45 research outputs found

    Application of waste wood for receiving building materials

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    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

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    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

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    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

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    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

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    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 Kazakhstan’s Regions

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    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 β€œgrowth poles” 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

    Analysis of the Digital Readiness and the Level of the ICT Development in Kazakhstan’s Regions

    Get PDF
    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 β€œgrowth poles” 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

    ΠžΡ†Π΅Π½ΠΊΠ° нСравСнства распрСдСлСния Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² ΠΈ образования Π² Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ… ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π°

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    Π’Π°ΠΆΠ½ΠΎΠΉ ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎΠΉ ΠΏΡ€ΠΎΠ±Π»Π΅ΠΌΠΎΠΉ являСтся вопрос Π½Π΅Ρ€Π°Π²Π½ΠΎΠΌΠ΅Ρ€Π½ΠΎΠ³ΠΎ распрСдСлСния Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ². Π’ связи с этим Π°ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½Ρ‹ΠΌ становится ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΠ΅ Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… Ρ€Π°Π·Π»ΠΈΡ‡ΠΈΠΉ Π² распрСдСлСнии Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² Π² Ρ€Π°Π·Π²ΠΈΠ²Π°ΡŽΡ‰ΠΈΡ…ΡΡ странах, Ρ‚Π°ΠΊΠΈΡ… ΠΊΠ°ΠΊ ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½. ЦСль исслСдования - ΠΎΡ†Π΅Π½ΠΊΠ° влияния Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ², ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½Ρ‹Ρ… расходов ΠΈ нСравСнства Π½Π° ΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΈ Π·Π°Ρ‚Ρ€Π°Ρ‚Ρ‹ Π½Π° ΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ Π² Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ… ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π°. Π’ ΠΎΡ‚Π»ΠΈΡ‡ΠΈΠ΅ ΠΎΡ‚ ΠΏΡ€Π΅Π΄Ρ‹Π΄ΡƒΡ‰ΠΈΡ… Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… Ρ€Π°Π±ΠΎΡ‚ Π² этой области, Π² Π΄Π°Π½Π½ΠΎΠΉ ΡΡ‚Π°Ρ‚ΡŒΠ΅ Π°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΡƒΡŽΡ‚ΡΡ ΠΏΠ°Π½Π΅Π»ΡŒΠ½Ρ‹Π΅ Π΄Π°Π½Π½Ρ‹Π΅ ΠΎ распрСдСлСнии чСловСчСского ΠΊΠ°ΠΏΠΈΡ‚Π°Π»Π° ΠΈ Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² Π² 17 Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ… ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π°. Для статистичСской ΠΎΡ†Π΅Π½ΠΊΠΈ использован ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΡŒ Π΄ΠΈΡ„Ρ„Π΅Ρ€Π΅Π½Ρ†ΠΈΠ°Ρ†ΠΈΠΈ, ΠΎΡ‚Ρ€Π°ΠΆΠ°ΡŽΡ‰ΠΈΠΉ ΡΡ‚Π΅ΠΏΠ΅Π½ΡŒ ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎΠ³ΠΎ ΠΈ экономичСского нСравСнства. На основС ΠΏΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠΈ ΠΏΡ€ΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡ€ΠΎΠ²Π°Π½Ρ‹ различия Π² ΡƒΡ€ΠΎΠ²Π½Π΅ образования. Богласно ΠΏΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹ΠΌ Π΄Π°Π½Π½Ρ‹ΠΌ, нСравСнство мСняСтся с Ρ‚Π΅Ρ‡Π΅Π½ΠΈΠ΅ΠΌ Π²Ρ€Π΅ΠΌΠ΅Π½ΠΈ ΠΈ влияСт ΠΊΠ°ΠΊ Π½Π° ΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠ΅, Ρ‚Π°ΠΊ ΠΈ Π½Π° Π·Π°Ρ‚Ρ€Π°Ρ‚Ρ‹ Π½Π° ΠΎΠ±Ρ€Π°Π·ΠΎΠ²Π°Π½ΠΈΠ΅ Π² Ρ€Π°Π·Π»ΠΈΡ‡Π½Ρ‹Ρ… сфСрах. НСравСнство Π΄ΠΎΡ…ΠΎΠ΄ΠΎΠ² нСсколько Π²Ρ‹ΡˆΠ΅ Π² ΠšΠ°Ρ€Π°Π³Π°Π½Π΄ΠΈΠ½ΡΠΊΠΎΠΉ ΠΈ Восточно-ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½ΡΠΊΠΎΠΉ областях; Π² Π΄Ρ€ΡƒΠ³ΠΈΡ… Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ… Π΄ΠΎΡ…ΠΎΠ΄Ρ‹ распрСдСлСны Π±ΠΎΠ»Π΅Π΅ Ρ€Π°Π²Π½ΠΎΠΌΠ΅Ρ€Π½ΠΎ, ΠΏΡ€ΠΈΠΌΠ΅Ρ€Π½ΠΎ Π½Π° 0,05 коэффициСнта Π”ΠΆΠΈΠ½ΠΈ. БпСцификация рСгрСссии ΠΏΠΎΠΊΠ°Π·Ρ‹Π²Π°Π΅Ρ‚, Ρ‡Ρ‚ΠΎ Π² ΠΊΡ€ΡƒΠΏΠ½Ρ‹Ρ… мСгаполисах, Ρ‚Π°ΠΊΠΈΡ… ΠΊΠ°ΠΊ Π¨Ρ‹ΠΌΠΊΠ΅Π½Ρ‚, Алматы ΠΈ Астана, исслСдуСмыС ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ ΠΎΠΊΠ°Π·Ρ‹Π²Π°ΡŽΡ‚ большСС влияниС, Ρ‚ΠΎΠ³Π΄Π° ΠΊΠ°ΠΊ Π² ΠœΠ°Π½Π³ΠΈΡΡ‚Π°ΡƒΡΠΊΠΎΠΉ ΠΈ Π‘Π΅Π²Π΅Ρ€ΠΎ-ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½ΡΠΊΠΎΠΉ областях ΠΈΡ… воздСйствиС мСньшС. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ ΠΏΠΎΠ΄Ρ‡Π΅Ρ€ΠΊΠΈΠ²Π°ΡŽΡ‚ Π²Π°ΠΆΠ½ΠΎΡΡ‚ΡŒ образования для сокращСния Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… Ρ€Π°Π·Π»ΠΈΡ‡ΠΈΠΉ ΠΈ достиТСния Ρ€Π°Π²Π½ΠΎΠΌΠ΅Ρ€Π½ΠΎΠ³ΠΎ распрСдСлСния 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‘Ρ‚Π°Ρ‚ΡŒΡ ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²Π»Π΅Π½Π° ΠΏΡ€ΠΈ ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΠ΅ ΠšΠΎΠΌΠΈΡ‚Π΅Ρ‚Π° Π½Π°ΡƒΠΊΠΈ ΠœΠΈΠ½ΠΈΡΡ‚Π΅Ρ€ΡΡ‚Π²Π° Π½Π°ΡƒΠΊΠΈ ΠΈ Π²Ρ‹ΡΡˆΠ΅Π³ΠΎ образования РСспублики ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½, ΠΏΡ€ΠΎΠ΅ΠΊΡ‚ AP09259332 «Врансформация экономичСского сознания общСства Π² условиях ΠΏΠ°Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ экономики (Π½Π° ΠΏΡ€ΠΈΠΌΠ΅Ρ€Π΅ РСспублики ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°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 β€œTransformation of the economic conscious of society in the conditions of the pathology of the economy (on the example of the Republic of Kazakhstan)”

    Анализ Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΠΉ готовности ΠΈ уровня развития ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ Π² Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ… ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π°

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    ΠšΠ»ΡŽΡ‡Π΅Π²Ρ‹ΠΌΠΈ аспСктами ΠΈΠ½Π½ΠΎΠ²Π°Ρ†ΠΈΠΎΠ½Π½ΠΎΠΉ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ ΡΠ²Π»ΡΡŽΡ‚ΡΡ цифровая Π³ΠΎΡ‚ΠΎΠ²Π½ΠΎΡΡ‚ΡŒ ΠΈ ΠΏΡ€ΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. Π’ ΡΡ‚Π°Ρ‚ΡŒΠ΅ прСдставлСны ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹ Π°Π½Π°Π»ΠΈΠ·Π° уровня Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΠΉ готовности ΠΈ ΠΎΡ†Π΅Π½ΠΊΠΈ Ρ†ΠΈΡ„Ρ€ΠΎΠ²Ρ‹Ρ… трансформаций, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ для Ρ€Π°Π·Ρ€Π°Π±ΠΎΡ‚ΠΊΠΈ стратСгий Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΠΉ трансформации Π½Π° всСх уровнях управлСния бизнСсом. ВСорСтичСскиС основы Π² области ΠΈΠ½Π½ΠΎΠ²Π°Ρ†ΠΈΠΉ ΠΈ пространствСнного развития Π±Ρ‹Π»ΠΈ рассмотрСны с ΡƒΡ‡Π΅Ρ‚ΠΎΠΌ влияния ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. Π’ исслСдовании ΠΏΡ€ΠΈΠΌΠ΅Π½ΡΠ»ΠΈΡΡŒ индСксный ΠΈ экономикостатистичСский ΠΌΠ΅Ρ‚ΠΎΠ΄Ρ‹, ΠΎΠΏΠΈΡ€Π°ΡŽΡ‰ΠΈΠ΅ΡΡ Π½Π° систСмный ΠΏΠΎΠ΄Ρ…ΠΎΠ΄. Разработанная ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΈΠΊΠ° Π±Ρ‹Π»Π° Π°Π΄Π°ΠΏΡ‚ΠΈΡ€ΠΎΠ²Π°Π½Π° для ΠΎΡ†Π΅Π½ΠΊΠΈ ΡƒΡ€ΠΎΠ²Π½Π΅ΠΉ управлСния Π² Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ…. Для Π°Π½Π°Π»ΠΈΠ·Π° Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΠΉ готовности ΠΈ развития ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ Π½Π° Ρ€Π΅Π³ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠΌ ΡƒΡ€ΠΎΠ²Π½Π΅ Π±Ρ‹Π»ΠΈ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ ΠΌΠΎΠ΄ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹Π΅ ΠΏΠΎΠΊΠ°Π·Π°Ρ‚Π΅Π»ΠΈ: индСкс развития ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, индСкс Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°Ρ†ΠΈΠΈ ΠšΡ€ΡƒΠ³ΠΌΠ°Π½Π° ΠΈ индСкс Π₯Срфиндаля - Π₯ΠΈΡ€ΡˆΠΌΠ°Π½Π°. ΠŸΡ€Π΅Π΄Π»ΠΎΠΆΠ΅Π½Π½Ρ‹ΠΉ Π² ΡΡ‚Π°Ρ‚ΡŒΠ΅ Π°Π»Π³ΠΎΡ€ΠΈΡ‚ΠΌ состоит ΠΈΠ· ΡΠ»Π΅Π΄ΡƒΡŽΡ‰ΠΈΡ… этапов: ΠΎΡ†Π΅Π½ΠΊΠ° уровня использования ΠΈΠ½Ρ‚Π΅Ρ€Π½Π΅Ρ‚Π°, Π°Π½Π°Π»ΠΈΠ· Π·Π°Ρ‚Ρ€Π°Ρ‚ Π½Π° производство ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ, ΠΎΡ†Π΅Π½ΠΊΠ° уровня Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΠΉ грамотности насСлСния, ΠΎΡ†Π΅Π½ΠΊΠ° стСпСни отраслСвой спСциализации Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ² Π² сфСрС ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ. ВыявлСно, Ρ‡Ρ‚ΠΎ Ρ€Π°Π·Π½Ρ‹ΠΉ ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ развития ΠΈΠ½Ρ„ΠΎΡ€ΠΌΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… ΠΈ ΠΊΠΎΠΌΠΌΡƒΠ½ΠΈΠΊΠ°Ρ†ΠΈΠΎΠ½Π½Ρ‹Ρ… Ρ‚Π΅Ρ…Π½ΠΎΠ»ΠΎΠ³ΠΈΠΉ Π² Ρ€Π΅Π³ΠΈΠΎΠ½Π°Ρ… ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π° влияСт Π½Π° пСрспСктивы Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΈΠ·Π°Ρ†ΠΈΠΈ ΠΈΡ… экономики. ΠžΠΏΡ€Π΅Π΄Π΅Π»Π΅Π½Ρ‹ Π°Π³Π»ΠΎΠΌΠ΅Ρ€Π°Ρ†ΠΈΠΈ, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΌΠΎΠ³ΡƒΡ‚ ΡΡ‚Π°Ρ‚ΡŒ полюсами роста экономики Π·Π½Π°Π½ΠΈΠΉ Π² ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π΅ - Π³. Алматы, Π³. Нурсултан, ΠšΠ°Ρ€Π°Π³Π°Π½Π΄ΠΈΠ½ΡΠΊΠ°Ρ ΠΈ ΠΠΊΡ‚ΡŽΠ±ΠΈΠ½ΡΠΊΠ°Ρ области. ΠŸΠΎΠ»ΡƒΡ‡Π΅Π½Π½Ρ‹Π΅ Ρ€Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹ исслСдования ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΠΎΠ²Π°Π½Ρ‹ государствСнными ΠΎΡ€Π³Π°Π½Π°ΠΌΠΈ ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½Π° для Ρ†ΠΈΡ„Ρ€ΠΎΠ²ΠΎΠΉ ΠΌΠΎΠ΄Π΅Ρ€Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ Ρ€Π΅Π³ΠΈΠΎΠ½ΠΎΠ² страны.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 β€œgrowth poles” 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‘Ρ‚Π°Ρ‚ΡŒΡ ΠΏΠΎΠ΄Π³ΠΎΡ‚ΠΎΠ²Π»Π΅Π½Π° Π½Π° основС Π½Π°ΡƒΡ‡Π½ΠΎΠ³ΠΎ исслСдования, ΠΏΡ€ΠΎΠ²Π΅Π΄Π΅Π½Π½ΠΎΠ³ΠΎ Π² Ρ€Π°ΠΌΠΊΠ°Ρ… Π³Ρ€Π°Π½Ρ‚ΠΎΠ²ΠΎΠ³ΠΎ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚Π° ИРН BR05236639 Β«ΠšΠ°Π·Π°Ρ…ΡΡ‚Π°Π½ΡΠΊΠΈΠΉ ΠΏΡƒΡ‚ΡŒ ΠΊ Π½Π°ΡƒΠΊΠΎΠ΅ΠΌΠΊΠΎΠΉ экономикС Π½Π° основС Ρ‚Ρ€Π΅Ρ‚ΡŒΠ΅ΠΉ тСхнологичСской ΠΌΠΎΠ΄Π΅Ρ€Π½ΠΈΠ·Π°Ρ†ΠΈΠΈ: стратСгия, ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈ ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌΡ‹ развития».The article has been prepared based on the conducted scientific research, the grant-funding project IRN BR05236639 β€œKazakhstan’s path to a knowledge-based economy based on the third technological modernization: strategy, models and mechanisms of development”
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