IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v260y2017i1p93-107.html
   My bibliography  Save this article

Order variability in perishable product supply chains

Author

Listed:
  • Minner, Stefan
  • Transchel, Sandra

Abstract

Empirical research has shown that the degree of order variability in supply chains is significantly influenced by product- and industry-specific factors. This paper analyzes the impact of perishability on order variability and the bullwhip effect in supply chains. We decompose the ordering process of a retailer into a sales and an outdating process and quantify their short- and long-term variability and correlation. We find differences to non-perishable product supply chains driven by the impact of the inventory depletion policy, stock-out management, and retailers service level requirement. These three factors significantly affect the retailer’s order variability and thus the decision making process and the profitability of the upstream supply stage. For the majority of instances, the perishable nature of a product results in the ordering process having a lower variability than the demand process. Only when inventory depletion is dominated by last-in-first-out in high service level environments, variability amplification can be observed. We propose a dynamic ordering policy for the upstream supply stage, taking into account negative correlation of retailer orders between periods. This dynamic policy may lead to substantial performance improvements. In a sensitivity analysis, we investigate the impact of shelf life, lead time and demand correlation.

Suggested Citation

  • Minner, Stefan & Transchel, Sandra, 2017. "Order variability in perishable product supply chains," European Journal of Operational Research, Elsevier, vol. 260(1), pages 93-107.
  • Handle: RePEc:eee:ejores:v:260:y:2017:i:1:p:93-107
    DOI: 10.1016/j.ejor.2016.12.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221716310359
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2016.12.016?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. Ad Ridder & Erwin van der Laan & Marc Salomon, 1998. "How Larger Demand Variability May Lead to Lower Costs in the Newsvendor Problem," Operations Research, INFORMS, vol. 46(6), pages 934-936, December.
    2. Cyrus Derman & Morton Klein, 1958. "Inventory Depletion Management," Management Science, INFORMS, vol. 4(4), pages 450-456, July.
    3. Awi Federgruen & Gregory Prastacos & Paul H. Zipkin, 1986. "An Allocation and Distribution Model for Perishable Products," Operations Research, INFORMS, vol. 34(1), pages 75-82, February.
    4. Li Chen & Hau L. Lee, 2012. "Bullwhip Effect Measurement and Its Implications," Operations Research, INFORMS, vol. 60(4), pages 771-784, August.
    5. Morris A. Cohen, 1976. "Analysis of Single Critical Number Ordering Policies for Perishable Inventories," Operations Research, INFORMS, vol. 24(4), pages 726-741, August.
    6. Borga Deniz & Itir Karaesmen & Alan Scheller-Wolf, 2010. "Managing Perishables with Substitution: Inventory Issuance and Replenishment Heuristics," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 319-329, July.
    7. Steven Nahmias, 1982. "Perishable Inventory Theory: A Review," Operations Research, INFORMS, vol. 30(4), pages 680-708, August.
    8. Robert L. Bray & Haim Mendelson, 2012. "Information Transmission and the Bullwhip Effect: An Empirical Investigation," Management Science, INFORMS, vol. 58(5), pages 860-875, May.
    9. John D. Sterman, 1989. "Modeling Managerial Behavior: Misperceptions of Feedback in a Dynamic Decision Making Experiment," Management Science, INFORMS, vol. 35(3), pages 321-339, March.
    10. Chon-Huat Goh & Betsy S. Greenberg & Hirofumi Matsuo, 1993. "Two-Stage Perishable Inventory Models," Management Science, INFORMS, vol. 39(5), pages 633-649, May.
    11. Brant E. Fries, 1975. "Optimal Ordering Policy for a Perishable Commodity with Fixed Lifetime," Operations Research, INFORMS, vol. 23(1), pages 46-61, February.
    12. Li Chen & Hau L. Lee, 2009. "Information Sharing and Order Variability Control Under a Generalized Demand Model," Management Science, INFORMS, vol. 55(5), pages 781-797, May.
    13. 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.
    14. Steven Nahmias, 2011. "Perishable Inventory Systems," International Series in Operations Research and Management Science, Springer, edition 1, number 978-1-4419-7999-5, December.
    15. Stephen C. Graves, 1999. "A Single-Item Inventory Model for a Nonstationary Demand Process," Manufacturing & Service Operations Management, INFORMS, vol. 1(1), pages 50-61.
    16. Dan Chazan & Shmuel Gal, 1977. "A Markovian Model for a Perishable Product Inventory," Management Science, INFORMS, vol. 23(5), pages 512-521, January.
    17. Gérard P. Cachon & Taylor Randall & Glen M. Schmidt, 2007. "In Search of the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 457-479, April.
    18. 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.
    19. 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.
    20. Morris A. Cohen & Dov Pekelman, 1978. "LIFO Inventory Systems," Management Science, INFORMS, vol. 24(11), pages 1150-1162, July.
    21. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    22. Yossi Aviv, 2007. "On the Benefits of Collaborative Forecasting Partnerships Between Retailers and Manufacturers," Management Science, INFORMS, vol. 53(5), pages 777-794, May.
    23. Gerald J. Lieberman, 1958. "LIFO vs FIFO in Inventory Depletion Management," Management Science, INFORMS, vol. 5(1), pages 102-105, October.
    24. 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.
    25. Stephen C. Graves, 1999. "Addendum to "A Single-Item Inventory Model for a Nonstationary Demand Process"," Manufacturing & Service Operations Management, INFORMS, vol. 1(2), pages 174-174.
    26. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
    27. Fujiwara, Okitsugu & Soewandi, Hanijanto & Sedarage, Dayani, 1997. "An optimal ordering and issuing policy for a two-stage inventory system for perishable products," European Journal of Operational Research, Elsevier, vol. 99(2), pages 412-424, June.
    28. Sterman, John D., 1989. "Misperceptions of feedback in dynamic decision making," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(3), pages 301-335, June.
    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. Avinadav, Tal, 2020. "The effect of decision rights allocation on a supply chain of perishable products under a revenue-sharing contract," International Journal of Production Economics, Elsevier, vol. 225(C).
    2. José Roberto Díaz-Reza & Jorge Luis García-Alcaraz & Valeria Martínez-Loya & Liliana Avelar-Sosa & Emilio Jiménez-Macías & Julio Blanco-Fernández, 2018. "Impact of Infrastructure and Production Processes on Rioja Wine Supply Chain Performance," Sustainability, MDPI, vol. 10(1), pages 1-14, January.
    3. Arzum Akkas & Dorothee Honhon, 2023. "Determining maximum shipping age requirements for shelf life and food waste management," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2173-2188, July.
    4. Liu, Wenqian & Ke, Ginger Y. & Chen, Jian & Zhang, Lianmin, 2020. "Scheduling the distribution of blood products: A vendor-managed inventory routing approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    5. Liu, Chao & Chen, Weidong & Zhou, Qian & Mu, Jing, 2021. "Modelling dynamic freshness-keeping effort over a finite time horizon in a two-echelon online fresh product supply chain," European Journal of Operational Research, Elsevier, vol. 293(2), pages 511-528.
    6. Santosh Shekhawat & Nazek Alessa & Himanshu Rathore & Kalpna Sharma, 2022. "A Green Approach—Cost Optimization for a Manufacturing Supply Chain with MFIFO Warehouse Dispatching Policy and Inspection Policy," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    7. Chernonog, Tatyana, 2020. "Inventory and marketing policy in a supply chain of a perishable product," International Journal of Production Economics, Elsevier, vol. 219(C), pages 259-274.
    8. 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).
    9. Shuai Yang & Yujie Xiao & Yong-Hong Kuo, 2017. "The Supply Chain Design for Perishable Food with Stochastic Demand," Sustainability, MDPI, vol. 9(7), pages 1-12, July.
    10. Ioannis Mallidis & Nikolaos Sariannidis & Dimitrios Vlachos & Volha Yakavenka & Georgia Aifadopoulou & Konstantinos Zopounidis, 2022. "Optimal inventory control policies for avoiding food waste," Operational Research, Springer, vol. 22(1), pages 685-701, March.
    11. Ioannis Mallidis & Dimitrios Vlachos & Volha Yakavenka & Zafeiriou Eleni, 2020. "Development of a single period inventory planning model for perishable product redistribution," Annals of Operations Research, Springer, vol. 294(1), pages 697-713, November.
    12. Kouki, Chaaben & Legros, Benjamin & Zied Babai, M. & Jouini, Oualid, 2020. "Analysis of base-stock perishable inventory systems with general lifetime and lead-time," European Journal of Operational Research, Elsevier, vol. 287(3), pages 901-915.
    13. 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.

    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. QU, Zhan & RAFF, Horst, 2023. "Two-part tariffs, inventory stockpiling, and the bullwhip effect," European Journal of Operational Research, Elsevier, vol. 308(1), pages 201-214.
    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. Robert L. Bray & Haim Mendelson, 2012. "Information Transmission and the Bullwhip Effect: An Empirical Investigation," Management Science, INFORMS, vol. 58(5), pages 860-875, May.
    4. 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.
    5. Li Chen & Wei Luo & Kevin Shang, 2017. "Measuring the Bullwhip Effect: Discrepancy and Alignment Between Information and Material Flows," Manufacturing & Service Operations Management, INFORMS, vol. 19(1), pages 36-51, February.
    6. Li Chen & Hau L. Lee, 2012. "Bullwhip Effect Measurement and Its Implications," Operations Research, INFORMS, vol. 60(4), pages 771-784, August.
    7. 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.
    8. Xiuli Chao & Xiting Gong & Cong Shi & Huanan Zhang, 2015. "Approximation Algorithms for Perishable Inventory Systems," Operations Research, INFORMS, vol. 63(3), pages 585-601, June.
    9. Pastore, Erica & Alfieri, Arianna & Zotteri, Giulio, 2019. "An empirical investigation on the antecedents of the bullwhip effect: Evidence from the spare parts industry," International Journal of Production Economics, Elsevier, vol. 209(C), pages 121-133.
    10. Zhu, Tianyuan & Balakrishnan, Jaydeep & da Silveira, Giovani J.C., 2020. "Bullwhip effect in the oil and gas supply chain: A multiple-case study," International Journal of Production Economics, Elsevier, vol. 224(C).
    11. Isaksson, Olov H.D. & Seifert, Ralf W., 2016. "Quantifying the bullwhip effect using two-echelon data: A cross-industry empirical investigation," International Journal of Production Economics, Elsevier, vol. 171(P3), pages 311-320.
    12. Ouyang, Yanfeng & Li, Xiaopeng, 2010. "The bullwhip effect in supply chain networks," European Journal of Operational Research, Elsevier, vol. 201(3), pages 799-810, March.
    13. 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.
    14. Duan, Qinglin & Liao, T. Warren, 2013. "A new age-based replenishment policy for supply chain inventory optimization of highly perishable products," International Journal of Production Economics, Elsevier, vol. 145(2), pages 658-671.
    15. Manuel Brauch & Andreas Größler, 2022. "Holistic versus analytic thinking orientation and its relationship to the bullwhip effect," System Dynamics Review, System Dynamics Society, vol. 38(2), pages 121-134, April.
    16. de Lima, Daruichi Pereira & Fioriolli, José Carlos & Padula, Antonio Domingos & Pumi, Guilherme, 2018. "The impact of Chinese imports of soybean on port infrastructure in Brazil: A study based on the concept of the “Bullwhip Effect”," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 55-76.
    17. Zotteri, Giulio, 2013. "An empirical investigation on causes and effects of the Bullwhip-effect: Evidence from the personal care sector," International Journal of Production Economics, Elsevier, vol. 143(2), pages 489-498.
    18. Ouyang, Yanfeng, 2007. "The effect of information sharing on supply chain stability and the bullwhip effect," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1107-1121, November.
    19. Robert L. Bray & Haim Mendelson, 2015. "Production Smoothing and the Bullwhip Effect," Manufacturing & Service Operations Management, INFORMS, vol. 17(2), pages 208-220, May.
    20. Li Chen & Hau L. Lee, 2009. "Information Sharing and Order Variability Control Under a Generalized Demand Model," Management Science, INFORMS, vol. 55(5), pages 781-797, May.

    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:ejores:v:260:y:2017:i:1:p:93-107. 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/eor .

    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.