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Original Articles

Exploring the bullwhip effect using simulation and Taguchi experimental design

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Pages 231-249 | Received 04 Apr 2012, Accepted 06 Jul 2012, Published online: 01 Aug 2012

Keep up to date with the latest research on this topic with citation updates for this article.

Read on this site (7)

Md. Habibur Rahman, Md. Abdur Rahman & Subrata Talapatra. (2020) The bullwhip effect: causes, intensity, and mitigation. Production & Manufacturing Research 8:1, pages 406-426.
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Vinaya Shukla & Mohamed M. Naim. (2018) Sensing endogenous seasonality in the case of a coffee supply chain. International Journal of Logistics Research and Applications 21:3, pages 279-299.
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Mehmood Khan, Matloub Hussain & Leopoldo Eduardo Cárdenas-Barrón. (2017) Learning and screening errors in an EPQ inventory model for supply chains with stochastic lead time demands. International Journal of Production Research 55:16, pages 4816-4832.
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Matloub Hussain, Mehmood Khan & Hussein Sabir. (2016) Analysis of capacity constraints on the backlog bullwhip effect in the two-tier supply chain: a Taguchi approach. International Journal of Logistics Research and Applications 19:1, pages 41-61.
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Wen-jin Lin, Zhi-bin Jiang & Lei Wang. (2014) Modelling and analysis of the bullwhip effect with customers’ baulking behaviours and production capacity constraint. International Journal of Production Research 52:16, pages 4835-4852.
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Wen-Jin Lin, Zhi-Bin Jiang, Ran Liu & Lei Wang. (2014) The bullwhip effect in hybrid supply chain. International Journal of Production Research 52:7, pages 2062-2084.
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Navin K. Dev, Rahul Caprihan & Sanjeev Swami. (2013) Strategic positioning of inventory review policies in alternative supply chain networks: an information-sharing paradigm perspective. International Journal of Logistics Research and Applications 16:1, pages 14-33.
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Articles from other publishers (10)

Borja Ponte, Roberto Dominguez, Salvatore Cannella & Jose M. Framinan. (2022) The implications of batching in the bullwhip effect and customer service of closed-loop supply chains. International Journal of Production Economics 244, pages 108379.
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Chih-Hung Hsu, Xue-Hua Yang, Ting-Yi Zhang, An-Yuan Chang & Qing-Wen Zheng. (2021) Deploying Big Data Enablers to Strengthen Supply Chain Agility to Mitigate Bullwhip Effect: An Empirical Study of China’s Electronic Manufacturers. Journal of Theoretical and Applied Electronic Commerce Research 16:7, pages 3375-3405.
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Lina Tang, Taho Yang, Yiliu Tu & Yizhong Ma. (2020) Supply chain information sharing under consideration of bullwhip effect and system robustness. Flexible Services and Manufacturing Journal 33:2, pages 337-380.
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Ahmed Shaban, Mohamed A. Shalaby, Giulio Di Gravio & Riccardo Patriarca. (2020) Analysis of Variance Amplification and Service Level in a Supply Chain with Correlated Demand. Sustainability 12:16, pages 6470.
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Kiyoung Jeong & Jae-Dong Hong. (2017) The impact of information sharing on bullwhip effect reduction in a supply chain. Journal of Intelligent Manufacturing 30:4, pages 1739-1751.
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Masoud Rahiminezhad Galankashi, Ehsan Fallahiarezoudar, Anoosh Moazzami, Syed Ahmad Helmi, Jafri Mohd Rohani & Noordin Mohd Yusof. (2016) An efficient integrated simulation–Taguchi approach for sales rate evaluation of a petrol station. Neural Computing and Applications 29:4, pages 1073-1085.
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Mehmood Khan, Matloub Hussain & Hussein M. Saber. (2016) Information sharing in a sustainable supply chain. International Journal of Production Economics 181, pages 208-214.
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Eun Suk Suh. (2015) Policy Safety Stock Cost Optimization : Xerox Consumable Supply Chain Case Study. Journal of Korean Institute of Industrial Engineers 41:5, pages 511-520.
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Francesco Costantino, Giulio Di Gravio, Ahmed Shaban & Massimo Tronci. (2015) The impact of information sharing on ordering policies to improve supply chain performances. Computers & Industrial Engineering 82, pages 127-142.
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Mouna Derbel, Wafik Hachicha & Faouzi Masmoudi. (2014) A literature survey of bullwhip effect (2010–2013) according to its causes and evaluation methods. A literature survey of bullwhip effect (2010–2013) according to its causes and evaluation methods.

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