Supporting Humanitarian Relief Distribution Decision-Making

The disputation will be held digitally, because of the Corona covid-19-situation. Spectators may follow the disputation digitally – link is available below.

Mohammad Tafiqur Rahman of the Faculty of Social Sciences at the University of Agder has submitted his thesis entitled “Supporting Humanitarian Relief Distribution Decision-Making under Deep Uncertainty.

A System Design Approach” and will defend the thesis for the PhD-degree Wednesday 13 January 2021.  

He has followed the PhD-programme at the Faculty of Social Sciences with Specilisation in Information Systems.

Summary of the thesis by Mohammad Tafiqur Rahman

Supporting Humanitarian Relief Distribution Decision-Making

Disasters threaten society with widespread destruction of infrastructure and livelihood.

To respond quickly in such crucial moments, humanitarian decision-makers (HDMs) act rapidly to distribute necessary relief goods, despite the deep and prevailing uncertainty that arises from scarce, conflicting, and uncertain information.

Existing models are scenario-specific

The literature avails various mathematical models to support HDMs in humanitarian relief distribution (HRD) decision-making.

These models are scenario-specific and mostly detached from the realities of the field. Although they produced good results when tested, they were not implemented in practice because of their operational inconsistency or complexity (i.e., lack of user-friendliness).

Practitioners not involved

In most cases, end-users (mainly practitioners) were found absent in the development process. So, for determining effective HRD, practitioners-participated decision support systems (DSS) are still needed.

Hence, developing computer-based DSSs is always the priority in humanitarian logistics (HL) to achieve necessary recommendations and suggestions on decision alternatives.

Supporting decisions

This research, therefore, attempts to model an IS to profile decision-making requirements and their interconnectedness—thereby developing the envisioned DSS.

So, it sets its research question (RQ) to identify “How can decisions in HRD be supported under deep uncertainty?”

By answering this RQ, this dissertation conceptualizes HRD as an operational ecosystem to model its DSS design.

Such a conceptualization will help researchers generating different decision models not only by identifying and combining various decision factors encompassed in different problem areas, but also recognizes their interconnections with and influences (or affects) to HRD decision-making.

Doable decision-making

Since the success of humanitarian operations (e.g., HRD) mostly depends on doable decision-making, this research argues for developing potential DSSs in task-oriented ways.

Finally, practitioners can save decision-making time by consulting the proposed prioritized lists of decision factors since faster decisions can be made if they are supported with the necessary information and with the essential decision variables and constraints for achieving specific objectives.

What to do as an audience member:

The disputation is open to the public, but to follow the trial lecture and the public defence, which is transmitted via the Zoom conferencing app, you have to register as an audience member.

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Opponent ex auditorio:

The chair invites members of the public to pose questions ex auditorio in the introduction to the public defense, with deadlines. Questions can be submitted to the chair, Dean Anne Halvorsen, at e-mail anne.halvorsen@uia.no