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Humanitarian Relief Chain

In: Supply Chain Transformation

Author

Listed:
  • Amiya K. Chakravarty

    (DM School of Business Northeastern University)

Abstract

Onset of a major disaster requires immediate effort to save human lives. The annual global cost of natural disasters is expected to exceed $300 billion by the year 2050. Saving lives or minimizing suffering, is the prime driver of humanitarian relief. It requires multiple capabilities: fund raising, logistics expertise, medical care, aid dispensing, evacuation, and rehabilitation. As individual organizations cannot possess every capability, multiple organizations comprising the UN, relief organizations, governments, and the military must collaborate. Logistics activities include prepositioning of inventory, setting up warehouses, rapid delivery of supplies in real time, managing a mix of transportation modes, transporting equipment and workers, repairing communication and transportation infrastructure, devising procurement contracts with suppliers, and using 3rd party service providers where feasible.

Suggested Citation

  • Amiya K. Chakravarty, 2014. "Humanitarian Relief Chain," Springer Texts in Business and Economics, in: Supply Chain Transformation, edition 127, chapter 8, pages 237-272, Springer.
    • Handle: RePEc:spr:sptchp:978-3-642-41911-9_8
    DOI: 10.1007/978-3-642-41911-9_8
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    Citations

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    Cited by:

    1. Jingxian Chen & Liang Liang & Dong-Qing Yao, 2017. "Pre-positioning of relief inventories for non-profit organizations: a newsvendor approach," Annals of Operations Research, Springer, vol. 259(1), pages 35-63, December.
    2. Yao, Chen & Fan, Bo & Zhao, Yupan & Cheng, Xinyue, 2023. "Evolutionary dynamics of supervision-compliance game on optimal pre-positioning strategies in relief supply chain management," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    3. Sahebjamnia, Navid & Torabi, S. Ali & Mansouri, S. Afshin, 2018. "Building organizational resilience in the face of multiple disruptions," International Journal of Production Economics, Elsevier, vol. 197(C), pages 63-83.
    4. Wang, Xihui & Li, Feng & Liang, Liang & Huang, Zhimin & Ashley, Allan, 2015. "Pre-purchasing with option contract and coordination in a relief supply chain," International Journal of Production Economics, Elsevier, vol. 167(C), pages 170-176.
    5. Rivera-Royero, Daniel & Galindo, Gina & Yie-Pinedo, Ruben, 2020. "Planning the delivery of relief supplies upon the occurrence of a natural disaster while considering the assembly process of the relief kits," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    6. Rameshwar Dubey & Angappa Gunasekaran & Thanos Papadopoulos, 2019. "Disaster relief operations: past, present and future," Annals of Operations Research, Springer, vol. 283(1), pages 1-8, December.
    7. V. G. Venkatesh & Abraham Zhang & Eric Deakins & Sunil Luthra & S. Mangla, 2019. "A fuzzy AHP-TOPSIS approach to supply partner selection in continuous aid humanitarian supply chains," Annals of Operations Research, Springer, vol. 283(1), pages 1517-1550, December.
    8. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    9. Amiya K. Chakravarty, 2018. "Humanitarian response to hurricane disasters: Coordinating flood‐risk mitigation with fundraising and relief operations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(3), pages 275-288, April.
    10. Rivera-Royero, Daniel & Galindo, Gina & Yie-Pinedo, Ruben, 2016. "A dynamic model for disaster response considering prioritized demand points," Socio-Economic Planning Sciences, Elsevier, vol. 55(C), pages 59-75.
    11. Patra, T. Devi Prasad & Jha, J.K., 2021. "A two-period newsvendor model for prepositioning with a post-disaster replenishment using Bayesian demand update," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    12. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    13. Baharmand, Hossein & Comes, Tina & Lauras, Matthieu, 2019. "Bi-objective multi-layer location–allocation model for the immediate aftermath of sudden-onset disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 86-110.
    14. Peiyu Zhang & Yankui Liu & Guoqing Yang & Guoqing Zhang, 2022. "A multi-objective distributionally robust model for sustainable last mile relief network design problem," Annals of Operations Research, Springer, vol. 309(2), pages 689-730, February.

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