studies have used control theoretic techniques and it has been pointed out that control theorists are unable to solve the lot sizing problem. Therefore, system dynamic simulation has been applied to investigate the impact of various batch sizes on bullwhip effect. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Physical Distribution & Logistics Management Emerald Publishing

Analysis of the bullwhip effect with order batching in multi‐echelon supply chains

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Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
0960-0035
DOI
10.1108/09600031111185248
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to understand the effect of batching on bullwhip effect in a model of multi‐echelon supply chain with information sharing. Design/methodology/approach – The model uses the system dynamics and control theoretic concepts of variables, flows and feedback processes and is implemented using iThink ® software. Findings – It has been seen that the relationship between batch size and demand amplification is non‐monotonic. Large batch sizes, that when combined in integer multiples can produce order rates that are close to the actual demand, produce little demand amplification, i.e. it is the size of the remainder of the quotient that is the determinant. It is further noted that the value of information sharing is greatest for smaller batch sizes, for which there is a much greater improvement in the amplification ratio. Research limitations/implications – Batching is associated with the inventory holding and backlog cost. Therefore, future work should investigate the cost implications of order batching in multi‐echelon supply chains. Practical implications – This is a contribution to the continuing research into the bullwhip effect, giving supply chain operations managers and designers a practical way into controlling the bullwhip produced by batching across multi‐echelon supply chains. Originality/value – Previous similar studies have used control theoretic techniques and it has been pointed out that control theorists are unable to solve the lot sizing problem. Therefore, system dynamic simulation has been applied to investigate the impact of various batch sizes on bullwhip effect.

Journal

International Journal of Physical Distribution & Logistics ManagementEmerald Publishing

Published: Nov 8, 2011

Keywords: Supply chain management; Batch size; Batch processing; Bullwhip effect; Batching; Information sharing; Multi‐echelon supply chain; Simulation

References