45 research outputs found
Application of waste wood for receiving building materials
Organic building materials include wooden materials and items, polymer-based materials and also organic binders and bitumen-based materials. The properties of wood, its application are described in the article
Application of waste wood for receiving building materials
Organic building materials include wooden materials and items, polymer-based materials and also organic binders and bitumen-based materials. The properties of wood, its application are described in the article
Evidence for preferential copackaging of Moloney murine leukemia virus genomic RNAs transcribed in the same chromosomal site
BACKGROUND: Retroviruses have a diploid genome and recombine at high frequency. Recombinant proviruses can be generated when two genetically different RNA genomes are packaged into the same retroviral particle. It was shown in several studies that recombinant proviruses could be generated in each round of HIV-1 replication, whereas the recombination rates of SNV and Mo-MuLV are 5 to 10-fold lower. The reason for these differences is not clear. One possibility is that these retroviruses may differ in their ability to copackage genomic RNAs produced at different chromosomal loci. RESULTS: To investigate whether there is a difference in the efficiency of heterodimer formation when two proviruses have the same or different chromosomal locations, we introduced two different Mo-MuLV-based retroviral vectors into the packaging cell line using either the cotransfection or sequential transfection procedure. The comparative study has shown that the frequency of recombination increased about four-fold when the cotransfection procedure was used. This difference was not associated with possible recombination of retroviral vectors during or after cotransfection and the ratios of retroviral virion RNAs were the same for two variants of transfection. CONCLUSIONS: The results of this study indicate that a mechanism exists to enable the preferential copackaging of Mo-MuLV genomic RNA molecules that are transcribed on the same DNA template. The properties of Mo-MuLV genomic RNAs transport, processing or dimerization might be responsible for this preference. The data presented in this report can be useful when designing methods to study different aspects of replication and recombination of a diploid retroviral genome
ASSESSMENT AND IDENTIFICATION OF THE POSSIBILITY FOR CREATING IT CLUSTERS IN Kazakhstan REGIONS1
The paper is devoted to the development of general methodological approaches to evaluate and identify the possibility for creating IT clusters in Kazakhstan regions. The present study considers the formation of IT clusters as growth poles. These poles are based on the establishing the groups of interconnected companies and institutions in IT industry linked by commonalities. The analysis of previous literature has shown that this approach is a novel approach to IT clusters formation. The study employs methods, which focus on analyzing and identifying IT clusters in the interests of innovative development and the possibility of spreading information technology in Kazakhstan regions. We propose the methodological tools for presenting a standard form to assess innovative potential and industry specialization. This assessment allows to objectively and realistically define a potentially important region for creating IT cluster. The empirical analysis has identified certain trends in possibilities to create IT clusters in the cities of Almaty and Astana. Therefore, these regions play the role of specialized platforms for a new generation. This platform is to provide a multiplier effect on the development of the agglomeration and located in close territories or periphery. The results of this research can be used to elaborate important strategic documents in the field of the development of the IT industry, digital technology, knowledge-based and high-tech sectors in Kazakhstan on the way to Industry 4.0. Β© 2018 Institute of Economics, Ural Branch of the Russian Academy of Sciences. All rights reserved
Evaluation of interspecific populations of grapevine in breeding for complex resistance to fungal diseases and phylloxera
Roentgenoscopy was used as a method to determine the quality of hybrid seeds and to predict the development of viable plants from interspecific hybridization. The seeds were grouped into five classes of quality (embryo classes) depending on embryo size and degree of endosperm development As the index number of a class increased, the proportion of plantlets and vigorous plants produced also increased. In order to evaluate genotypic peculiarities of the original forms and seedlings, the seedlings were studied at the juvenile stage of ontogeny. Analysis of development of the hybrids studied during 5-6 years under conditions of complex infection pressure at a special planting site made it possible to evaluate the degree of their resistance to phylloxera, pathogenic soil microflora and fungal diseases and to eliminate susceptible genotypes. The heritability of resistance to fungal diseases (mildew, oidium, grey rot) and phylloxera was studied, conclusions were made concerning the combining ability of the original forms, and these forms were evaluated as donors of the desirable characters. Using transgressive resistant hybrids as donors in backcrossing provided improved quality with a broad range of resistance variability, which made it possible to select promising genotypes
Analysis of the Digital Readiness and the Level of the ICT Development in Kazakhstanβs Regions
The level of digital readiness and the application of information and communication technologies (ICT) are
key factors of any innovation policy. This research has highlighted the development of analysis of the degree of digital readiness and assessment methods of digital transformations, which can be used at various levels of business management to formulate digital transformation strategies. The present study investigates the theoretical framework in the field of innovation and spatial development considering the impact of the level of ICT. The research was conducted using index and economic-statistical methods based on a systematic approach.
We developed a methodological tool adapted to the regional management level. The ICT development index, Krugman localisation index and Herfindahl-Hirschman index were modified to analyse digital readiness and ICT development at the regional level. The algorithm includes the following steps: assessment of the internet usage level; analysis of the degree of costs for the production of ICT; evaluation of the digital literacy rate of the population; evaluation of the degree of regional industry specialisation in the field of ICT. It was revealed that Kazakhstanβs regions have varying levels of ICT development, which is why they have different prerequisites and prospects for digitalising their economy. The agglomerations that could become βgrowth polesβ of Kazakhstanβs knowledge-based economy were identified, such as Almaty city, Nur-Sultan city, Karaganda, and Aktobe regions. Government bodies can use the research findings for Kazakhstani territoriesβ digital modernisation
Analysis of the Digital Readiness and the Level of the ICT Development in Kazakhstanβs Regions
The level of digital readiness and the application of information and communication technologies (ICT) are
key factors of any innovation policy. This research has highlighted the development of analysis of the degree of digital readiness and assessment methods of digital transformations, which can be used at various levels of business management to formulate digital transformation strategies. The present study investigates the theoretical framework in the field of innovation and spatial development considering the impact of the level of ICT. The research was conducted using index and economic-statistical methods based on a systematic approach.
We developed a methodological tool adapted to the regional management level. The ICT development index, Krugman localisation index and Herfindahl-Hirschman index were modified to analyse digital readiness and ICT development at the regional level. The algorithm includes the following steps: assessment of the internet usage level; analysis of the degree of costs for the production of ICT; evaluation of the digital literacy rate of the population; evaluation of the degree of regional industry specialisation in the field of ICT. It was revealed that Kazakhstanβs regions have varying levels of ICT development, which is why they have different prerequisites and prospects for digitalising their economy. The agglomerations that could become βgrowth polesβ of Kazakhstanβs knowledge-based economy were identified, such as Almaty city, Nur-Sultan city, Karaganda, and Aktobe regions. Government bodies can use the research findings for Kazakhstani territoriesβ digital modernisation
ΠΡΠ΅Π½ΠΊΠ° Π½Π΅ΡΠ°Π²Π΅Π½ΡΡΠ²Π° ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π΄ΠΎΡ ΠΎΠ΄ΠΎΠ² ΠΈ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ ΠΠ°Π·Π°Ρ ΡΡΠ°Π½Π°
ΠΠ°ΠΆΠ½ΠΎΠΉ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΎΠΉ ΡΠ²Π»ΡΠ΅ΡΡΡ Π²ΠΎΠΏΡΠΎΡ Π½Π΅ΡΠ°Π²Π½ΠΎΠΌΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ². Π ΡΠ²ΡΠ·ΠΈ Ρ ΡΡΠΈΠΌ Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΠΌ ΡΡΠ°Π½ΠΎΠ²ΠΈΡΡΡ ΠΈΠ·ΡΡΠ΅Π½ΠΈΠ΅ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΡΠΈΠΉ Π² ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ² Π² ΡΠ°Π·Π²ΠΈΠ²Π°ΡΡΠΈΡ
ΡΡ ΡΡΡΠ°Π½Π°Ρ
, ΡΠ°ΠΊΠΈΡ
ΠΊΠ°ΠΊ ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½. Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ - ΠΎΡΠ΅Π½ΠΊΠ° Π²Π»ΠΈΡΠ½ΠΈΡ Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ², ΡΠΎΡΠΈΠ°Π»ΡΠ½ΡΡ
ΡΠ°ΡΡ
ΠΎΠ΄ΠΎΠ² ΠΈ Π½Π΅ΡΠ°Π²Π΅Π½ΡΡΠ²Π° Π½Π° ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ Π·Π°ΡΡΠ°ΡΡ Π½Π° ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½Π°. Π ΠΎΡΠ»ΠΈΡΠΈΠ΅ ΠΎΡ ΠΏΡΠ΅Π΄ΡΠ΄ΡΡΠΈΡ
Π½Π°ΡΡΠ½ΡΡ
ΡΠ°Π±ΠΎΡ Π² ΡΡΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ, Π² Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΡΡΡΡΡ ΠΏΠ°Π½Π΅Π»ΡΠ½ΡΠ΅ Π΄Π°Π½Π½ΡΠ΅ ΠΎ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ ΡΠ΅Π»ΠΎΠ²Π΅ΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΊΠ°ΠΏΠΈΡΠ°Π»Π° ΠΈ Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ² Π² 17 ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½Π°. ΠΠ»Ρ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Ρ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΠ°ΡΠΈΠΈ, ΠΎΡΡΠ°ΠΆΠ°ΡΡΠΈΠΉ ΡΡΠ΅ΠΏΠ΅Π½Ρ ΡΠΎΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π½Π΅ΡΠ°Π²Π΅Π½ΡΡΠ²Π°. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΡΠ°Π·Π»ΠΈΡΠΈΡ Π² ΡΡΠΎΠ²Π½Π΅ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ. Π‘ΠΎΠ³Π»Π°ΡΠ½ΠΎ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠΌ Π΄Π°Π½Π½ΡΠΌ, Π½Π΅ΡΠ°Π²Π΅Π½ΡΡΠ²ΠΎ ΠΌΠ΅Π½ΡΠ΅ΡΡΡ Ρ ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ΠΌ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ ΠΈ Π²Π»ΠΈΡΠ΅Ρ ΠΊΠ°ΠΊ Π½Π° ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅, ΡΠ°ΠΊ ΠΈ Π½Π° Π·Π°ΡΡΠ°ΡΡ Π½Π° ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΡΡΠ΅ΡΠ°Ρ
. ΠΠ΅ΡΠ°Π²Π΅Π½ΡΡΠ²ΠΎ Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ² Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΎ Π²ΡΡΠ΅ Π² ΠΠ°ΡΠ°Π³Π°Π½Π΄ΠΈΠ½ΡΠΊΠΎΠΉ ΠΈ ΠΠΎΡΡΠΎΡΠ½ΠΎ-ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΡΡ
; Π² Π΄ΡΡΠ³ΠΈΡ
ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
Π΄ΠΎΡ
ΠΎΠ΄Ρ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ Π±ΠΎΠ»Π΅Π΅ ΡΠ°Π²Π½ΠΎΠΌΠ΅ΡΠ½ΠΎ, ΠΏΡΠΈΠΌΠ΅ΡΠ½ΠΎ Π½Π° 0,05 ΠΊΠΎΡΡΡΠΈΡΠΈΠ΅Π½ΡΠ° ΠΠΆΠΈΠ½ΠΈ. Π‘ΠΏΠ΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΈ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°Π΅Ρ, ΡΡΠΎ Π² ΠΊΡΡΠΏΠ½ΡΡ
ΠΌΠ΅Π³Π°ΠΏΠΎΠ»ΠΈΡΠ°Ρ
, ΡΠ°ΠΊΠΈΡ
ΠΊΠ°ΠΊ Π¨ΡΠΌΠΊΠ΅Π½Ρ, ΠΠ»ΠΌΠ°ΡΡ ΠΈ ΠΡΡΠ°Π½Π°, ΠΈΡΡΠ»Π΅Π΄ΡΠ΅ΠΌΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ ΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ Π±ΠΎΠ»ΡΡΠ΅Π΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅, ΡΠΎΠ³Π΄Π° ΠΊΠ°ΠΊ Π² ΠΠ°Π½Π³ΠΈΡΡΠ°ΡΡΠΊΠΎΠΉ ΠΈ Π‘Π΅Π²Π΅ΡΠΎ-ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΡΡ
ΠΈΡ
Π²ΠΎΠ·Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΠΌΠ΅Π½ΡΡΠ΅. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΏΠΎΠ΄ΡΠ΅ΡΠΊΠΈΠ²Π°ΡΡ Π²Π°ΠΆΠ½ΠΎΡΡΡ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ Π΄Π»Ρ ΡΠΎΠΊΡΠ°ΡΠ΅Π½ΠΈΡ ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΡΠΈΠΉ ΠΈ Π΄ΠΎΡΡΠΈΠΆΠ΅Π½ΠΈΡ ΡΠ°Π²Π½ΠΎΠΌΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π΄ΠΎΡ
ΠΎΠ΄ΠΎΠ².In the current social conditions, the problems of inequality associated with the uneven distribution of income in society is an important research problem. Thus, it is necessary to investigate the level of regional differences in income distribution in developing countries like Kazakhstan. The study aims to assess the influence of income, social expenditures, and inequality in the distribution of education and education costs between different regions of Kazakhstan. Unlike previous scientific papers in this area, this paper uses panel data on the distribution of human capital and income in 17 regions of Kazakhstan. The methodological framework of the research is represented by methods of statistical assessment of economic inequality, such as the indicator of differentiation, reflecting the degree of social and economic inequality. Based on the proposed methodology, we analysed the disparity in the level of education and obtained data on the standard deviations of the distribution of education for the population of the regions of Kazakhstan. According to these data, inequality changes over time and affects the distribution of education and education costs between different areas. Income inequality is slightly higher in Karaganda and East-Kazakhstan regions; other areas have a more equitable income distribution by about 0.05 Gini coefficients. The regression specification shows that large megacities like Shymkent, Almaty, and Astana have a more significant influence, while Mangystau and North-Kazakhstan regions have minor power. The obtained results emphasise the importance ensuring access to education for reducing regional disparities and achieving stability in income distribution.Π‘ΡΠ°ΡΡΡ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²Π»Π΅Π½Π° ΠΏΡΠΈ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ΅ ΠΠΎΠΌΠΈΡΠ΅ΡΠ° Π½Π°ΡΠΊΠΈ ΠΠΈΠ½ΠΈΡΡΠ΅ΡΡΡΠ²Π° Π½Π°ΡΠΊΠΈ ΠΈ Π²ΡΡΡΠ΅Π³ΠΎ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°Π½ΠΈΡ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½, ΠΏΡΠΎΠ΅ΠΊΡ AP09259332 Β«Π’ΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΡ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΎΠ·Π½Π°Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΡΡΠ²Π° Π² ΡΡΠ»ΠΎΠ²ΠΈΡΡ
ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ (Π½Π° ΠΏΡΠΈΠΌΠ΅ΡΠ΅ Π Π΅ΡΠΏΡΠ±Π»ΠΈΠΊΠΈ ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½)Β».The article has been prepared with the support of the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan, the project AP09259332 βTransformation of the economic conscious of society in the conditions of the pathology of the economy (on the example of the Republic of Kazakhstan)β
ΠΠ½Π°Π»ΠΈΠ· ΡΠΈΡΡΠΎΠ²ΠΎΠΉ Π³ΠΎΡΠΎΠ²Π½ΠΎΡΡΠΈ ΠΈ ΡΡΠΎΠ²Π½Ρ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ ΠΠ°Π·Π°Ρ ΡΡΠ°Π½Π°
ΠΠ»ΡΡΠ΅Π²ΡΠΌΠΈ Π°ΡΠΏΠ΅ΠΊΡΠ°ΠΌΠΈ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡΠΈΠΊΠΈ ΡΠ²Π»ΡΡΡΡΡ ΡΠΈΡΡΠΎΠ²Π°Ρ Π³ΠΎΡΠΎΠ²Π½ΠΎΡΡΡ ΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΠΌΠ΅ΡΠΎΠ΄Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΡΡΠΎΠ²Π½Ρ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ Π³ΠΎΡΠΎΠ²Π½ΠΎΡΡΠΈ ΠΈ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΠΈΡΡΠΎΠ²ΡΡ
ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΠΉ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ Π΄Π»Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΡΡΡΠ°ΡΠ΅Π³ΠΈΠΉ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΠΈΠΈ Π½Π° Π²ΡΠ΅Ρ
ΡΡΠΎΠ²Π½ΡΡ
ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ Π±ΠΈΠ·Π½Π΅ΡΠΎΠΌ. Π’Π΅ΠΎΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΎΡΠ½ΠΎΠ²Ρ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΈΠ½Π½ΠΎΠ²Π°ΡΠΈΠΉ ΠΈ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ Π±ΡΠ»ΠΈ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ Ρ ΡΡΠ΅ΡΠΎΠΌ Π²Π»ΠΈΡΠ½ΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΈΠΌΠ΅Π½ΡΠ»ΠΈΡΡ ΠΈΠ½Π΄Π΅ΠΊΡΠ½ΡΠΉ ΠΈ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΎΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΌΠ΅ΡΠΎΠ΄Ρ, ΠΎΠΏΠΈΡΠ°ΡΡΠΈΠ΅ΡΡ Π½Π° ΡΠΈΡΡΠ΅ΠΌΠ½ΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄. Π Π°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½Π°Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° Π±ΡΠ»Π° Π°Π΄Π°ΠΏΡΠΈΡΠΎΠ²Π°Π½Π° Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΡΡΠΎΠ²Π½Π΅ΠΉ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
. ΠΠ»Ρ Π°Π½Π°Π»ΠΈΠ·Π° ΡΠΈΡΡΠΎΠ²ΠΎΠΉ Π³ΠΎΡΠΎΠ²Π½ΠΎΡΡΠΈ ΠΈ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ Π½Π° ΡΠ΅Π³ΠΈΠΎΠ½Π°Π»ΡΠ½ΠΎΠΌ ΡΡΠΎΠ²Π½Π΅ Π±ΡΠ»ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»ΠΈ: ΠΈΠ½Π΄Π΅ΠΊΡ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, ΠΈΠ½Π΄Π΅ΠΊΡ Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΡΡΠ³ΠΌΠ°Π½Π° ΠΈ ΠΈΠ½Π΄Π΅ΠΊΡ Π₯Π΅ΡΡΠΈΠ½Π΄Π°Π»Ρ - Π₯ΠΈΡΡΠΌΠ°Π½Π°. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΡΠΉ Π² ΡΡΠ°ΡΡΠ΅ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΡΠΎΡΡΠΎΠΈΡ ΠΈΠ· ΡΠ»Π΅Π΄ΡΡΡΠΈΡ
ΡΡΠ°ΠΏΠΎΠ²: ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΠΎΠ²Π½Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΠΈΠ½ΡΠ΅ΡΠ½Π΅ΡΠ°, Π°Π½Π°Π»ΠΈΠ· Π·Π°ΡΡΠ°Ρ Π½Π° ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²ΠΎ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΠΎΠ²Π½Ρ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ Π³ΡΠ°ΠΌΠΎΡΠ½ΠΎΡΡΠΈ Π½Π°ΡΠ΅Π»Π΅Π½ΠΈΡ, ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΠΎΡΡΠ°ΡΠ»Π΅Π²ΠΎΠΉ ΡΠΏΠ΅ΡΠΈΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π² ΡΡΠ΅ΡΠ΅ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. ΠΡΡΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠ°Π·Π½ΡΠΉ ΡΡΠΎΠ²Π΅Π½Ρ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΠΈ ΠΊΠΎΠΌΠΌΡΠ½ΠΈΠΊΠ°ΡΠΈΠΎΠ½Π½ΡΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ Π² ΡΠ΅Π³ΠΈΠΎΠ½Π°Ρ
ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½Π° Π²Π»ΠΈΡΠ΅Ρ Π½Π° ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Ρ ΡΠΈΡΡΠΎΠ²ΠΈΠ·Π°ΡΠΈΠΈ ΠΈΡ
ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ. ΠΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Ρ Π°Π³Π»ΠΎΠΌΠ΅ΡΠ°ΡΠΈΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ ΡΡΠ°ΡΡ ΠΏΠΎΠ»ΡΡΠ°ΠΌΠΈ ΡΠΎΡΡΠ° ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠΈ Π·Π½Π°Π½ΠΈΠΉ Π² ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½Π΅ - Π³. ΠΠ»ΠΌΠ°ΡΡ, Π³. ΠΡΡΡΡΠ»ΡΠ°Π½, ΠΠ°ΡΠ°Π³Π°Π½Π΄ΠΈΠ½ΡΠΊΠ°Ρ ΠΈ ΠΠΊΡΡΠ±ΠΈΠ½ΡΠΊΠ°Ρ ΠΎΠ±Π»Π°ΡΡΠΈ. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΌΠΎΠ³ΡΡ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½Ρ Π³ΠΎΡΡΠ΄Π°ΡΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ ΠΎΡΠ³Π°Π½Π°ΠΌΠΈ ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½Π° Π΄Π»Ρ ΡΠΈΡΡΠΎΠ²ΠΎΠΉ ΠΌΠΎΠ΄Π΅ΡΠ½ΠΈΠ·Π°ΡΠΈΠΈ ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² ΡΡΡΠ°Π½Ρ.The level of digital readiness and the application of information and communication technologies (ICT) are key factors of any innovation policy. This research has highlighted the development of analysis of the degree of digital readiness and assessment methods of digital transformations, which can be used at various levels of business management to formulate digital transformation strategies. The present study investigates the theoretical framework in the field of innovation and spatial development considering the impact of the level of ICT. The research was conducted using index and economic-statistical methods based on a systematic approach. We developed a methodological tool adapted to the regional management level. The ICT development index, Krugman localisation index and Herfindahl-Hirschman index were modified to analyse digital readiness and ICT development at the regional level. The algorithm includes the following steps: assessment of the internet usage level; analysis of the degree of costs for the production of ICT; evaluation of the digital literacy rate of the population; evaluation of the degree of regional industry specialisation in the field of ICT. It was revealed that Kazakhstan's regions have varying levels of ICT development, which is why they have different prerequisites and prospects for digitalising their economy. The agglomerations that could become βgrowth polesβ of Kazakhstan's knowledge-based economy were identified, such as Almaty city, Nur-Sultan city, Karaganda, and Aktobe regions. Government bodies can use the research findings for Kazakhstani territories' digital modernisation.Π‘ΡΠ°ΡΡΡ ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²Π»Π΅Π½Π° Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π½Π°ΡΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ, ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠ³ΠΎ Π² ΡΠ°ΠΌΠΊΠ°Ρ
Π³ΡΠ°Π½ΡΠΎΠ²ΠΎΠ³ΠΎ ΠΏΡΠΎΠ΅ΠΊΡΠ° ΠΠ Π BR05236639 Β«ΠΠ°Π·Π°Ρ
ΡΡΠ°Π½ΡΠΊΠΈΠΉ ΠΏΡΡΡ ΠΊ Π½Π°ΡΠΊΠΎΠ΅ΠΌΠΊΠΎΠΉ ΡΠΊΠΎΠ½ΠΎΠΌΠΈΠΊΠ΅ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΠ΅ΡΡΠ΅ΠΉ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅ΡΠ½ΠΈΠ·Π°ΡΠΈΠΈ: ΡΡΡΠ°ΡΠ΅Π³ΠΈΡ, ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΡ ΡΠ°Π·Π²ΠΈΡΠΈΡΒ».The article has been prepared based on the conducted scientific research, the grant-funding project IRN BR05236639 βKazakhstanβs path to a knowledge-based economy based on the third technological modernization: strategy, models and mechanisms of developmentβ