Applying Interpretive Structural Modeling and MICMAC Analysis to Evaluate Inhibitors to Transparency in Humanitarian Logistics
Abstract
ABSTRACT
The main purpose of this study is to identify the variables for the lack of transparency in humanitarian logistics (HL) and to determine their mutual relationship. The interpretive structure modeling (ISM) method was applied to extend a hierarchy-based model of the identified variables. The study makes two key contributions: the variables that can be reflected as inhibitors to transparency in HL are determined, and the ISM methodology is used to determine the group of variables that have full control, low reliance and strategic importance. The study findings are beneficial for all stakeholders of disaster risk reductions.
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