Supporting Humanitarian Relief Distribution Decision-Making under Deep Uncertainty : A System Design Approach
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Original versionRahman, M. T. (2020). Supporting Humanitarian Relief Distribution Decision-Making under Deep Uncertainty : A System Design Approach (Doctoral thesis). University of Agder, Kristiansand.
Disasters threaten society with widespread destruction of infrastructure and livelihood. For their survival, affected inhabitants depend on immediate humanitarian assistance from diverse organizations. During quick responses, humanitarian decision- makers (HDMs) act rapidly to distribute necessary relief goods, despite the deep, prevailing uncertainty that arises from scarce, conflicting, and uncertain information. To support HDMs in humanitarian relief distribution (HRD) decision-making, humanitarian logistics (HL) researchers have developed various mathematical models. These models are, however, specific to disaster scenarios, and most of them are detached from the realities of the field since end-users (mainly practitioners) have been absent in the development process. When tested, these decision-making models were found to be capable of producing good results, but they have not been implemented in practice because of operational inconsistency or complexity (i.e., lack of user-friendliness). Therefore, humanitarian responders are still in need of support systems to assist them in determining effective HRD. A computer-based decision support system (DSS) can fill this need by providing necessary recommendations and suggesting decision alternatives. Hence, developing such DSSs is always the priority in HL.
With respect to copyright, all the papers were excluded from the dissertation.
Has partsPaper I: Rahman, M. T., Comes, T. & Majchrzak, T. A. (2017). Understanding decision support in large-scale disasters: challenges in humanitarian logistics distribution. In M. I. Dokas, N. B. Saoud, J. Dugdale & P. Diaz (Eds.), Proceedings of the International Conference on Information Systems for Crisis Response and Management in Mediterranean Countries (p. 106-121). Springer. https://doi.org/10.1007/978-3-319-67633-3_9. Published version. Full-text is not available in AURA as a separate file.
Paper II: Rahman, M. T., Majchrzak, T. A. & Comes, T. (2019). Deep uncertainty in humanitarian logistics operations: decision-making challenges in responding to large-scale natural disasters. International Journal of Emergency Management, 15(3), 276-297. https://doi.org/10.1504/IJEM.2019.10023857. Published version. Full-text is not available in AURA as a separate file.
Paper III: Rahman, M. T. (2018). Pragmatism in decision support system research: the context of humanitarian relief distribution. International Journal of Information Systems for Crisis Response and Management, 10(3), 63-83. https://doi.org/10.4018/IJISCRAM.2018070104. Published version. Full-text is not available in AURA as a separate file.
Paper IV: Rahman, M. T., Majchrzak, T. A., Comes, T. & Sein, M. K. (Forthcoming). A conceptual framework to support decision-making in humanitarian relief operations. Author´s submitted manuscript. Full-text is not available in AURA as a separate file.
Paper V: Rahman, M. T. & Majchrzak, T. A. (2020). Requirements for relief distribution decision support in humanitarian logistics. In A. Siarheyeva, C. Barry, M. Lang, H. Linger & C. Schneider (Eds.), Advances in information systems development. Lecture Notes in Information Systems and Organisation, 39, 93-112. Springer. https://doi.org/10.1007/978-3-030-49644-9_6. Published version. Full-text is not available in AURA as a separate file.