Yuliia SYNYTSINA
Candidate of Technical Sciences, Associate Professor (Dnipropetrovsk State University of Internal Affairs), Ukraine
ORCiD orcid.org/0000-0002-6447-821X
mail@dduvs.in.ua
Serhii ABRAMOV
Candidate of Technical Sciences, Associate Professor (Ukrainian State University of Science and Technology), Ukraine
ORCID orcid.org/0000-0003-0675-4850
abramovs706@gmail.com
Alexandru MANOLE
D.Sc. in Philosophy, Professor (Artifex University of Bucharest), Romania
universitate@artifex.org.ro
UDC 658.5
DOI 10.31733/2786-491X-2022-1-127-138
Keywords: marketing environment, information system, neural network, decision making, forecasting
Abstract. It is offered to consider practical aspects of application of neural networks (NN) in the marketing information system (MIS) of the enterprise. The aim of the research is to improve the information system of the enterprise by introducing an intellectual decision support system (IDSS) with the use of the neural network and considering its capabilities in forecasting the state of the marketing environment. As a result of the study, recommendations for the use of such an improved system have been developed and testing has been carried out in three directions. The first direction is the forecasting of the indicators of the macro environment of the company as the main factor of the marketing environment, by developing an appropriate mathematical model, in order to implement appropriate exit strategies for external markets. The second direction is the use of NN in forecasting the state of the elements of the internal environment of the enterprise, for example, an enterprise providing engineering services. The third direction the approbation proved the effectiveness of the application of NN for the forecast of macroeconomic indicators.
Consequently, the proposed subsystem of analysis and forecasting on the basis of the IDSS with the use of NN will enable to predict the indicators of the marketing environment of the enterprise. On this basis, managers will be able to make informed decisions based on the information foundation, adequate actions, skilled performance and, as a result, to ensure the success of the entire enterprise.
The specificity of the IDSS with the neural network proposed in the study is that decision support from different functional areas of the enterprise is supported on the basis of predictive results obtained through neural networks. The development of the proposed method is due to the need for training artificial neural networks for intelligent decision support systems, in order to process more information.
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