The Management of Regional Information Space in the Conditions of Digital Economy
The article suggests an original uniquely designed model based on the entropic approach and the method determining the synergizing effect from the convergence of information spaces in the context of the digital economy. The model includes a 3D-modeling-built surface characterizing the reduction of t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Russian Academy of Sciences, Institute of Economics of the Ural Branch
2018-12-01
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| Series: | Экономика региона |
| Subjects: | |
| Online Access: | http://economyofregion.com/current/2018/71/3108/pdf/ |
| _version_ | 1797724986069221376 |
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| author | Sergey Alexeevich Dyatlov Oleg Sergeevich Lobanov Weidi Zhou |
| author_facet | Sergey Alexeevich Dyatlov Oleg Sergeevich Lobanov Weidi Zhou |
| author_sort | Sergey Alexeevich Dyatlov |
| collection | DOAJ |
| description | The article suggests an original uniquely designed model based on the entropic approach and the method determining the synergizing effect from the convergence of information spaces in the context of the digital economy. The model includes a 3D-modeling-built surface characterizing the reduction of the entropy of information systems clusters in the regional information space, which occurs in the process of network convergence. This model defines the entropy changes for the information systems clusters with the most typical parameters based on “The State Information System Registry of St. Petersburg” in terms of the number of modules, general typology, and functional purpose. Moreover, the model considers ranges of specific indicators characterizing the real regional information systems of St. Petersburg. We have concluded that the synergetic effects of convergence in the context of the digital economy lead to a reduction in the regional information space entropy. We have discovered that the increasing number of the converged clusters of information spaces leads to a stable entropy decrease in them. These features allow numerically describing the discovered convergence effects and estimating the effect of digital structural transformations of the economic system on the information space of a region in terms of its management efficiency. We have concluded that increasing the number of information systems involved in the digital convergence processes causes a more considerable entropy reduction and, consequently, a more significant increase in the effectiveness of regional system management. The research has revealed a relevant area of cross-disciplinary research, which consists in the emergence of a whole class of new neural network in the modern digital neural network economy. This research is of practical significance in developing new management algorithms and making effective managerial decisions in the conditions of large-scale digitalization and networking of regional and national management. |
| first_indexed | 2024-03-12T10:24:43Z |
| format | Article |
| id | doaj.art-85885d5e1b8b408fa05da2744e646edf |
| institution | Directory Open Access Journal |
| issn | 2072-6414 2411-1406 |
| language | English |
| last_indexed | 2024-03-12T10:24:43Z |
| publishDate | 2018-12-01 |
| publisher | Russian Academy of Sciences, Institute of Economics of the Ural Branch |
| record_format | Article |
| series | Экономика региона |
| spelling | doaj.art-85885d5e1b8b408fa05da2744e646edf2023-09-02T09:50:28ZengRussian Academy of Sciences, Institute of Economics of the Ural BranchЭкономика региона2072-64142411-14062018-12-011441194120610.17059/2018–4–11The Management of Regional Information Space in the Conditions of Digital EconomySergey Alexeevich Dyatlov0Oleg Sergeevich Lobanov1Weidi Zhou2Saint-Petersburg State University of EconomicsSaint-Petersburg State University of EconomicsSchool of Economics & Business Administration, Central China Normal UniversityThe article suggests an original uniquely designed model based on the entropic approach and the method determining the synergizing effect from the convergence of information spaces in the context of the digital economy. The model includes a 3D-modeling-built surface characterizing the reduction of the entropy of information systems clusters in the regional information space, which occurs in the process of network convergence. This model defines the entropy changes for the information systems clusters with the most typical parameters based on “The State Information System Registry of St. Petersburg” in terms of the number of modules, general typology, and functional purpose. Moreover, the model considers ranges of specific indicators characterizing the real regional information systems of St. Petersburg. We have concluded that the synergetic effects of convergence in the context of the digital economy lead to a reduction in the regional information space entropy. We have discovered that the increasing number of the converged clusters of information spaces leads to a stable entropy decrease in them. These features allow numerically describing the discovered convergence effects and estimating the effect of digital structural transformations of the economic system on the information space of a region in terms of its management efficiency. We have concluded that increasing the number of information systems involved in the digital convergence processes causes a more considerable entropy reduction and, consequently, a more significant increase in the effectiveness of regional system management. The research has revealed a relevant area of cross-disciplinary research, which consists in the emergence of a whole class of new neural network in the modern digital neural network economy. This research is of practical significance in developing new management algorithms and making effective managerial decisions in the conditions of large-scale digitalization and networking of regional and national management.http://economyofregion.com/current/2018/71/3108/pdf/digital economytechnological revolutionneural networkmanagemententropy approachregional information spacesnetwork convergenceneural network effectsinfrastructureinformatization |
| spellingShingle | Sergey Alexeevich Dyatlov Oleg Sergeevich Lobanov Weidi Zhou The Management of Regional Information Space in the Conditions of Digital Economy Экономика региона digital economy technological revolution neural network management entropy approach regional information spaces network convergence neural network effects infrastructure informatization |
| title | The Management of Regional Information Space in the Conditions of Digital Economy |
| title_full | The Management of Regional Information Space in the Conditions of Digital Economy |
| title_fullStr | The Management of Regional Information Space in the Conditions of Digital Economy |
| title_full_unstemmed | The Management of Regional Information Space in the Conditions of Digital Economy |
| title_short | The Management of Regional Information Space in the Conditions of Digital Economy |
| title_sort | management of regional information space in the conditions of digital economy |
| topic | digital economy technological revolution neural network management entropy approach regional information spaces network convergence neural network effects infrastructure informatization |
| url | http://economyofregion.com/current/2018/71/3108/pdf/ |
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