Analysis of the human security in Ukraine in a regional perspective

Nazarova, Galyna; Demianenko, Alina

doi:10.21511/slrtp.8(2).2018.01

Cited by 2 publications

(1 citation statement)

References 1 publication

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“…The dynamics of the quantitative distribution of Ukrainian regions by the selected clusters were also analyzed. The study identified cores with a constant composition of regions and presented characteristics of each cluster [ 28 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Discovering smart cities’ potential in Kazakhstan: A cluster analysis

Urdabayev,

Kireyeva,

Vasa

et al. 2024

PLoS ONE

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The potential for developing smart cities in Kazakhstan is evaluated using cluster analysis. Built on previous research focused on clustering the regions of Kazakhstan, this study applies the same method to the cities of the country. The analysis uses indicators related to human capital, infrastructure, education, information technology, production, and other factors to assess the potential of each city. The clustering is performed using Single Linkage, Complete Linkage, and Ward’s methods. The results show that Almaty and Astana are the cities with the highest potential for becoming smart cities. Aktobe is identified as a city with distinctive features that may help or hinder its development as a smart city. The remaining cities are clustered into two groups, with one group having the potential to catch up and maintain the trend of developing smart cities, while the other group is less suitable for starting smart city projects and may require more investment per capita. The study highlights the deep regional inequality affecting the potential to successfully develop and manage smart cities in Kazakhstan. The analysis also reveals some limitations and challenges in the data and variables used, including the lack of data for some variables and the difficulties in "translating" some factors and indicators into quantitative variables for clustering. The study concludes that future research should address these challenges and consider clustering inside certain regions to focus on their unique features. The study recommends launching pilot projects in small cities, with the most successful practices then scaled and implemented in the core smart cities and possibly Aktobe, if it manages to use its advantages to compensate for risks. Overall, this study provides insights into the potential of smart city development in Kazakhstan and can inform policymakers in their efforts to support smart city projects in the country.

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Section: Literature Reviewmentioning

confidence: 99%

Discovering smart cities’ potential in Kazakhstan: A cluster analysis

Urdabayev,

Kireyeva,

Vasa

et al. 2024

PLoS ONE

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Evaluating development prospects of smart cities: Cluster analysis of Kazakhstan’s regions

Digel

Mussabalina

Urdabayev

et al. 2022

Problems and Perspectives in Management

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This study aims to study Kazakhstan’s regions and identify places with the best potential for developing smart cities based on cluster analysis. To analyze the differentiation by the level of development, 17 regions of Kazakhstan are grouped according to 2020 data from the statistical bulletin of the National Bureau of Statistics of the Republic of Kazakhstan. The formation of groups of regions with different values of indicators was carried out based on agglomerative clustering using the single linkage, complete linkage, and Ward’s clustering methods. In agglomerative clustering, the algorithm groups regions based on observations into clusters, and indicators determine each area’s innovative development level. The instrument to build clustering is the “RStudio” software package. As a result, regions with their essential characteristics were identified, and an assessment of their prospects was obtained with the most significant potential for developing and managing “smart cities” – Atyrau region, Almaty city, and Astana city. The remaining clusters include regions where favorable conditions for the development of innovations have not yet been formed, which require more resources and efforts to build “smart cities.” Therefore, they should not be the first to implement this concept. They need a more balanced, integrated approach, ideally supported by experience in implementing the idea in more promising regions. In a sense, clustering also allowed for identifying potential (or even existing) innovation clusters in regions of Kazakhstan. The study results can be used in developing government programs to form smart cities and further study the potential of smart cities.

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Analysis of the human security in Ukraine in a regional perspective

Cited by 2 publications

References 1 publication

Discovering smart cities’ potential in Kazakhstan: A cluster analysis

Discovering smart cities’ potential in Kazakhstan: A cluster analysis

Evaluating development prospects of smart cities: Cluster analysis of Kazakhstan’s regions

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