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Enhancement of resilience and quality of cold supply chain under the disruptions caused by COVID-19: A case of a developing country

Author

Listed:
  • Amin Ullah Khan

    (Department of Economics and Law, University of Macerata, Macerata, Italy)

  • Yousaf Ali

    (School of Management Sciences, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan)

Abstract

Cold supply chain (CSC) comprises temperature-sensitive processes, starting from the supply of raw materials, manufacturing, and finally the delivery of finished goods to the end consumers via transport services. Pandemics such as COVID-19 pose threats to its overall functioning and to cater to this issue, the study will ensure the sustainable functioning of CSC by recommending resilience strategies. To do so, the COVID-19 disruptions in the CSC and the resilient sustainability strategies were collected via a vigorous literature review and were analyzed via a Fuzzy QFD technique. The results concluded “crisis simulation,†“identification and securing of logistics,†and “digitalization of cold supply chain†as the top three strategies to ensure the resilience of CSC under disruptions caused by COVID-19. The study recommends necessary steps to the policymakers to ensure a resilient and quality effective CSC. The application of the study proves to be the first of its kind in a developing country such as Pakistan. JEL Classification: C54, D81, H12

Suggested Citation

  • Amin Ullah Khan & Yousaf Ali, 2023. "Enhancement of resilience and quality of cold supply chain under the disruptions caused by COVID-19: A case of a developing country," Australian Journal of Management, Australian School of Business, vol. 48(2), pages 341-365, May.
    • Handle: RePEc:sae:ausman:v:48:y:2023:i:2:p:341-365
    DOI: 10.1177/03128962221095596
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    References listed on IDEAS

    as
    1. Angappa Gunasekaran & Nachiappan Subramanian & Shams Rahman, 2015. "Supply chain resilience: role of complexities and strategies," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6809-6819, November.
    2. 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.
    3. Bottani, Eleonora & Rizzi, Antonio, 2006. "Strategic management of logistics service: A fuzzy QFD approach," International Journal of Production Economics, Elsevier, vol. 103(2), pages 585-599, October.
    4. Amin Ullah Khan & Yousaf Ali, 2021. "Sustainable supplier selection for the cold supply chain (CSC) in the context of a developing country," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(9), pages 13135-13164, September.
    5. Dmitry Ivanov & Alexandre Dolgui, 2020. "Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak," International Journal of Production Research, Taylor & Francis Journals, vol. 58(10), pages 2904-2915, May.
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    Cited by:

    1. A. F. M. Jalal Ahamed & Niina Nummela & Tiia Vissak, 2025. "When East Meets West in Building Organisational Resilience: An Exploratory Study Among Bangladeshi Exporters," Management International Review, Springer, vol. 65(1), pages 85-113, February.
    2. Ali, Yousaf & Khan, Amin Ullah, 2025. "A framework for disrupting extremist recruitment in a developing country: Mapping pathways and prioritizing interventions," Journal of Policy Modeling, Elsevier, vol. 47(6), pages 1180-1200.
    3. Yunting Feng & Xiaoping Zhao & Qinghua Zhu, 2023. "Sustainable supply chains in a turbulent world: Challenges and opportunities," Australian Journal of Management, Australian School of Business, vol. 48(2), pages 199-203, May.

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    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management

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