When dealing with complex systems, all decision making occurs under some level of uncertainty. This is due to the physical\r\nattributes of the system being analyzed, the environment in which the system operates, and the individuals which operate the\r\nsystem. Techniques for decision making that rely on traditional probability theory have been extensively pursued to incorporate\r\nthese inherent aleatory uncertainties. However, complex problems also typically include epistemic uncertainties that result from\r\nlack of knowledge. These problems are fundamentally different and cannot be addressed in the same fashion. In these instances,\r\ndecision makers typically use subject matter expert judgment to assist in the analysis of uncertainty. The difficulty with expert\r\nanalysis, however, is in assessing the accuracy of the expert�s input. The credibility of different information can vary widely\r\ndepending on the expert�s familiarity with the subject matter and their intentional (i.e., a preference for one alternative over\r\nanother) and unintentional biases (heuristics, anchoring, etc.). This paper proposes the metric of evidential credibility to deal with\r\nthis issue. The proposed approach is ultimately demonstrated on an example problem concerned with the estimation of aircraft\r\nmaintenance times for the Turkish Air Force.
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