IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v42y2022i3d10.1007_s10669-021-09836-w.html
   My bibliography  Save this article

Logistics and supply chain management of food industry during COVID-19: disruptions and a recovery plan

Author

Listed:
  • Abhijit Barman

    (National Institute of Technology Silchar)

  • Rubi Das

    (National Institute of Technology Silchar)

  • Pijus Kanti De

    (National Institute of Technology Silchar)

Abstract

An ongoing worldwide pandemic, known as Covid infection 2019 (COVID-19), influences the food supply chains significantly. In the pandemic situation, the movements of the people are restricted due to strict lock-down, and retail shops are closed. The supply of products to the customer is a challenging situation for the food supplier. These disruptions impact the food supply chain system suddenly, and the process can collapse without necessary and immediate actions. In this paper, a direct delivery channel has been used as a recovery strategy to minimize the effects of disruptions in the pandemic situation. In the recovery plan, the manufacturer appoints vendors and delivers the products directly to the customers by introducing multi-delivery channels. We optimize the recovery plan under the profit maximization criteria from the recovery window. Some numerical examples have been illustrated to justify that the developed recovery model can resist the reduction of demand and improve the profit of the system. Also, managerial insights are discussed which help the decision-makers to make an accurate and prompt decision of designing a recovery strategy during COVID-19.

Suggested Citation

  • Abhijit Barman & Rubi Das & Pijus Kanti De, 2022. "Logistics and supply chain management of food industry during COVID-19: disruptions and a recovery plan," Environment Systems and Decisions, Springer, vol. 42(3), pages 338-349, September.
    • Handle: RePEc:spr:envsyd:v:42:y:2022:i:3:d:10.1007_s10669-021-09836-w
    DOI: 10.1007/s10669-021-09836-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-021-09836-w
    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/s10669-021-09836-w?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. Florian Lücker & Ralf W. Seifert & Işık Biçer, 2019. "Roles of inventory and reserve capacity in mitigating supply chain disruption risk," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1238-1249, February.
    2. Maihami, Reza & Nakhai Kamalabadi, Isa, 2012. "Joint pricing and inventory control for non-instantaneous deteriorating items with partial backlogging and time and price dependent demand," International Journal of Production Economics, Elsevier, vol. 136(1), pages 116-122.
    3. Hosseini, Seyedmohsen & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "A review of definitions and measures of system resilience," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 47-61.
    4. Alexander Trautrims & Martin C. Schleper & M. Selim Cakir & Stefan Gold, 2020. "Survival at the expense of the weakest? Managing modern slavery risks in supply chains during COVID-19," Journal of Risk Research, Taylor & Francis Journals, vol. 23(7-8), pages 1067-1072, August.
    5. S. E. Galaitsi & Jeffrey M. Keisler & Benjamin D. Trump & Igor Linkov, 2021. "The Need to Reconcile Concepts that Characterize Systems Facing Threats," Risk Analysis, John Wiley & Sons, vol. 41(1), pages 3-15, January.
    6. Sanjoy Kumar Paul & Sobhan Asian & Mark Goh & S. Ali Torabi, 2019. "Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss," Annals of Operations Research, Springer, vol. 273(1), pages 783-814, February.
    7. Syed Mithun Ali & Koichi Nakade, 2017. "Optimal ordering policies in a multi-sourcing supply chain with supply and demand disruptions-a CVaR approach," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 28(2), pages 180-199.
    8. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    9. Ivanov, Dmitry & Pavlov, Alexander & Dolgui, Alexandre & Pavlov, Dmitry & Sokolov, Boris, 2016. "Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 90(C), pages 7-24.
    10. Benjamin D. Trump & Igor Linkov, 2020. "Risk and resilience in the time of the COVID-19 crisis," Environment Systems and Decisions, Springer, vol. 40(2), pages 171-173, June.
    11. Hosseini, Seyedmohsen & Barker, Kash, 2016. "A Bayesian network model for resilience-based supplier selection," International Journal of Production Economics, Elsevier, vol. 180(C), pages 68-87.
    Full references (including those not matched with items on IDEAS)

    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. Li, Yuhong & Zobel, Christopher W. & Seref, Onur & Chatfield, Dean, 2020. "Network characteristics and supply chain resilience under conditions of risk propagation," International Journal of Production Economics, Elsevier, vol. 223(C).
    2. 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).
    3. 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.
    4. Sanjoy Kumar Paul & Priyabrata Chowdhury, 2020. "Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(3), pages 283-293, September.
    5. Trucco, Paolo & Petrenj, Boris, 2023. "Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    7. R. Cantelmi & G. Di Gravio & R. Patriarca, 2021. "Reviewing qualitative research approaches in the context of critical infrastructure resilience," Environment Systems and Decisions, Springer, vol. 41(3), pages 341-376, September.
    8. Belhadi, Amine & Kamble, Sachin & Jabbour, Charbel Jose Chiappetta & Gunasekaran, Angappa & Ndubisi, Nelson Oly & Venkatesh, Mani, 2021. "Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    9. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    10. Mohammad Amin Hariri-Ardebili, 2020. "Living in a Multi-Risk Chaotic Condition: Pandemic, Natural Hazards and Complex Emergencies," IJERPH, MDPI, vol. 17(16), pages 1-16, August.
    11. Jethro Kiers & Jaap Seinhorst & Mirthe Zwanenburg & Klaas Stek, 2022. "Which Strategies and Corresponding Competences Are Needed to Improve Supply Chain Resilience: A COVID-19 Based Review," Logistics, MDPI, vol. 6(1), pages 1-17, February.
    12. Iman Kazemian & S. Ali Torabi & Christopher W. Zobel & Yuhong Li & Milad Baghersad, 2022. "A multi-attribute supply chain network resilience assessment framework based on SNA-inspired indicators," Operational Research, Springer, vol. 22(3), pages 1853-1883, July.
    13. Hossain, Niamat Ullah Ibne & Nur, Farjana & Hosseini, Seyedmohsen & Jaradat, Raed & Marufuzzaman, Mohammad & Puryear, Stephen M., 2019. "A Bayesian network based approach for modeling and assessing resilience: A case study of a full service deep water port," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 378-396.
    14. Hossain, Niamat Ullah Ibne & Jaradat, Raed & Hosseini, Seyedmohsen & Marufuzzaman, Mohammad & Buchanan, Randy K., 2019. "A framework for modeling and assessing system resilience using a Bayesian network: A case study of an interdependent electrical infrastructure system," International Journal of Critical Infrastructure Protection, Elsevier, vol. 25(C), pages 62-83.
    15. Niamat Ullah Ibne Hossain & Farjana Nur & Raed Jaradat & Seyedmohsen Hosseini & Mohammad Marufuzzaman & Stephen M. Puryear & Randy K. Buchanan, 2019. "Metrics for Assessing Overall Performance of Inland Waterway Ports: A Bayesian Network Based Approach," Complexity, Hindawi, vol. 2019, pages 1-17, May.
    16. Ni, Ni & Howell, Brendan J. & Sharkey, Thomas C., 2018. "Modeling the impact of unmet demand in supply chain resiliency planning," Omega, Elsevier, vol. 81(C), pages 1-16.
    17. Dormady, Noah & Roa-Henriquez, Alfredo & Rose, Adam, 2019. "Economic resilience of the firm: A production theory approach," International Journal of Production Economics, Elsevier, vol. 208(C), pages 446-460.
    18. Hosseini, Seyedmohsen & Morshedlou, Nazanin & Ivanov, Dmitry & Sarder, M.D. & Barker, Kash & Khaled, Abdullah Al, 2019. "Resilient supplier selection and optimal order allocation under disruption risks," International Journal of Production Economics, Elsevier, vol. 213(C), pages 124-137.
    19. Yin, Jiateng & Ren, Xianliang & Liu, Ronghui & Tang, Tao & Su, Shuai, 2022. "Quantitative analysis for resilience-based urban rail systems: A hybrid knowledge-based and data-driven approach," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    20. Behzadi, Golnar & O’Sullivan, Michael Justin & Olsen, Tava Lennon, 2020. "On metrics for supply chain resilience," European Journal of Operational Research, Elsevier, vol. 287(1), pages 145-158.

    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:envsyd:v:42:y:2022:i:3:d:10.1007_s10669-021-09836-w. 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.