IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v44y1996i1p215-222.html
   My bibliography  Save this article

Managing Inventory with the Prospect of Obsolescence

Author

Listed:
  • Jing-Sheng Song

    (University of California, Irvine, California)

  • Paul H. Zipkin

    (Duke University, Durham, North Carolina)

Abstract

How should inventory management respond when there is a possibility of imminent obsolescence (or, more generally, deteriorating demand)? We use an inventory-control model to address this question. The model incorporates a Markovian submodel to describe the uncertain events leading to obsolescence. These events and their uncertainties come in a variety of patterns. We devote considerable attention to specifying the submodel, and we compare a few alternatives numerically. Also, we compare optimal policies to simpler alternatives, and we investigate the response of the model to parameter changes. Generally, we find that obsolescence does (or should) have a substantial impact in the way inventories are managed. The nature of these effects, moreover, is fairly intricate. It appears that obsolescence cannot be captured in a simpler model through parameter adjustments. These conclusions presume that we cannot dispose of excess stock, either directly or through price promotions; we show also that the disposal option can make the problems of obsolescence more manageable.

Suggested Citation

  • Jing-Sheng Song & Paul H. Zipkin, 1996. "Managing Inventory with the Prospect of Obsolescence," Operations Research, INFORMS, vol. 44(1), pages 215-222, February.
  • Handle: RePEc:inm:oropre:v:44:y:1996:i:1:p:215-222
    DOI: 10.1287/opre.44.1.215
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.44.1.215
    Download Restriction: no

    File URL: https://libkey.io/10.1287/opre.44.1.215?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
    ---><---

    Citations

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


    Cited by:

    1. Opher Baron & Oded Berman & David Perry, 2010. "Continuous review inventory models for perishable items ordered in batches," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 72(2), pages 217-247, October.
    2. Jochen Schlapp & Moritz Fleischmann & Danja Sonntag, 2022. "Inventory timing: How to serve a stochastic season," Production and Operations Management, Production and Operations Management Society, vol. 31(7), pages 2891-2906, July.
    3. James T. Treharne & Charles R. Sox, 2002. "Adaptive Inventory Control for Nonstationary Demand and Partial Information," Management Science, INFORMS, vol. 48(5), pages 607-624, May.
    4. Pinçe, Çerag & Dekker, Rommert, 2011. "An inventory model for slow moving items subject to obsolescence," European Journal of Operational Research, Elsevier, vol. 213(1), pages 83-95, August.
    5. Pinçe, C. & Dekker, R., 2010. "A Continuous Review Inventory Model with Advance Policy Change and Obsolescence," Econometric Institute Research Papers EI 2009-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. van Jaarsveld, Willem & Dekker, Rommert, 2011. "Estimating obsolescence risk from demand data to enhance inventory control--A case study," International Journal of Production Economics, Elsevier, vol. 133(1), pages 423-431, September.
    7. Chad R. Larson & Danko Turcic & Fuqiang Zhang, 2015. "An Empirical Investigation of Dynamic Ordering Policies," Management Science, INFORMS, vol. 61(9), pages 2118-2138, September.
    8. Barron, Yonit, 2016. "Clearing control policies for MAP inventory process with lost sales," European Journal of Operational Research, Elsevier, vol. 251(2), pages 495-508.
    9. Alamri, Adel A. & Syntetos, Aris A., 2018. "Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model," International Journal of Production Economics, Elsevier, vol. 206(C), pages 33-45.
    10. Yossi Aviv, 2003. "A Time-Series Framework for Supply-Chain Inventory Management," Operations Research, INFORMS, vol. 51(2), pages 210-227, April.
    11. Li Chen & Jing-Sheng Song & Yue Zhang, 2017. "Serial Inventory Systems with Markov-Modulated Demand: Derivative Bounds, Asymptotic Analysis, and Insights," Operations Research, INFORMS, vol. 65(5), pages 1231-1249, October.
    12. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Data Science Solutions for Retail Strategy to Reduce Waste Keeping High Profit," Sustainability, MDPI, vol. 11(13), pages 1-30, June.
    13. Song, Yuyue & Lau, Hoong Chuin, 2004. "A periodic-review inventory model with application to the continuous-review obsolescence problem," European Journal of Operational Research, Elsevier, vol. 159(1), pages 110-120, November.
    14. Cattani, Kyle D. & Souza, Gilvan C., 2003. "Good buy? Delaying end-of-life purchases," European Journal of Operational Research, Elsevier, vol. 146(1), pages 216-228, April.
    15. Xiangwen Lu & Jing-Sheng Song & Amelia Regan, 2006. "Inventory Planning with Forecast Updates: Approximate Solutions and Cost Error Bounds," Operations Research, INFORMS, vol. 54(6), pages 1079-1097, December.
    16. Susan H. Xu & Zhaolin Li, 2007. "Managing a Single-Product Assemble-to-Order System with Technology Innovations," Management Science, INFORMS, vol. 53(9), pages 1467-1485, September.
    17. Awi Federgruen & Min Wang, 2013. "Monotonicity properties of a class of stochastic inventory systems," Annals of Operations Research, Springer, vol. 208(1), pages 155-186, September.
    18. Fleischhacker, Adam J. & Zhao, Yao, 2011. "Planning for demand failure: A dynamic lot size model for clinical trial supply chains," European Journal of Operational Research, Elsevier, vol. 211(3), pages 496-506, June.

    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:inm:oropre:v:44:y:1996:i:1:p:215-222. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.