JEL Classification: C 10; C 13; D 89; M 11; O 10.
Sharko Margarita, Doctor of Economics, Professor, Head of Department of Economics and Entrepreneurship, Kherson National Technical University, Kherson, Ukraine.
Gusarina Nataliya, PhD in Economics, Associate Professor, Department of Economics and Entrepreneurship, Kherson National Technical University, Kherson, Ukraine.
Implementation of the concept of added academic value in the foreshortening of the economy and society of knowledge
Abstract. Innovative development of production in the current context becomes relevant due to an increase in the level of uncertainty. All this requires enterprises to use new approaches for doing business. Therefore, enterprises are increasingly focusing on the analysis of economic information indicators and their ranking, since they generally determine the features of innovative development. Economic data of business processes are classified as weakly structured and hard-formalized, for which incompleteness, ambiguity and uncertainty of input data are typical. Therein, it is difficult to single out a sole formal criterion. When solving them, it is necessary to apply a complex of various indicators, which is based on the different degree of informational content.
Purpose. The purpose of this article seeks in the development of a methodology for business analysis of economic indicators and their ranking on the priorities of informational content. In the paper, the authors based on a combination of factors of production and information systems, analyzed the approaches of expert estimation of ranking, described the main features of building a scale of relations, considered obstacles and difficulties in solving the problems of business analytics of ranking in the context of uncertainty, classification stages of determining the quality ranks and the degree of pertaining to the rank. A model for estimating input information on the innovative development of enterprises-factors describing production activity, determined by means of Bayes’ formula allowing to precise and list the probability values by using both known information and data of new observations in subsequent years was proposed.In order to exclude the subjectivity of experts it was suggested to consider the degree of uncertainty of the true value of economic indicators as the entropy of their input information. It was established that the most informative parameter of business analytics of enterprises economic growth is the parameter, in which the difference between a priori and a posteriori information is of the least value.
Results. The results of the conducted studies should be used to make the decisions on innovative development of productions, based on the ranking of information, contained in the economic indicators.
Conclusions. In further studies, it is planned to scientifically substantiate the developing of trends and determining the forecast values of financial and economic indicators against the background of the environmental changes effect.
Keywords: Bayes’ theorem; estimation; information; uncertainty; production management; economic development.
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