AN ESTIMATE OF THE AMOUNT OF INFORMATION FOR ADEQUATE FORECASTING CHANGES IN THE EXTERNAL ENVIRONMENT UNDER CONDITIONS OF UNCERTAINTY
Journal Title: ЕКОНОМІЧНИЙ ДИСКУРС - Year 2018, Vol 1, Issue 1
Abstract
Introduction. The relevance of the study is due to the fact that the main problem for forecasting the innovative development of enterprises under the influence of the environment is to obtain the required volume of quality information, since its small number reduces the accuracy of forecasts, and the greater number is associated with the difficulties of processing the production data. Methods. The methods of forecasting and identification are used in the management of the innovative development of industrial enterprises,, where the task of the forecast according to the data of observations is to predict future values of economic indicators, the task of identification is to determine the parameters of the system that created to this time range; as for building a model for estimation of the information total amount, the financial and economic indicators of the enterprise are used. Results. The model of the required amount of input information is suggested at making managerial decisions on innovative development of enterprises in conditions of uncertainty. The model is based on the difference between a priori and a posteriori information. The experimental verification of the representativeness of the input information is carried out on the basis of the analysis of economic dynamicsindicators, using the Bayesian theorem. As a result of the work, the values of a posteriori probability have been clarified, on the basis of which the calculations of the required amount of information for making forecasts are made. Discussion. Prospects for further research are to construct the trends of financial and economic indicators of the dynamic range in different time intervals to make forecasts of adequate changes in the external environment in conditions of uncertainty. The refined values of the a posteriori probability on the basis of which the calculations of the right amount of information to make predictions in this work.
Authors and Affiliations
Nataliya Gusarinа
Keywords
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