IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v193y2017icp617-632.html
   My bibliography  Save this article

Establishing dynamic expiration dates for perishables: An application of rfid and sensor technology

Author

Listed:
  • Gaukler, Gary
  • Ketzenberg, Michael
  • Salin, Victoria

Abstract

Our research addresses the value of information (voi) for the use of a product's time and temperature history (tth). Using tth information, the retailer can set expiration dates dynamically, based on known environmental conditions. This dynamically set expiration date corresponds to the maximum number of periods that inventory may remain available for sale before it must be removed from inventory and discarded (outdated). In current static practice, however, without the availability of tth, environmental conditions are not known and all units of inventory receive the same expiration date, generally predicated on worst case conditions. Our research demonstrates that information on the tth as a product flows through the supply chain can be very valuable. Using the example of a supply chain for fresh packaged tomatoes, we quantify the value of tth information when used for dynamic expiration date setting. We find that the voi is quite sensitive to environmental and parametric settings, ranging upwards to 90.5% with a mean of 41.2%. Our studies demonstrate that the cost savings that leads to the voi from tth and expiration dating stems from two major sources: eliminating the chance of selling perished product, and greatly decreasing the rate at which lost sales occur. In addition, we show that when dynamic expiration dating is used, average product freshness at the time of sale increases significantly. This indicates a win-win situation where costs to the retailer are reduced, and also additional value for the consumer is created. We also extend our analysis into the impact of imperfect information and find that the voi is fairly robust, up to error levels corresponding to a mean absolute percentage error (mape) of approximately 12%. Median voi at those error levels is 16.5%. The impact of errors, however, differs depending on the model parameterization and we find that under certain settings, the voi can remain significant for much larger values of mape.

Suggested Citation

  • Gaukler, Gary & Ketzenberg, Michael & Salin, Victoria, 2017. "Establishing dynamic expiration dates for perishables: An application of rfid and sensor technology," International Journal of Production Economics, Elsevier, vol. 193(C), pages 617-632.
  • Handle: RePEc:eee:proeco:v:193:y:2017:i:c:p:617-632
    DOI: 10.1016/j.ijpe.2017.07.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527317302360
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2017.07.019?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. Kouki, Chaaben & Sahin, Evren & Jemaï, Zied & Dallery, Yves, 2013. "Assessing the impact of perishability and the use of time temperature technologies on inventory management," International Journal of Production Economics, Elsevier, vol. 143(1), pages 72-85.
    2. Fangruo Chen, 1998. "Echelon Reorder Points, Installation Reorder Points, and the Value of Centralized Demand Information," Management Science, INFORMS, vol. 44(12-Part-2), pages 221-234, December.
    3. Lynn Fish, 2011. "Supply Chain Quality Management," Chapters, in: Dilek Onkal (ed.), Supply Chain Management - Pathways for Research and Practice, IntechOpen.
    4. Muriana, Cinzia, 2016. "An EOQ model for perishable products with fixed shelf life under stochastic demand conditions," European Journal of Operational Research, Elsevier, vol. 255(2), pages 388-396.
    5. Gérard P. Cachon & Marshall Fisher, 2000. "Supply Chain Inventory Management and the Value of Shared Information," Management Science, INFORMS, vol. 46(8), pages 1032-1048, August.
    6. Ketzenberg, Michael E. & Rosenzweig, Eve D. & Marucheck, Ann E. & Metters, Richard D., 2007. "A framework for the value of information in inventory replenishment," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1230-1250, November.
    7. Kamran Moinzadeh, 2002. "A Multi-Echelon Inventory System with Information Exchange," Management Science, INFORMS, vol. 48(3), pages 414-426, March.
    8. Haijema, René, 2013. "A new class of stock-level dependent ordering policies for perishables with a short maximum shelf life," International Journal of Production Economics, Elsevier, vol. 143(2), pages 434-439.
    9. Tijskens, L. M. M. & Polderdijk, J. J., 1996. "A generic model for keeping quality of vegetable produce during storage and distribution," Agricultural Systems, Elsevier, vol. 51(4), pages 431-452, August.
    10. Mark Ferguson & V. Daniel R. Guide , Jr. & Gilvan C. Souza, 2006. "Supply Chain Coordination for False Failure Returns," Manufacturing & Service Operations Management, INFORMS, vol. 8(4), pages 376-393, August.
    11. Steven Nahmias, 1982. "Perishable Inventory Theory: A Review," Operations Research, INFORMS, vol. 30(4), pages 680-708, August.
    12. Mark Ferguson & Michael E. Ketzenberg, 2006. "Information Sharing to Improve Retail Product Freshness of Perishables," Production and Operations Management, Production and Operations Management Society, vol. 15(1), pages 57-73, March.
    13. Michael Ketzenberg & Jacqueline Bloemhof & Gary Gaukler, 2015. "Managing Perishables with Time and Temperature History," Production and Operations Management, Production and Operations Management Society, vol. 24(1), pages 54-70, January.
    14. Aiello, Giuseppe & Enea, Mario & Muriana, Cinzia, 2015. "The expected value of the traceability information," European Journal of Operational Research, Elsevier, vol. 244(1), pages 176-186.
    15. Zied Jemai & Chaaben Kouki & Evren Sahin & Yves Dallery, 2014. "Analysis of a periodic review inventory control system with perishables having random lifetime," Post-Print hal-01672391, HAL.
    16. Chaaben Kouki & Evren Sahin & Zied Jemai & Yves Dallery, 2013. "Assessing the impact of perishability and the use of time temperature technologies on inventory management," Post-Print hal-01672396, HAL.
    17. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    18. Goyal, S. K. & Giri, B. C., 2001. "Recent trends in modeling of deteriorating inventory," European Journal of Operational Research, Elsevier, vol. 134(1), pages 1-16, October.
    19. Steven Nahmias, 1977. "On Ordering Perishable Inventory when Both Demand and Lifetime are Random," Management Science, INFORMS, vol. 24(1), pages 82-90, September.
    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. Voelkel, Michael A. & Sachs, Anna-Lena & Thonemann, Ulrich W., 2020. "An aggregation-based approximate dynamic programming approach for the periodic review model with random yield," European Journal of Operational Research, Elsevier, vol. 281(2), pages 286-298.
    2. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2023. "Industry 5.0 and Triple Bottom Line Approach in Supply Chain Management: The State-of-the-Art," Sustainability, MDPI, vol. 15(7), pages 1-30, March.
    3. Yang, Ya & Chi, Huihui & Tang, Ou & Zhou, Wei & Fan, Tijun, 2019. "Cross perishable effect on optimal inventory preservation control," European Journal of Operational Research, Elsevier, vol. 276(3), pages 998-1012.
    4. Ketzenberg, Michael & Gaukler, Gary & Salin, Victoria, 2018. "Expiration dates and order quantities for perishables," European Journal of Operational Research, Elsevier, vol. 266(2), pages 569-584.
    5. Siawsolit, Chokdee & Gaukler, Gary M., 2021. "Offsetting omnichannel grocery fulfillment cost through advance ordering of perishables," International Journal of Production Economics, Elsevier, vol. 239(C).
    6. Gaukler, Gary M. & Zuidwijk, Rob A. & Ketzenberg, Michael E., 2023. "The value of time and temperature history information for the distribution of perishables," European Journal of Operational Research, Elsevier, vol. 310(2), pages 627-639.

    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. Ketzenberg, Michael & Gaukler, Gary & Salin, Victoria, 2018. "Expiration dates and order quantities for perishables," European Journal of Operational Research, Elsevier, vol. 266(2), pages 569-584.
    2. Ketzenberg, Michael & Oliva, Rogelio & Wang, Yimin & Webster, Scott, 2023. "Retailer inventory data sharing in a fresh product supply chain," European Journal of Operational Research, Elsevier, vol. 307(2), pages 680-693.
    3. Ketzenberg, M.E. & Bloemhof-Ruwaard, J.M., 2009. "The Value of RFID Technology Enabled Information to Manage Perishables," ERIM Report Series Research in Management ERS-2009-020-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    4. Gaukler, Gary M. & Zuidwijk, Rob A. & Ketzenberg, Michael E., 2023. "The value of time and temperature history information for the distribution of perishables," European Journal of Operational Research, Elsevier, vol. 310(2), pages 627-639.
    5. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
    6. Kouki, Chaaben & Jemaï, Zied & Minner, Stefan, 2015. "A lost sales (r, Q) inventory control model for perishables with fixed lifetime and lead time," International Journal of Production Economics, Elsevier, vol. 168(C), pages 143-157.
    7. Kouki, Chaaben & Babai, M. Zied & Jemai, Zied & Minner, Stefan, 2016. "A coordinated multi-item inventory system for perishables with random lifetime," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 226-237.
    8. Janssen, Larissa & Diabat, Ali & Sauer, Jürgen & Herrmann, Frank, 2018. "A stochastic micro-periodic age-based inventory replenishment policy for perishable goods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 445-465.
    9. Li‐Ming Chen & Amar Sapra, 2021. "Inventory renewal for a perishable product: Economies of scale and age‐dependent demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(3), pages 359-377, April.
    10. Ketzenberg, Michael E. & Rosenzweig, Eve D. & Marucheck, Ann E. & Metters, Richard D., 2007. "A framework for the value of information in inventory replenishment," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1230-1250, November.
    11. Yang, Ya & Chi, Huihui & Tang, Ou & Zhou, Wei & Fan, Tijun, 2019. "Cross perishable effect on optimal inventory preservation control," European Journal of Operational Research, Elsevier, vol. 276(3), pages 998-1012.
    12. Jake Clarkson & Michael A. Voelkel & Anna‐Lena Sachs & Ulrich W. Thonemann, 2023. "The periodic review model with independent age‐dependent lifetimes," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 813-828, March.
    13. Broekmeulen, Rob A.C.M. & van Donselaar, Karel H., 2019. "Quantifying the potential to improve on food waste, freshness and sales for perishables in supermarkets," International Journal of Production Economics, Elsevier, vol. 209(C), pages 265-273.
    14. Siawsolit, Chokdee & Gaukler, Gary M., 2021. "Offsetting omnichannel grocery fulfillment cost through advance ordering of perishables," International Journal of Production Economics, Elsevier, vol. 239(C).
    15. Kouki, Chaaben & Jouini, Oualid, 2015. "On the effect of lifetime variability on the performance of inventory systems," International Journal of Production Economics, Elsevier, vol. 167(C), pages 23-34.
    16. Hansen, Ole & Transchel, Sandra & Friedrich, Hanno, 2023. "Replenishment strategies for lost sales inventory systems of perishables under demand and lead time uncertainty," European Journal of Operational Research, Elsevier, vol. 308(2), pages 661-675.
    17. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    18. 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.
    19. Kaijie Zhu & Ulrich W. Thonemann, 2004. "Modeling the Benefits of Sharing Future Demand Information," Operations Research, INFORMS, vol. 52(1), pages 136-147, February.
    20. Sven Axsäter & Johan Marklund, 2008. "Optimal Position-Based Warehouse Ordering in Divergent Two-Echelon Inventory Systems," Operations Research, INFORMS, vol. 56(4), pages 976-991, August.

    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:193:y:2017:i:c:p:617-632. 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.