Strategy competition as an expert judgment procedure

2016 ◽  
Keyword(s):  
Expert Judgment

scholarly journals To Weight or Not to Weight, That Is the Question: The Design of a Composite Indicator of Landscape Fragmentation

2021 ◽  
Vol 11 (7) ◽  
pp. 3208
Author(s):  
Andrea De Montis ◽  
Vittorio Serra ◽  
Giovanna Calia ◽  
Daniele Trogu ◽  
Antonio Ledda
Keyword(s):  
Principal Component Analysis ◽  
Geometric Mean ◽  
Composite Index ◽  
Weighted Average ◽  
Principal Component ◽  
Expert Judgment ◽  
Landscape Fragmentation ◽  
Composite Indicator ◽  
Per Se ◽  
Higher Sensitivity

Composite indicators (CIs), i.e., combinations of many indicators in a unique synthetizing measure, are useful for disentangling multisector phenomena. Prominent questions concern indicators’ weighting, which implies time-consuming activities and should be properly justified. Landscape fragmentation (LF), the subdivision of habitats in smaller and more isolated patches, has been studied through the composite index of landscape fragmentation (CILF). It was originally proposed by us as an unweighted combination of three LF indicators for the study of the phenomenon in Sardinia, Italy. In this paper, we aim at presenting a weighted release of the CILF and at developing the Hamletian question of whether weighting is worthwhile or not. We focus on the sensitivity of the composite to different algorithms combining three weighting patterns (equalization, extraction by principal component analysis, and expert judgment) and three indicators aggregation rules (weighted average mean, weighted geometric mean, and weighted generalized geometric mean). The exercise provides the reader with meaningful results. Higher sensitivity values signal that the effort of weighting leads to more informative composites. Otherwise, high robustness does not mean that weighting was not worthwhile. Weighting per se can be beneficial for more acceptable and viable decisional processes.

Resilience Estimation of Critical Infrastructure Systems: Application of Expert judgment

2021 ◽  
pp. 107849
Author(s):  
Adel Mottahedi ◽  
Farhang Sereshki ◽  
Mohamad Ataei ◽  
Ali Nouri Qarahasanlou ◽  
Abbas Barabadi
Keyword(s):  
Critical Infrastructure ◽  
Expert Judgment ◽  
Infrastructure Systems ◽  
Critical Infrastructure Systems

scholarly journals Epistemic Uncertainty Analysis: An Approach Using Expert Judgment and Evidential Credibility

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Patrick Hester
Keyword(s):  
Decision Making ◽  
Probability Theory ◽  
Air Force ◽  
Subject Matter ◽  
Epistemic Uncertainty ◽  
Expert Judgment ◽  
Decision Makers ◽  
Expert Analysis ◽  
Physical Attributes ◽  
The Subject

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

Health risk assessment for nanoparticles: A case for using expert judgment

2007 ◽  
pp. 137-156 ◽  
Author(s):  
Milind Kandlikar ◽  
Gurumurthy Ramachandran ◽  
Andrew Maynard ◽  
Barbara Murdock ◽  
William A. Toscano
Keyword(s):  
Risk Assessment ◽  
Health Risk ◽  
Health Risk Assessment ◽  
Expert Judgment
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