IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v291y2020i1d10.1007_s10479-017-2643-8.html
   My bibliography  Save this article

Coordination of production and ordering policies under capacity disruption and product write-off risk: an analytical study with real-data based simulations of a fast moving consumer goods company

Author

Listed:
  • Dmitry Ivanov

    (Berlin School of Economics and Law)

  • Maxim Rozhkov

    (X5 Retail Group)

Abstract

Performance impacts of ordering and production control policies in the presence of capacity disruptions are studied on the real-life example of a retail supply chain with product perishability considerations. Constraints on product perishability typically result in reductions in safety stock and increases in transportation frequency. Consideration of the production capacity disruption risks may lead to safety stock increases. This trade-off is approached with the help of a simulation model that is used to compare supply chain performance impacts with regard to coordinated and non-coordinated ordering and production control policies. Real data of a fast moving consumer goods company is used to perform simulations and to derive novel managerial insights and practical recommendations on inventory, on-time delivery and service level control. In particular, for the first time, the effect of ‘postponed redundancy’ has been observed. Moreover, a coordinated production–ordering contingency policy in the supply chain within and after the disruption period has been developed and tested to reduce the negative impacts of the ‘postponed redundancy’. The lessons learned from experiments provide evidence that a coordinated policy is advantageous for inventory dynamics stabilization, improvement in on-time delivery, and variation reduction in customer service level.

Suggested Citation

  • Dmitry Ivanov & Maxim Rozhkov, 2020. "Coordination of production and ordering policies under capacity disruption and product write-off risk: an analytical study with real-data based simulations of a fast moving consumer goods company," Annals of Operations Research, Springer, vol. 291(1), pages 387-407, August.
  • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-017-2643-8
    DOI: 10.1007/s10479-017-2643-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-017-2643-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-017-2643-8?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. Chen, Haoya & Chen, Youhua (Frank) & Chiu, Chun-Hung & Choi, Tsan-Ming & Sethi, Suresh, 2010. "Coordination mechanism for the supply chain with leadtime consideration and price-dependent demand," European Journal of Operational Research, Elsevier, vol. 203(1), pages 70-80, May.
    2. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    3. Spiegler, Virginia L.M. & Naim, Mohamed M. & Towill, Denis R. & Wikner, Joakim, 2016. "A technique to develop simplified and linearised models of complex dynamic supply chain systems," European Journal of Operational Research, Elsevier, vol. 251(3), pages 888-903.
    4. Klibi, Walid & Martel, Alain & Guitouni, Adel, 2010. "The design of robust value-creating supply chain networks: A critical review," European Journal of Operational Research, Elsevier, vol. 203(2), pages 283-293, June.
    5. Jean-François Cordeau & Federico Pasin & Marius Solomon, 2006. "An integrated model for logistics network design," Annals of Operations Research, Springer, vol. 144(1), pages 59-82, April.
    6. Pahl, Julia & Voß, Stefan, 2014. "Integrating deterioration and lifetime constraints in production and supply chain planning: A survey," European Journal of Operational Research, Elsevier, vol. 238(3), pages 654-674.
    7. Dmitry Ivanov, 2017. "Simulation-based ripple effect modelling in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2083-2101, April.
    8. Sang-Hyun Kim & Brian Tomlin, 2013. "Guilt by Association: Strategic Failure Prevention and Recovery Capacity Investments," Management Science, INFORMS, vol. 59(7), pages 1631-1649, July.
    9. Zhibin (Ben) Yang & Göker Ayd{i}n & Volodymyr Babich & Damian R. Beil, 2009. "Supply Disruptions, Asymmetric Information, and a Backup Production Option," Management Science, INFORMS, vol. 55(2), pages 192-209, February.
    10. Fangruo Chen & Awi Federgruen & Yu-Sheng Zheng, 2001. "Coordination Mechanisms for a Distribution System with One Supplier and Multiple Retailers," Management Science, INFORMS, vol. 47(5), pages 693-708, May.
    11. Editors, 2014. "International Journal of Systems Science," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(12), pages 1-1, December.
    12. David Simchi-Levi & William Schmidt & Yehua Wei & Peter Yun Zhang & Keith Combs & Yao Ge & Oleg Gusikhin & Michael Sanders & Don Zhang, 2015. "Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain," Interfaces, INFORMS, vol. 45(5), pages 375-390, October.
    13. Lawrence V. Snyder & Zümbül Atan & Peng Peng & Ying Rong & Amanda J. Schmitt & Burcu Sinsoysal, 2016. "OR/MS models for supply chain disruptions: a review," IISE Transactions, Taylor & Francis Journals, vol. 48(2), pages 89-109, February.
    14. Dmitry Ivanov & Boris Sokolov & Inna Solovyeva & Alexandre Dolgui & Ferry Jie, 2016. "Dynamic recovery policies for time-critical supply chains under conditions of ripple effect," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7245-7258, December.
    15. Brian M. Lewis & Alan L. Erera & Maciek A. Nowak & White Chelsea C., 2013. "Managing Inventory in Global Supply Chains Facing Port-of-Entry Disruption Risks," Transportation Science, INFORMS, vol. 47(2), pages 162-180, May.
    16. A. Agnetis & P. Detti & C. Meloni & D. Pacciarelli, 2001. "Set-Up Coordination between Two Stages of a Supply Chain," Annals of Operations Research, Springer, vol. 107(1), pages 15-32, October.
    17. Tsan-Ming Choi & T. C. E. Cheng & Xiande Zhao & Tsan-Ming Choi & T. C. E. Cheng & Xiande Zhao, 2016. "Multi-Methodological Research in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 25(3), pages 379-389, March.
    18. Dmitry Ivanov & Alexander Tsipoulanidis & Jörn Schönberger, 2017. "Global Supply Chain and Operations Management," Springer Texts in Business and Economics, Springer, number 978-3-319-24217-0, June.
    19. 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.
    20. Nader Azad & Georgios Saharidis & Hamid Davoudpour & Hooman Malekly & Seyed Yektamaram, 2013. "Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach," Annals of Operations Research, Springer, vol. 210(1), pages 125-163, November.
    21. Henk Zijm & Judith Timmer, 2008. "Coordination mechanisms for inventory control in three-echelon serial and distribution systems," Annals of Operations Research, Springer, vol. 158(1), pages 161-182, February.
    22. Jing-Sheng Song & Paul Zipkin, 2009. "Inventories with Multiple Supply Sources and Networks of Queues with Overflow Bypasses," Management Science, INFORMS, vol. 55(3), pages 362-372, March.
    23. 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.
    24. 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.
    25. Lawrence V. Snyder & Mark S. Daskin, 2005. "Reliability Models for Facility Location: The Expected Failure Cost Case," Transportation Science, INFORMS, vol. 39(3), pages 400-416, August.
    26. Qi, Xiangtong & Bard, Jonathan F. & Yu, Gang, 2004. "Supply chain coordination with demand disruptions," Omega, Elsevier, vol. 32(4), pages 301-312, August.
    27. Tiaojun Xiao & Gang Yu & Zhaohan Sheng & Yusen Xia, 2005. "Coordination of a Supply Chain with One-Manufacturer and Two-Retailers Under Demand Promotion and Disruption Management Decisions," Annals of Operations Research, Springer, vol. 135(1), pages 87-109, March.
    28. Harvey M. Wagner & Thomson M. Whitin, 1958. "Dynamic Version of the Economic Lot Size Model," Management Science, INFORMS, vol. 5(1), pages 89-96, October.
    29. Li, Xiuhui & Wang, Qinan, 2007. "Coordination mechanisms of supply chain systems," European Journal of Operational Research, Elsevier, vol. 179(1), pages 1-16, May.
    30. Schmitt, Amanda J. & Sun, Siyuan Anthony & Snyder, Lawrence V. & Shen, Zuo-Jun Max, 2015. "Centralization versus decentralization: Risk pooling, risk diversification, and supply chain disruptions," Omega, Elsevier, vol. 52(C), pages 201-212.
    31. Ivanov, Dmitry & Pavlov, Alexander & Sokolov, Boris, 2014. "Optimal distribution (re)planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics," European Journal of Operational Research, Elsevier, vol. 237(2), pages 758-770.
    32. Jayaraman, Vaidyanathan & Pirkul, Hasan, 2001. "Planning and coordination of production and distribution facilities for multiple commodities," European Journal of Operational Research, Elsevier, vol. 133(2), pages 394-408, January.
    33. Brian Tomlin, 2009. "Disruption‐management strategies for short life‐cycle products," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(4), pages 318-347, 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. Dmitry Ivanov & Alexandre Dolgui, 2022. "Stress testing supply chains and creating viable ecosystems," Operations Management Research, Springer, vol. 15(1), pages 475-486, June.
    2. Giorgia Sammarco & Daniel Ruzza & Behzad Maleki Vishkaei & Pietro De Giovanni, 2022. "The Impact of Digital Technologies on Company Restoration Time Following the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    3. Ana Esteso & M. M. E. Alemany & Fernando Ottati & Ángel Ortiz, 2023. "System dynamics model for improving the robustness of a fresh agri-food supply chain to disruptions," Operational Research, Springer, vol. 23(2), pages 1-53, June.
    4. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    5. Ivanov, Dmitry, 2024. "Cash flow dynamics in the supply chain during and after disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    6. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    7. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    8. Jaya Priyadarshini & Rajesh Kr Singh & Ruchi Mishra & Surajit Bag, 2022. "Investigating the interaction of factors for implementing additive manufacturing to build an antifragile supply chain: TISM-MICMAC approach," Operations Management Research, Springer, vol. 15(1), pages 567-588, June.
    9. Meng, Lin & Lv, Wangyong & Yuan, George Xianzhi & Wang, Huiqi, 2023. "The dynamic risk profiles and management strategies in supply chain coopetition under altruistic preference," International Review of Financial Analysis, Elsevier, vol. 90(C).
    10. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).

    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. Azad, Nader & Hassini, Elkafi, 2019. "Recovery strategies from major supply disruptions in single and multiple sourcing networks," European Journal of Operational Research, Elsevier, vol. 275(2), pages 481-501.
    2. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    3. Dmitry Ivanov, 2017. "Simulation-based ripple effect modelling in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2083-2101, April.
    4. Nader Azad & Elkafi Hassini, 2019. "A Benders Decomposition Method for Designing Reliable Supply Chain Networks Accounting for Multimitigation Strategies and Demand Losses," Transportation Science, INFORMS, vol. 53(5), pages 1287-1312, September.
    5. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    6. Sherwin, Michael D. & Medal, Hugh & Lapp, Steven A., 2016. "Proactive cost-effective identification and mitigation of supply delay risks in a low volume high value supply chain using fault-tree analysis," International Journal of Production Economics, Elsevier, vol. 175(C), pages 153-163.
    7. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    8. Dmitry Ivanov & Richard Hartl & Alexandre Dolgui & Alexander Pavlov & Boris Sokolov, 2015. "Integration of aggregate distribution and dynamic transportation planning in a supply chain with capacity disruptions and the ripple effect consideration," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 6963-6979, December.
    9. Behzadi, Golnar & O’Sullivan, Michael Justin & Olsen, Tava Lennon & Zhang, Abraham, 2018. "Agribusiness supply chain risk management: A review of quantitative decision models," Omega, Elsevier, vol. 79(C), pages 21-42.
    10. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    11. Dmitry Ivanov & Boris Sokolov & Inna Solovyeva & Alexandre Dolgui & Ferry Jie, 2016. "Dynamic recovery policies for time-critical supply chains under conditions of ripple effect," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 7245-7258, December.
    12. Chernonog, Tatyana & Avinadav, Tal, 2019. "Pricing and advertising in a supply chain of perishable products under asymmetric information," International Journal of Production Economics, Elsevier, vol. 209(C), pages 249-264.
    13. 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.
    14. Liu, Zhongyi & Li, Mengyu & Zhai, Xin, 2022. "Managing supply chain disruption threat via a strategy combining pricing and self-protection," International Journal of Production Economics, Elsevier, vol. 247(C).
    15. Cheng, Chun & Qi, Mingyao & Zhang, Ying & Rousseau, Louis-Martin, 2018. "A two-stage robust approach for the reliable logistics network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 185-202.
    16. Sazvar, Z. & Mirzapour Al-e-hashem, S.M.J. & Govindan, K. & Bahli, B., 2016. "A novel mathematical model for a multi-period, multi-product optimal ordering problem considering expiry dates in a FEFO system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 232-261.
    17. Ehsan Ahmadi & Dale T. Masel & Seth Hostetler & Reza Maihami & Iman Ghalehkhondabi, 2020. "A centralized stochastic inventory control model for perishable products considering age-dependent purchase price and lead time," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 231-269, April.
    18. Nader Azad & Georgios Saharidis & Hamid Davoudpour & Hooman Malekly & Seyed Yektamaram, 2013. "Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach," Annals of Operations Research, Springer, vol. 210(1), pages 125-163, November.
    19. Alikhani, Reza & Torabi, S.Ali & Altay, Nezih, 2021. "Retail supply chain network design with concurrent resilience capabilities," International Journal of Production Economics, Elsevier, vol. 234(C).
    20. Liu, Ming & Liu, Zhongzheng & Chu, Feng & Dolgui, Alexandre & Chu, Chengbin & Zheng, Feifeng, 2022. "An optimization approach for multi-echelon supply chain viability with disruption risk minimization," Omega, Elsevier, vol. 112(C).

    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:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-017-2643-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.