The humanitarian aid delivery problem associated with the early recovery phase of a disaster often incorporates multiple attributes. In this paper, the relative importance of various humanitarian aid attributes was measured using a discrete choice multi-attribute value method. This approach identifies all possible non-dominated pairs explicitly ranked by experts and provides an overall complete ranking of attributes. The performance score of each aid delivery plan was then calculated using the attributes’ ranking by solving a corresponding linear programming model. As an application study, the issues pertaining to the early recovery phase of 2017 flood in Assam, India, were analyzed. It was concluded that the ‘delivery amount’ is the most preferred attribute selected by humanitarian experts.
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The authors would like to thank the Associate Editor and anonymous reviewers for their constructive comments that helped in improving the quality and presentation of this manuscript. The authors are also thankful to Dr. Shibu K. Mani, Tata Institute of Social Sciences, Mumbai Campus, for his support while conducting this study, and Professor Paul Hansen, Department of Economics, University of Otago, for granting free access to 1000minds software.
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Jana, R.K., Chandra, C.P. & Tiwari, A.K. Humanitarian aid delivery decisions during the early recovery phase of disaster using a discrete choice multi-attribute value method. Ann Oper Res 283, 1211–1225 (2019). https://doi.org/10.1007/s10479-018-3074-x
- Humanitarian logistics
- Aid delivery
- Early recovery phase
- Pairwise comparison
- Discrete choice method