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THE GOAL-STRUCTURE APPROACH TO QUALITATIVE VALUATION
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THE GOAL-STRUCTURE APPROACH TO QUALITATIVE VALUATION
Annotation
PII
S042473880000487-4-1
Publication type
Article
Status
Published
Authors
Viktor Istratov 
Abstract

The author analyses qualitative valuation: while being frequently used in economic literature, very little attention is paid to the study of qualitative estimates themselves. As a consequence, qualitative assessments are often inconvenient to use because of the vagueness of their wording, which, in turn, generates discrepancies and misunderstandings. In addition, the ambiguity of the wording leads to the impossibility of comparing qualitative estimates, or substantially limits this possibility. Both ambiguity and incomparability are detrimental to the prospects for qualitative valuation as a scientific tool. In the current situation, it is necessary to develop a unified formulation approach (a language) to qualitative assessments to make them unambiguous and comparable. The author makes an attempt to formalize and standardize the presentation of qualitative values, and to find a method for their submission and formulation that differs from those already available. The article contains an overview of the approaches to qualitative assessments adopted in several areas of knowledge that are close to the computational economy and simulation modeling: in particular, in the economics, in artificial intelligence, and the others. The approach proposed in the article takes into account the goals with which a qualitative estimate is used. It involves the interpretation of a qualitative assessment as a complex element which structure plays the key role in understanding and applying the value. Qualitative assessment in this approach is not opposed to quantitative, and in some cases they are combined. The proposed approach may be useful in computer simulation of human behavior and socio-economic interactions.

Keywords
qualitative value, quality, economic valuation
Date of publication
01.04.2018
Number of purchasers
8
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762
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