IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v16y2023i4d10.1007_s12063-023-00405-9.html
   My bibliography  Save this article

Modelling and analysing supply chain disruption: a case of online grocery retailer

Author

Listed:
  • D. G. Mogale

    (Cardiff University)

  • Xun Wang

    (Cardiff University)

  • Emrah Demir

    (Cardiff University)

  • Vasco Sanchez Rodrigues

    (Cardiff University)

Abstract

Supply Chains (SCs) are becoming more vulnerable to disruption risks because of globalisation, competitiveness, and uncertainties. This study is motivated by an online grocery retailer in the UK that experienced multiple disruption risks, such as demand and supply shocks, facility closures, and disruption propagation simultaneously in 2020. The main purpose of this study is to model and perform quantitative analyses of a range of SC disruption risks affecting the UK online retailer. We have attempted to study how UK retailers responded to the first and second waves of the pandemic and the effect on multiple products. Six scenarios are developed based on SC disruption risks and their impacts on SC performance are analysed. The quantitative analysis of two strategies used by grocery retailers during the pandemic, namely vulnerable priority delivery slots and rationing of products, illustrates that rationing of products had a greater SC impact than the use of priority delivery slots. The effects of two resilience strategies, backup supplier and ramping up distribution centre capacity, are also quantified and discussed. Novel managerial insights and theoretical implications are discussed to make online grocery SC more resilient and robust during future disruptions.

Suggested Citation

  • D. G. Mogale & Xun Wang & Emrah Demir & Vasco Sanchez Rodrigues, 2023. "Modelling and analysing supply chain disruption: a case of online grocery retailer," Operations Management Research, Springer, vol. 16(4), pages 1901-1924, December.
    • Handle: RePEc:spr:opmare:v:16:y:2023:i:4:d:10.1007_s12063-023-00405-9
    DOI: 10.1007/s12063-023-00405-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-023-00405-9
    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/s12063-023-00405-9?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. Wen Jun Tan & Wentong Cai & Allan N. Zhang, 2020. "Structural-aware simulation analysis of supply chain resilience," International Journal of Production Research, Taylor & Francis Journals, vol. 58(17), pages 5175-5195, September.
    2. Jill E. Hobbs, 2021. "Food supply chain resilience and the COVID‐19 pandemic: What have we learned?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(2), pages 189-196, June.
    3. Tang, Christopher S. & Davarzani, Hoda & Sarkis, Joseph, 2015. "Quantitative models for managing supply chain risks: A reviewAuthor-Name: Fahimnia, Behnam," European Journal of Operational Research, Elsevier, vol. 247(1), pages 1-15.
    4. Dmitry Ivanov, 2021. "Supply Chain Viability and the COVID-19 pandemic: a conceptual and formal generalisation of four major adaptation strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 59(12), pages 3535-3552, June.
    5. Ruiying Li & Qiang Dong & Chong Jin & Rui Kang, 2017. "A New Resilience Measure for Supply Chain Networks," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    6. 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.
    7. Sube Singh & Ramesh Kumar & Rohit Panchal & Manoj Kumar Tiwari, 2021. "Impact of COVID-19 on logistics systems and disruptions in food supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 59(7), pages 1993-2008, April.
    8. Maciel M. Queiroz & Dmitry Ivanov & Alexandre Dolgui & Samuel Fosso Wamba, 2022. "Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1159-1196, December.
    9. George Baryannis & Sahar Validi & Samir Dani & Grigoris Antoniou, 2019. "Supply chain risk management and artificial intelligence: state of the art and future research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 2179-2202, April.
    10. Dmitry Ivanov, 2018. "Revealing interfaces of supply chain resilience and sustainability: a simulation study," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3507-3523, May.
    11. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    12. Ritesh Ojha & Abhijeet Ghadge & Manoj Kumar Tiwari & Umit S. Bititci, 2018. "Bayesian network modelling for supply chain risk propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5795-5819, September.
    13. Alexandre Dolgui & Dmitry Ivanov & Maxim Rozhkov, 2020. "Does the ripple effect influence the bullwhip effect? An integrated analysis of structural and operational dynamics in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1285-1301, March.
    14. William Ho & Tian Zheng & Hakan Yildiz & Srinivas Talluri, 2015. "Supply chain risk management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 5031-5069, August.
    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. Dmitry Ivanov, 2022. "Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 319(1), pages 1411-1431, December.
    2. 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.
    3. Dmitry Ivanov, 2024. "Exiting the COVID-19 pandemic: after-shock risks and avoidance of disruption tails in supply chains," Annals of Operations Research, Springer, vol. 335(3), pages 1627-1644, April.
    4. Giulio Marcucci & Filippo Emanuele Ciarapica & Giovanni Mazzuto & Maurizio Bevilacqua, 2024. "Analysis of ripple effect and its impact on supply chain resilience: a general framework and a case study on agri-food supply chain during the COVID-19 pandemic," Operations Management Research, Springer, vol. 17(1), pages 175-200, March.
    5. 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).
    6. 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.
    7. Ivanov, Dmitry, 2023. "Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability," International Journal of Production Economics, Elsevier, vol. 263(C).
    8. Riccardo Aldrighetti & Ilenia Zennaro & Serena Finco & Daria Battini, 2019. "Healthcare Supply Chain Simulation with Disruption Considerations: A Case Study from Northern Italy," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 81-102, December.
    9. Emilia Vann Yaroson & Soumyadeb Chowdhury & Sachin Kumar Mangla & Prasanta Kumar Dey, 2024. "Unearthing the interplay between organisational resources, knowledge and industry 4.0 analytical decision support tools to achieve sustainability and supply chain wellbeing," Annals of Operations Research, Springer, vol. 342(2), pages 1321-1368, November.
    10. 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.
    11. 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).
    12. 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.
    13. Célestin Elock Son, 2018. "Supply Chain Risk Management: A Review of Thirteen Years of Research," Post-Print hal-03029453, HAL.
    14. Yingjie Fan & Frank Schwartz & Stefan Voß & David L. Woodruff, 2017. "Stochastic programming for flexible global supply chain planning," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 601-633, December.
    15. Nishat Alam Choudhary & Shalabh Singh & Tobias Schoenherr & M. Ramkumar, 2023. "Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications," Annals of Operations Research, Springer, vol. 322(2), pages 565-607, March.
    16. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    17. Margolis, Joshua T. & Sullivan, Kelly M. & Mason, Scott J. & Magagnotti, Mariah, 2018. "A multi-objective optimization model for designing resilient supply chain networks," International Journal of Production Economics, Elsevier, vol. 204(C), pages 174-185.
    18. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    19. Lydia Novoszel & Tina Wakolbinger, 2022. "Meta-analysis of Supply Chain Disruption Research," SN Operations Research Forum, Springer, vol. 3(1), pages 1-25, March.
    20. 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).

    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:opmare:v:16:y:2023:i:4:d:10.1007_s12063-023-00405-9. 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.