Authors:
Rumiko Azuma
1
and
Shinya Nozaki
2
Affiliations:
1
Aoyama Gakuin University, Japan
;
2
University of the Ryukyus, Japan
Keyword(s):
Decision-making Model, Implicit Evaluation, Principal Component Analysis, Analytic Hierarchy Process.
Related
Ontology
Subjects/Areas/Topics:
Decision Analysis
;
Decision Support Systems
;
Information Systems
;
Methodologies and Technologies
;
Operational Research
Abstract:
The Analytic Hierarchy Process (AHP) is a decision-making method for smoothly managing problems, criteria, and alternatives. AHP can be used to respond to multiple criteria, and allows for the quantification of subjective human judgments, as well as objective evaluations. In a classical AHP, a decision-maker derives a list of priorities by consciously comparing criteria and alternatives in order to deriving a comprehensive evaluation. However, when the number of criteria increases, the problem also becomes complicated and the subjective judgment of the decision-maker tends to be clouded by ambiguity and inconsistency. As the solution, this study proposes a method whereby latent elements are extracted from the data given by the decision-maker, and an evaluation is made from a different aspect based on the extracted elements. This allows for the construction of a model in which a decision is made from both explicit and implicit elements by making a final synthesis of the results obtain
ed using the conventional method as well as the evaluation obtained using the method proposed in this study. As a result, we can conclude that it is possible to make a decision that is not affected by the ambiguity or inconsistency of the decision-maker.
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