IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i20p13423-d945818.html
   My bibliography  Save this article

A Multi-Attribute Decision Support System for Allocation of Humanitarian Cluster Resources Based on Decision Makers’ Perspective

Author

Listed:
  • Sara Rye

    (School of Business, London South Bank University, London SE1 0AA, UK)

  • Emel Aktas

    (Cranfield School of Management, Cranfield University, Cranfield MK43 0AL, UK)

Abstract

The rush of the humanitarian suppliers into the disaster area proved to be counter-productive. To reduce this proliferation problem, the present research is designed to provide a technique for supplier ranking/selection in disaster response using the principles of utility theory. A resource allocation problem is solved using optimisation based on decision maker’s preferences. Due to the lack of real-time data in the first 72 h after the disaster strike, a Decision Support System (DSS) framework called EDIS is introduced to employ secondary historical data from disaster response in four humanitarian clusters (WASH: Water, Sanitation and Hygiene, Nutrition, Health, and Shelter) to estimate the demand of the affected population. A methodology based on multi-attribute decision-making (MADM), Analytical Hierarchy processing (AHP) and Multi-attribute utility theory (MAUT) provides the following results. First a need estimation technique is put forward to estimate minimum standard requirements for disaster response. Second, a method for optimization of the humanitarian partners selection is provided based on the resources they have available during the response phase. Third, an estimate of resource allocation is provided based on the preferences of the decision makers. This method does not require real-time data from the aftermath of the disasters and provides the need estimation, partner selection and resource allocation based on historical data before the MIRA report is released.

Suggested Citation

  • Sara Rye & Emel Aktas, 2022. "A Multi-Attribute Decision Support System for Allocation of Humanitarian Cluster Resources Based on Decision Makers’ Perspective," Sustainability, MDPI, vol. 14(20), pages 1-28, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13423-:d:945818
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/20/13423/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/20/13423/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mikhailov, L., 2002. "Fuzzy analytical approach to partnership selection in formation of virtual enterprises," Omega, Elsevier, vol. 30(5), pages 393-401, October.
    2. Ustun, Ozden & DemI[dot above]rtas, Ezgi Aktar, 2008. "An integrated multi-objective decision-making process for multi-period lot-sizing with supplier selection," Omega, Elsevier, vol. 36(4), pages 509-521, August.
    3. Linet Özdamar & Ediz Ekinci & Beste Küçükyazici, 2004. "Emergency Logistics Planning in Natural Disasters," Annals of Operations Research, Springer, vol. 129(1), pages 217-245, July.
    4. Chang, Mei-Shiang & Tseng, Ya-Ling & Chen, Jing-Wen, 2007. "A scenario planning approach for the flood emergency logistics preparation problem under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 737-754, November.
    5. N C Simpson & P G Hancock, 2009. "Fifty years of operational research and emergency response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 126-139, May.
    6. Shuvrangshu Jana & Rudrashis Majumder & Prathyush P. Menon & Debasish Ghose, 2022. "Decision Support System (DSS) for Hierarchical Allocation of Resources and Tasks for Disaster Management," SN Operations Research Forum, Springer, vol. 3(3), pages 1-30, September.
    7. Nagurney, Anna & Flores, Emilio Alvarez & Soylu, Ceren, 2016. "A Generalized Nash Equilibrium network model for post-disaster humanitarian relief," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 1-18.
    8. Doan, Xuan Vinh & Shaw, Duncan, 2019. "Resource allocation when planning for simultaneous disasters," European Journal of Operational Research, Elsevier, vol. 274(2), pages 687-709.
    9. Balcik, Burcu & Beamon, Benita M. & Krejci, Caroline C. & Muramatsu, Kyle M. & Ramirez, Magaly, 2010. "Coordination in humanitarian relief chains: Practices, challenges and opportunities," International Journal of Production Economics, Elsevier, vol. 126(1), pages 22-34, July.
    10. L N Van Wassenhove, 2006. "Humanitarian aid logistics: supply chain management in high gear," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 475-489, May.
    11. F. Maon & A. Lindgreen & J. Vanhamme, 2009. "Developing supply chains in disaster relief operations through cross-sector socially oriented collaborations : a theoretical model," Post-Print hal-00575871, HAL.
    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. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    2. 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.
    3. Yiping Jiang & Yufei Yuan, 2019. "Emergency Logistics in a Large-Scale Disaster Context: Achievements and Challenges," IJERPH, MDPI, vol. 16(5), pages 1-23, March.
    4. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    5. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.
    6. Daniel A. Griffith & Bradley Boehmke & Randy V. Bradley & Benjamin T. Hazen & Alan W. Johnson, 2019. "Embedded analytics: improving decision support for humanitarian logistics operations," Annals of Operations Research, Springer, vol. 283(1), pages 247-265, December.
    7. Anne M. Quarshie & Rudolf Leuschner, 2020. "Interorganizational Interaction in Disaster Response Networks: A Government Perspective," Journal of Supply Chain Management, Institute for Supply Management, vol. 56(3), pages 3-25, July.
    8. Nagurney, Anna & Salarpour, Mojtaba & Daniele, Patrizia, 2019. "An integrated financial and logistical game theory model for humanitarian organizations with purchasing costs, multiple freight service providers, and budget, capacity, and demand constraints," International Journal of Production Economics, Elsevier, vol. 212(C), pages 212-226.
    9. Oscar Rodríguez-Espíndola, 2023. "Two-stage stochastic formulation for relief operations with multiple agencies in simultaneous disasters," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 477-523, June.
    10. Rameshwar Dubey & Nezih Altay & Constantin Blome, 2019. "Swift trust and commitment: The missing links for humanitarian supply chain coordination?," Annals of Operations Research, Springer, vol. 283(1), pages 159-177, December.
    11. Lu, Chung-Cheng & Ying, Kuo-Ching & Chen, Hui-Ju, 2016. "Real-time relief distribution in the aftermath of disasters – A rolling horizon approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 1-20.
    12. Christian Wankmüller & Gerald Reiner, 2021. "Identifying Challenges and Improvement Approaches for More Efficient Procurement Coordination in Relief Supply Chains," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    13. Laura Laguna-Salvadó & Matthieu Lauras & Uche Okongwu & Tina Comes, 2019. "A multicriteria Master Planning DSS for a sustainable humanitarian supply chain," Annals of Operations Research, Springer, vol. 283(1), pages 1303-1343, December.
    14. Serap Ergün & Pınar Usta & Sırma Zeynep Alparslan Gök & Gerhard Wilhelm Weber, 2023. "A game theoretical approach to emergency logistics planning in natural disasters," Annals of Operations Research, Springer, vol. 324(1), pages 855-868, May.
    15. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    16. Jaime Moreno-Serna & Teresa Sánchez-Chaparro & Leda Stott & Javier Mazorra & Ruth Carrasco-Gallego & Carlos Mataix, 2021. "Feedback Loops and Facilitation: Catalyzing Transformational Multi-Stakeholder Refugee Response Partnerships," Sustainability, MDPI, vol. 13(21), pages 1-21, October.
    17. 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.
    18. Rodríguez-Espíndola, Oscar & Albores, Pavel & Brewster, Christopher, 2018. "Dynamic formulation for humanitarian response operations incorporating multiple organisations," International Journal of Production Economics, Elsevier, vol. 204(C), pages 83-98.
    19. Muhammad Umar & Mark Wilson, 2021. "Supply Chain Resilience: Unleashing the Power of Collaboration in Disaster Management," Sustainability, MDPI, vol. 13(19), pages 1-20, September.
    20. Galindo, Gina & Batta, Rajan, 2013. "Review of recent developments in OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 230(2), pages 201-211.

    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:gam:jsusta:v:14:y:2022:i:20:p:13423-:d:945818. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.