Page 59 - Azerbaijan State University of Economics

A.D.Huseynova, O.I.Mazanova: Model of a evaluation of an innovative capital of the
subjects on the basis

methods of expert evaluations cannot be used in their pure form because of their
serious drawbacks (Table 1).
Therefore usually the method of expert evaluations and the statistical method
co-exist in an analysis of the economic indicators, which have digital presentations.
In this case drawbacks of one method are compensated for by the advantages of
another. However such a combined approach to evaluation of economic indicators
also has its drawbacks. This is connected with the fact that an accuracy of evaluation
of a probability of realization of an event depends on a number of factors, beginning
from the quality of the statistical information and finishing with the expert
evaluations: uncertainty is present in evaluation of this or that economic indicator.

Table 1.Comparison of the basic methods for analysis of social and economic
indexes
Methods for
evaluation of Positive characteristics Negative characteristics
indicators
 Subjectivity of the
expert evaluations;
Method of  Not always based on
expert Evaluation of the quality indicators is possible
evaluations mathematical
calculations;
 Labor intensiveness
 Inaccuracy due to
absence of a big entire
Statistical sample of the initial data;
method Based on mathematical calculations and numerical data
 Impossibility to
evaluate the qualitatively
expressed indicators
Allows:
- To use the data of a non-numerical nature and the data,
characterized as quasi-statistics;
- To obtain more reliable data in the conditions of a low
statistical sample;
- To form a full range of possible scenarios for
evaluation of an innovative potential;
- To obtain evaluations in the form of a point value and
in the form of a multitude of interval values with its
Fuzzy set distribution of possibilities characterized by the Labor intensiveness when
method (non- the method is for first
numerical membership function of the corresponding fuzzy number, time applied for a
which opens opportunities for forecasting and evaluation
statistics) of risks; concrete object of
research
- To operate with a not absolutely accurate set of a
membership function, but with interval values (unlike
probabilistic methods, the result on the basis of fuzzy-
interval descriptions is characterized by a low sensitivity
to the change of the membership functions of the initial
fuzzy numbers, which in real conditions makes
application of the given method more substantiated);
- To reveal successfully expert knowledge with
possibility of its formalization.

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