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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 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).