IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v155y2014icp132-142.html
   My bibliography  Save this article

An EOQ model for MRO customers under stochastic price to quantify bullwhip effect for the manufacturer

Author

Listed:
  • Sodhi, ManMohan S.
  • Sodhi, Navdeep S.
  • Tang, Christopher S.

Abstract

Motivated by a particular multinational cutting-tools manufacturer, we extend the traditional economic order quantity (EOQ) model for maintenance-repair-and-overhaul (MRO) customers under stochastic purchase price and use it to show how price variance leads to bullwhip effect for the MRO manufacturer despite constant consumption by the customer. Our extension of the EOQ model is based on two assumptions that are reasonable for MRO customers: (a) customer consumption rate of the product is constant; and (b) the customer places each order when the inventory level drops to a pre-specified level (say, zero). We determine the customer's optimal ordering quantity in closed form expressions, which enables us to examine the impact of sales price variance on the variance in the orders the customer places on the manufacturer, thus creating a pricing-induced bullwhip effect. We then extend our analysis to multiple products and multiple customer segments and discuss ways for the manufacturer to mitigate the variance in the customer's orders.

Suggested Citation

  • Sodhi, ManMohan S. & Sodhi, Navdeep S. & Tang, Christopher S., 2014. "An EOQ model for MRO customers under stochastic price to quantify bullwhip effect for the manufacturer," International Journal of Production Economics, Elsevier, vol. 155(C), pages 132-142.
  • Handle: RePEc:eee:proeco:v:155:y:2014:i:c:p:132-142
    DOI: 10.1016/j.ijpe.2013.12.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527313005793
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2013.12.020?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gunasekaran, Angappa & McGaughey, Ronald E. & Ngai, Eric W.T. & Rai, Bharatendra K., 2009. "E-Procurement adoption in the Southcoast SMEs," International Journal of Production Economics, Elsevier, vol. 122(1), pages 161-175, November.
    2. Hamister, James W. & Suresh, Nallan C., 2008. "The impact of pricing policy on sales variability in a supermarket retail context," International Journal of Production Economics, Elsevier, vol. 111(2), pages 441-455, February.
    3. Robin Roundy, 1989. "Rounding Off to Powers of Two in Continuous Relaxations of Capacitated Lot Sizing Problems," Management Science, INFORMS, vol. 35(12), pages 1433-1442, December.
    4. Özelkan, Ertunga C. & ÇakanyIldIrIm, Metin, 2009. "Reverse bullwhip effect in pricing," European Journal of Operational Research, Elsevier, vol. 192(1), pages 302-312, January.
    5. Khan, M. & Jaber, M.Y. & Guiffrida, A.L. & Zolfaghari, S., 2011. "A review of the extensions of a modified EOQ model for imperfect quality items," International Journal of Production Economics, Elsevier, vol. 132(1), pages 1-12, July.
    6. Uday S. Karmarkar, 1981. "Equalization of Runout Times," Operations Research, INFORMS, vol. 29(4), pages 757-762, August.
    7. Teck-Hua Ho & Christopher S. Tang & David R. Bell, 1998. "Rational Shopping Behavior and the Option Value of Variable Pricing," Management Science, INFORMS, vol. 44(12-Part-2), pages 145-160, December.
    8. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    9. 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.
    10. Christopher S. Tang & Serguei Netessine (ed.), 2009. "Consumer-Driven Demand and Operations Management Models," International Series in Operations Research and Management Science, Springer, edition 1, number 978-0-387-98026-3, December.
    11. Donald Erlenkotter, 1990. "Ford Whitman Harris and the Economic Order Quantity Model," Operations Research, INFORMS, vol. 38(6), pages 937-946, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ponte, Borja & Puche, Julio & Rosillo, Rafael & de la Fuente, David, 2020. "The effects of quantity discounts on supply chain performance: Looking through the Bullwhip lens," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    2. Wang, Xun & Disney, Stephen M., 2016. "The bullwhip effect: Progress, trends and directions," European Journal of Operational Research, Elsevier, vol. 250(3), pages 691-701.
    3. Sadeghi, Ahmad, 2015. "Providing a measure for bullwhip effect in a two-product supply chain with exponential smoothing forecasts," International Journal of Production Economics, Elsevier, vol. 169(C), pages 44-54.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Xun & Disney, Stephen M., 2016. "The bullwhip effect: Progress, trends and directions," European Journal of Operational Research, Elsevier, vol. 250(3), pages 691-701.
    2. Özelkan, Ertunga C. & Lim, Churlzu & Adnan, Ziaul Haq, 2018. "Conditions of reverse bullwhip effect in pricing under joint decision of replenishment and pricing," International Journal of Production Economics, Elsevier, vol. 200(C), pages 207-223.
    3. Ma, Yungao & Wang, Nengmin & He, Zhengwen & Lu, Jizhou & Liang, Huigang, 2015. "Analysis of the bullwhip effect in two parallel supply chains with interacting price-sensitive demands," European Journal of Operational Research, Elsevier, vol. 243(3), pages 815-825.
    4. Zhang, Xiaolong & Burke, Gerard J., 2011. "Analysis of compound bullwhip effect causes," European Journal of Operational Research, Elsevier, vol. 210(3), pages 514-526, May.
    5. 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.
    6. Ponte, Borja & Puche, Julio & Rosillo, Rafael & de la Fuente, David, 2020. "The effects of quantity discounts on supply chain performance: Looking through the Bullwhip lens," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    7. Patrick R. Burgess & Funlade T. Sunmola, 2022. "Exploring Attractive Quality Requirements for Short Food Supply Chain Digital Platforms," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-24, January.
    8. Lin, J. & Naim, M.M. & Purvis, L. & Gosling, J., 2017. "The extension and exploitation of the inventory and order based production control system archetype from 1982 to 2015," International Journal of Production Economics, Elsevier, vol. 194(C), pages 135-152.
    9. Li, Xiuhui & Wang, Qinan, 2007. "Coordination mechanisms of supply chain systems," European Journal of Operational Research, Elsevier, vol. 179(1), pages 1-16, May.
    10. Ponte, Borja & Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2022. "The implications of batching in the bullwhip effect and customer service of closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 244(C).
    11. Gérard P. Cachon, 2020. "A Research Framework for Business Models: What Is Common Among Fast Fashion, E-Tailing, and Ride Sharing?," Management Science, INFORMS, vol. 66(3), pages 1172-1192, March.
    12. Xi Gang Yuan & Nan Zhu, 2016. "Bullwhip Effect Analysis in Two-Level Supply Chain Distribution Network Using Different Demand Forecasting Technology," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(03), pages 1-23, June.
    13. Chen, Chang-Chih & Huang, Henry Hongren & Lee, Chun I., 2022. "Supply chain, product pricing, and dynamic capital structure," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 938-952.
    14. Piramuthu, Selwyn, 2005. "Knowledge-based framework for automated dynamic supply chain configuration," European Journal of Operational Research, Elsevier, vol. 165(1), pages 219-230, August.
    15. Enrique Holgado de Frutos & Juan R Trapero & Francisco Ramos, 2020. "A literature review on operational decisions applied to collaborative supply chains," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-28, March.
    16. 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.
    17. Dai, Hongyan & Li, Jianbin & Yan, Nina & Zhou, Weihua, 2016. "Bullwhip effect and supply chain costs with low- and high-quality information on inventory shrinkage," European Journal of Operational Research, Elsevier, vol. 250(2), pages 457-469.
    18. Kiyoung Jeong & Jae-Dong Hong, 2019. "The impact of information sharing on bullwhip effect reduction in a supply chain," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1739-1751, April.
    19. K. Devika & A. Jafarian & A. Hassanzadeh & R. Khodaverdi, 2016. "Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics," Annals of Operations Research, Springer, vol. 242(2), pages 457-487, July.
    20. Williams, Brent D. & Waller, Matthew A. & Ahire, Sanjay & Ferrier, Gary D., 2014. "Predicting retailer orders with POS and order data: The inventory balance effect," European Journal of Operational Research, Elsevier, vol. 232(3), pages 593-600.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:155:y:2014:i:c:p:132-142. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.