Territorial Structure of the Russian Digital Economy
Preliminary Delimitation of Smart Urban Agglomerations and Regions
Bibliographic Data
| ID | 21219089 |
|---|---|
| Authors | В И Блануца (0000-0003-3958-216X, V. B. Sochava Institute of Geography, corresponding author), V I Blanutsa |
| Year | 2019 |
| Volume | 9 |
| Issue | 4 |
| Pages | 318-328 |
| Publication date | 2019-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Regional Research of Russia (JOURNAL) |
| Journal identifiers | ISSN: 2079-9713 • E-ISSN: 2079-9705 |
| Publisher | Pleiades Publishing Ltd (PUBLISHER) |
| DOI | 10.1134/s207997051904004x |
| OpenAlex | W2997604878 |
| Language | EN |
| Citations received | 2 |
| References cited | 21 |
The fourth industrial revolution will form a new digital economy in Russia, dominated by smart objects (factories, transport, roads, buildings, etc.) with artificial intelligence systems. There are currently no studies on identifying the territorial structure of Russia’s future digital economy. Due to the inertia of the existing settlement system and the agglomeration economy, it has been assumed that the future territorial structure will be represented by smart urban agglomerations and regions. It has been established that the most critical parameter for controlling smart objects is signal delay in telecommunication networks. It has been proposed to draw the borders of digital agglomerations and regions based on isochrons of 1 and 10 ms delays with adjustment of borders for the extreme proximity or remoteness of regional centers. The signal delay between 1112 cities of Russia has been determined. Forty-three digital agglomerations and 45 regions were selected. The results can be used to create a development strategy for Russia’s digital economy
Business · Digital economy · Economic geography · Economic growth · Economics · Economies of agglomeration · Economy · Geography · Urban agglomeration · Computer Science · Economic and Technological Systems Analysis · Smart Cities and Technologies · University-Industry-Government Innovation Models
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| Citations per year | 0.4 |
|---|---|
| Citation span | 2021 - 2024 (4) |
| Highly cited | No |