Volume 10 • Issue 3 • July-September 2018
Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Mohammad Taqur Rahman, University of Agder, Kristiansand, Norway
Decision making on relief distribution is a complex multidisciplinary task in humanitarian logistics.
It incorporates decision makers from different but related problem areas. The failure to perform
assigned decision-making tasks in any area makes the entire system unstable and delays the relief
distribution process. An organized, well-planned, and practical decision support system (DSS) can
assist practitioners in making rapid decisions on delivering relief items. Hence, DSS researchers in
humanitarian logistics require rigorous thinking, close and critical analysis, and the identification
of challenges to conduct research or validate the generated knowledge properly. To perform such
complex knowledge-based tasks, the philosophical understanding of DSS in the humanitarian context
is necessary. After analyzing the commonly used philosophical paradigms, this research identifies
the pragmatic approach as the adequate support for solving decision-making problems in relief
distribution during large-scale disasters.
Axiology, Critical Realism, Decision Support Systems, Epistemology, Humanitarian Logistics, Information
Systems, Interpretivism, Methodology, Ontology, Paradigms, Philosophy, Positivism, Pragmatism
A decision support system (DSS) is a human–computer joint venture for identifying alternative
solutions to complex decision-making problems in shorter durations. DSS research in humanitarian
logistics (HumLog) supports relief distribution as it incorporates multidisciplinary problems and thus
a larger number of researchers and practitioners from different operational areas. To distribute relief
items efficiently and effectively, a DSS research team should have experts for (i) assessing the need
(information management), (ii) selecting potential suppliers to procure assessed relief items (supply
chain management), (iii) warehousing those procured relief items (facility location) and finally,
scheduling and delivering them (transportation) to the demand points (Blecken, 2010). In addition
to that, decision making in large-scale disasters faces challenges due to events’ unstable, dynamic,
and unpredictable nature that brings thousands of independent, informal, and/or hastily organized
responders who are far from united (Comes, Van de Walle, Laguna, & Lauras, 2015; Holguín-Veras,
Jaller, Van Wassenhove, Pérez, & Wachtendorf, 2012). Thus, in such situations, the number of
decision-making problems increases along with the number of decision makers and the ways they
utilize to make decisions (Comes et al., 2015).
Tackling these complex and challenging problems for effective response to such disastrous events,
decision-making operations require aligned and concurrent decisions among six different problem
Volume 10 • Issue 3 • July-September 2018
areas: relief supply chain, facility location, inventory management, transportation, relief distribution,
and scheduling (Baharmand, Salvadό, Comes, & Lauras, 2015; Comes et al., 2015; Gupta, Starr,
Farahani, & Matinrad, 2016; Peres, Brito, Leiras, & Yoshizaki, 2012; Roy, Albores, & Brewster,
2012; Holguín-Veras et al., 2012). This research concentrates on decision-making problems in relief
distribution during large-scale disasters.
While delivering humanitarian goods, decision makers face challenges in every step of the
process, from demand allocation to relief distribution (Cordeiro, Campos, & Borges, 2014). To
produce rapid decision making, humanitarian responders need assistance from DSSs to understand
all types of flows (material, resource, information, etc.), potential and involved stakeholders (donors,
suppliers, volunteers, etc.), transport networks and planning (road links, vehicles, scheduling, etc.),
and decision-making processes (models, frameworks, applications, etc.) in each of the related problem
areas. Therefore, DSS research concentrates on human values in both individual and collective forms
to develop knowledge by bringing diversity in views, thoughts, and concepts about practical problems.
The knowledge developed in DSS research been accumulated by many researchers over time. To
understand their contributions to the establishment and advancement of DSS research, a detailed study
on this field’s research philosophy plays a vital role (Hirschheim & Klein, 1989). A philosophical
analysis can explain the overall idea of the research field: (i) its roots, (ii) how it is developed, (iii) the
assumptions it holds, (iv) the knowledge developed and the way to extend it, (v) research strategies
and methods to select or produce research designs apposite to the investigated phenomena, and (vi)
philosophical issues that researchers may encounter (Artz, 2013; Ihuah & Eaton, 2013). As DSSs in
the humanitarian context incorporate multiple academic research areas, it is necessary to investigate
how the overall information system contributes to modeling aspect of the real world through knowledge
identification (ontology), how this acceptable knowledge is constituted (epistemology) by utilizing
which actions or techniques (methodology), and whether this knowledge is ethically appropriate in
evaluating researchers’ personal values (axiology). Since DSSs involve the process of knowing the
reality by gathering and interpreting data for their users, philosophical understanding is implicit in
every DSS to extend human decision-making capabilities (Carrier & Wallace, 1989). The system must
know (or should be provided with) the reality and how to perceive it. Otherwise, destructive instead
of productive decisions may be made. Philosophical knowledge can guide researchers in selecting
appropriate tools to produce better solutions to the targeted problems (Wade & Hulland, 2004).
Decision making in HumLog differs from that in businesses, for example, where DSSs are
fed with proper information to produce appropriate decision alternatives. Humanitarian DSSs
concentrate on practical implementation of research outcomes rather than just explaining how and
why phenomena occur, developing contextual understandings, and identifying the best way of solving
a problem. Based on individual problem areas, humanitarian DSS researchers practically follow a
positivist approach while utilizing scenario creation or a table-top exercise with controlled variables,
as well as an interpretive approach while utilizing case studies, field works, and interviews to explore
affective parameters for better decision making. For effective decision support in relief distribution,
it is necessary to tackle decisions in all problem areas concurrently, not separately as has been done
so far (Roy et al., 2012). When developing the system, DSS researchers must think of pragmatically
tackling the unplanned issues arising during the operation. Although different responders exploit
varying mechanisms to implicitly solve operational problems while distributing relief items, the field
requires an explicit knowledge base to handle such problems so that future research can be undertaken
with proper guidance. By understanding the above-mentioned consequences, this article attempts to
answer the research questions:
Which paradigm is suitable for guiding DSS research in HumLog to solve decision-making problems
in the relief distribution process? Why and how is it suitable?
19 more pages are available in the full version of this
document, which may be purchased using the "Add to Cart"
button on the product's webpage:
This title is available in InfoSci-Civic Engagement,
Sustainable Planning, and Crisis Response eJournal
Collection, InfoSci-Management Science and Organizational
Research eJournal Collection, InfoSci-Surveillance, Security,
and Defense eJournal Collection, InfoSci-Journals, InfoSci-
Journal Disciplines Communications and Social Science,
InfoSci-Journal Disciplines Business, Administration, and
Management. Recommend this product to your librarian:
WiPo for SAR: Taking the Web in Your Pocket When Doing Search and
Rescue in New Zealand
Karyn Rastrick, Florian Stahl, Gottfried Vossen and Stuart Dillon (2019). Emergency
and Disaster Management: Concepts, Methodologies, Tools, and Applications (pp.
Security of Dependable Systems
Naveed Ahmed and Christian Damsgaard Jensen (2014). Crisis Management:
Concepts, Methodologies, Tools, and Applications (pp. 131-165).
Learning from Accidents: A Systematic Review of Accident Analysis Methods
Hans Wienen, Faiza Allah Bukhsh, Eelco Vriezekolk and Roel J. Wieringa (2018).
International Journal of Information Systems for Crisis Response and Management
Influence Factors for Innovation in Digital Self-Preparedness Services and
Iris Gräßler, Jens Pottebaum and Philipp Scholle (2018). International Journal of
Information Systems for Crisis Response and Management (pp. 20-37).