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DC Field | Value | Language |
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dc.contributor.author | Gavkalova N. L. | - |
dc.contributor.author | Lola Y. Y. | - |
dc.contributor.author | Prokopovych S. V. | - |
dc.contributor.author | Sybirtsev V. | - |
dc.contributor.author | Diachek V. | - |
dc.date.accessioned | 2021-02-22T08:48:37Z | - |
dc.date.available | 2021-02-22T08:48:37Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Gavkalova N. Neural Network Modeling of E-Government Development and the Socio-Economic Environment / N.Gavkalova., Y. Lola., S. Prokopovych. other // International Journal of Advanced Science and Technology.- 2020. - 29(8 Special Issue). - Р. 2379–2384. | ru_RU |
dc.identifier.uri | http://repository.hneu.edu.ua/handle/123456789/24745 | - |
dc.description.abstract | Many studies are devoted to the peculiarities of the information society, new level of interaction between government, business and citizens, assessment of the E-government progress in developed and developing countries. This paper examines the influence of the e-government development on the economic, social and political activities of modern society. The correlation and regression analysis and Neural network modeling has been used to identify the relationship between the E-Government Development Index (EGDI), the Doing Business (DB), the Global Competitiveness Index (GCI) and the Democracy Index (DI). The results demonstrate that there is a close link between the level of e-Government development and the countries’ economic, social and political attractiveness. However, it is not equal for different countries. | ru_RU |
dc.language.iso | en | ru_RU |
dc.subject | the E-Government Development | ru_RU |
dc.subject | the Democracy Index | ru_RU |
dc.subject | the Doing Business | ru_RU |
dc.subject | the Global Competitiveness Index | ru_RU |
dc.title | Neural Network Modeling of E-Government Development and the Socio-Economic Environment | ru_RU |
dc.type | Article | ru_RU |
Appears in Collections: | Статті (ДУПАЕП) |
Files in This Item:
File | Description | Size | Format | |
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SCOPUS_Neural_Network_Modeling_2019.pdf | 778,17 kB | Adobe PDF | View/Open |
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