The impact of stochastic lead times on the bullwhip effect – a theoretical insight

In this article, we analyze the models quantifying the bullwhip effect in supply chains with stochastic lead times and find advantages and disadvantages of their approaches to the bullwhip problem. Moreover, using computer simulation, we find interesting insights into the bullwhip behavior for a par...

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Main Authors: Zbigniew Michna, Peter Nielsen, Izabela E. Nielsen
Format: Article
Language:English
Published: Taylor & Francis Group 2018-01-01
Series:Production and Manufacturing Research: An Open Access Journal
Subjects:
Online Access:http://dx.doi.org/10.1080/21693277.2018.1484822
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spelling doaj-ac18851bcd6d41bcb571fc3a6191638b2020-11-24T23:20:20ZengTaylor & Francis GroupProduction and Manufacturing Research: An Open Access Journal2169-32772018-01-016119020010.1080/21693277.2018.14848221484822The impact of stochastic lead times on the bullwhip effect – a theoretical insightZbigniew Michna0Peter Nielsen1Izabela E. Nielsen2Uniwersytet Ekonomiczny we WroclawiuAalborg UniversityAalborg UniversityIn this article, we analyze the models quantifying the bullwhip effect in supply chains with stochastic lead times and find advantages and disadvantages of their approaches to the bullwhip problem. Moreover, using computer simulation, we find interesting insights into the bullwhip behavior for a particular instance of a multi-echelon supply chain with constant customer demands and random lead times. We confirm the recent finding of Michna and Nielsen that under certain circumstances lead time signal processing is by itself a fundamental cause of bullwhip effect just like demand-signal processing is. The simulation also shows that in this supply chain the delay parameter of demand forecasting smooths the bullwhip effect at the manufacturer level much faster than the delay parameter of lead time forecasting. Additionally, in the supply chain with random demands, the reverse behavior is observed, that is, the delay parameter of lead time forecasting smooths bullwhip effect at the retailer stage much faster than the delay parameter of demand forecasting. At the manufacturer level, the delay parameter of demand forecasting and the delay parameter of lead time forecasting dampen the effect with a similar strength.http://dx.doi.org/10.1080/21693277.2018.1484822Supply chainBullwhip effectlead time demandlead time forecastingstochastic lead time
collection DOAJ
language English
format Article
sources DOAJ
author Zbigniew Michna
Peter Nielsen
Izabela E. Nielsen
spellingShingle Zbigniew Michna
Peter Nielsen
Izabela E. Nielsen
The impact of stochastic lead times on the bullwhip effect – a theoretical insight
Production and Manufacturing Research: An Open Access Journal
Supply chain
Bullwhip effect
lead time demand
lead time forecasting
stochastic lead time
author_facet Zbigniew Michna
Peter Nielsen
Izabela E. Nielsen
author_sort Zbigniew Michna
title The impact of stochastic lead times on the bullwhip effect – a theoretical insight
title_short The impact of stochastic lead times on the bullwhip effect – a theoretical insight
title_full The impact of stochastic lead times on the bullwhip effect – a theoretical insight
title_fullStr The impact of stochastic lead times on the bullwhip effect – a theoretical insight
title_full_unstemmed The impact of stochastic lead times on the bullwhip effect – a theoretical insight
title_sort impact of stochastic lead times on the bullwhip effect – a theoretical insight
publisher Taylor & Francis Group
series Production and Manufacturing Research: An Open Access Journal
issn 2169-3277
publishDate 2018-01-01
description In this article, we analyze the models quantifying the bullwhip effect in supply chains with stochastic lead times and find advantages and disadvantages of their approaches to the bullwhip problem. Moreover, using computer simulation, we find interesting insights into the bullwhip behavior for a particular instance of a multi-echelon supply chain with constant customer demands and random lead times. We confirm the recent finding of Michna and Nielsen that under certain circumstances lead time signal processing is by itself a fundamental cause of bullwhip effect just like demand-signal processing is. The simulation also shows that in this supply chain the delay parameter of demand forecasting smooths the bullwhip effect at the manufacturer level much faster than the delay parameter of lead time forecasting. Additionally, in the supply chain with random demands, the reverse behavior is observed, that is, the delay parameter of lead time forecasting smooths bullwhip effect at the retailer stage much faster than the delay parameter of demand forecasting. At the manufacturer level, the delay parameter of demand forecasting and the delay parameter of lead time forecasting dampen the effect with a similar strength.
topic Supply chain
Bullwhip effect
lead time demand
lead time forecasting
stochastic lead time
url http://dx.doi.org/10.1080/21693277.2018.1484822
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