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Managing the order pipeline to reduce supply chain volatility

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  • Springer, Mark
  • Kim, Ilhyung

Abstract

The bullwhip effect in particular, and supply chain volatility in general, has been the subject of much analytical and empirical investigation by researchers. One goal of this work has been to determine supply chain designs and policies that minimize volatility. Using a system dynamics approach, we use three distinct supply chain volatility metrics to compare the ability of two alternative pipeline inventory management policies to respond to a demand shock. The results indicate that no one policy dominates on all three metrics of supply chain volatility. A simplistic static pipeline policy minimizes the bullwhip effect and lessens the likelihood of on-hand inventory oscillations, while a more sophisticated dynamic pipeline policy may converge more rapidly to the new equilibrium. In addition, simulation results suggest that the dynamic policy provides better customer service through fewer stockouts and backorders.

Suggested Citation

  • Springer, Mark & Kim, Ilhyung, 2010. "Managing the order pipeline to reduce supply chain volatility," European Journal of Operational Research, Elsevier, vol. 203(2), pages 380-392, June.
  • Handle: RePEc:eee:ejores:v:203:y:2010:i:2:p:380-392
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    Cited by:

    1. Dejian Yu & Zhaoping Yan, 2021. "Knowledge diffusion of supply chain bullwhip effect: main path analysis and science mapping analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8491-8515, October.
    2. Ciancimino, Elena & Cannella, Salvatore & Bruccoleri, Manfredi & Framinan, Jose M., 2012. "On the Bullwhip Avoidance Phase: The Synchronised Supply Chain," European Journal of Operational Research, Elsevier, vol. 221(1), pages 49-63.
    3. Chatfield, Dean C. & Pritchard, Alan M., 2013. "Returns and the bullwhip effect," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 159-175.
    4. Gao, Long, 2015. "Collaborative forecasting, inventory hedging and contract coordination in dynamic supply risk management," European Journal of Operational Research, Elsevier, vol. 245(1), pages 133-145.
    5. Lin, Junyi & Huang, Hongfu & Li, Shanshan & Naim, Mohamed M., 2023. "On the dynamics of order pipeline inventory in a nonlinear order-up-to system," International Journal of Production Economics, Elsevier, vol. 266(C).
    6. Sodhi, ManMohan S. & Tang, Christopher S., 2011. "The incremental bullwhip effect of operational deviations in an arborescent supply chain with requirements planning," European Journal of Operational Research, Elsevier, vol. 215(2), pages 374-382, December.
    7. Ivanov, Dmitry & Sokolov, Boris, 2013. "Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty," European Journal of Operational Research, Elsevier, vol. 224(2), pages 313-323.
    8. Carole Camisullis & Vincent Giard & Gisele Mendy-Bilek, 2011. "Information to share in supply chains dedicated to the mass production of customized products for decentralized management," Working Papers hal-00876865, HAL.
    9. Ojha, Divesh & Sahin, Funda & Shockley, Jeff & Sridharan, Sri V., 2019. "Is there a performance tradeoff in managing order fulfillment and the bullwhip effect in supply chains? The role of information sharing and information type," International Journal of Production Economics, Elsevier, vol. 208(C), pages 529-543.
    10. Subramanian, Nachiappan & Rahman, Shams & Abdulrahman, Muhammad D., 2015. "Sourcing complexity in the Chinese manufacturing sector: An assessment of intangible factors and contractual relationship strategies," International Journal of Production Economics, Elsevier, vol. 166(C), pages 269-284.
    11. Lin, Junyi & Zhou, Li & Spiegler, Virginia L.M. & Naim, Mohamed M. & Syntetos, Aris, 2022. "Push or Pull? The impact of ordering policy choice on the dynamics of a hybrid closed-loop supply chain," European Journal of Operational Research, Elsevier, vol. 300(1), pages 282-295.
    12. Yu, Dejian & Yan, Zhaoping, 2023. "Main path analysis considering citation structure and content: Case studies in different domains," Journal of Informetrics, Elsevier, vol. 17(1).
    13. Tianjian Yang & Weiguo Fan, 2016. "Information management strategies and supply chain performance under demand disruptions," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 8-27, January.

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