scholarly journals Assessment of the level of business readiness for digitalization using marketing and neural network technologies

2019 ◽  
Vol 15 (3) ◽  
pp. 42-59
Author(s):  
Nadiia Yasynska ◽  
Inna Fomichenko ◽  
Olena Voloshyna ◽  
Lada Byvsheva ◽  
Ekaterina Krikunenko

The marketing environment of the world economy is changing due to intensive digitalization of trade exchange operations. Formation of marketing forecasts based on current and past periods in modern conditions is irrelevant to the current situation. The purpose of the article is to assess the situational precedents of business readiness for digitalization based on monitoring data, operating environment, applications and management system when using the tools of marketing and neural network modeling. The article uses a systematic approach and methods of statistical, financial and marketing analysis, tools for modeling a neural network. Based on the estimated indicators, the current and forecasted levels of electronic retail in the world are revealed. Based on the application of the concept of portfolio analysis to the data of national and international monitoring, а marketing model of research has been built, in which low business efficiency has been determined, situational modeling of business readiness for digital transformation has been carried out and characteristics of the identified precedents have been given. A low degree of business readiness to digitize the economy has been established. The results emphasize the importance of monitoring business readiness for the digitalization of the economy in real time with marketing and neural network modeling.

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Džemila Agić́ ◽  
Halid́ Makic ◽  
Gorań Tadic ◽  
Miladiń Gligoric ◽  
Sejfudiń Agic

According to the report of the World Health Organization, the city of Tuzla is the second in the world, and the first in Europe in terms of the number of diseases caused by air pollution. Tuzla Canton since 2003 has continuous air monitoring. Concentrations of individual pollutants exceed hourly, daily and annual limit values. In this paper, based on the existing results of air monitoring and meteorological data, using statistical methods and neural network modeling methods, unique and reliable models for predicting the concentration of NO2 in the air for the City of Tuzla have been developed. The results obtained using these models can be used in strategic decision-making processes and activities related to air quality control and management. This paper, on the example of the City of Tuzla, showed that using existing air monitoring data, concentrations of pollutants can be predicted for a longer period of time, using artificial intelligence methods. Reliable models with a high correlation coefficient can be obtained. In the case of a short or long interruption of the measurement of pollutant concentrations for the City of Tuzla with the help of models, which are the result of this work, it is possible to predict the concentrations of pollutants and plan to take measures based on them.


2009 ◽  
Vol 29 (6) ◽  
pp. 1529-1531 ◽  
Author(s):  
Wei-ren SHI ◽  
Yan-xia WANG ◽  
Yun-jian TANG ◽  
Min FAN

2012 ◽  
Vol 34 (6) ◽  
pp. 1414-1419
Author(s):  
Qing-bing Sang ◽  
Zhao-hong Deng ◽  
Shi-tong Wang ◽  
Xiao-jun Wu

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