Перегляд за Автор "Grygoruk, Svitlana"

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    A Novel Method for Determining Weighting Coefficients in the Block Convolution Model of the Managerial Decisions Effectiveness Comprehensive Assessment
    (2023) Hryhoruk, Pavlo; Khrushch, Nila; Grygoruk, Svitlana
    The development of effective managerial decisions is the most crucial stage in management activities, a necessary condition for ensuring the competitiveness of a business entity. The complexity and high dynamism of the market environment make it essential to consider a large number of partial criteria when choosing the most effective alternative. The analysis of modern studies showed that despite many different approaches to evaluating alternatives, they are mainly based on aggregating initial criteria. Such a procedure can be carried out by applying the technology of comprehensive index assessment. A large number of partial criteria complicates the procedure for constructing a comprehensive index, makes it cumbersome, reduces its informativeness and discriminating ability, and negatively affects the significance of the weighting coefficients. To eliminate these shortcomings, the article considers the procedure of block convolution, in which the initial criteria are first divided into groups according to specific rules. A partial comprehensive index is constructed for each group. At the next stage, they are integrated into a comprehensive index of the effectiveness of alternatives by weighted convolution. For the case of two partial comprehensive indexes, a method of dynamic weighting coefficients has been developed to evaluate each component's importance in their convolution. Its feature is the consideration of a more significant partial comprehensive indicator obtained at the first stage of convolution, which allows for reducing the compensatory influence of another one. For the interpretation of alternatives' evaluation results and the selection of the most suitable as a managerial decision, it is proposed to use the Harrington scale. The paper contains a graphic interpretation of the proposed approach and its practical approbation, which confirms its effectiveness
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    Application of Multidimensional Statistical Analysis Technology for Grouping Regions by the Investment Attractiveness Level
    (SCITEPRESS – Science and Technology Publications, Lda , Setúbal, Portugal, 2023) Hryhoruk, Pavlo; Khrushch, Nila; Grygoruk, Svitlana; Ovchynnikova, Olena
    The paper is devoted to studying multidimensional statistical analysis tools for grouping regions by the level of their investment attractiveness and identifying changes in the structure of regions in the context of the continued destructive impact of the COVID-19 pandemic. An analysis of approaches to assessing investment attractiveness identified their strengths. Insufficient attention to the application of methods of multidimensional statistical analysis to a grouping of regions is stated. The authors consider the clustering of regions of Ukraine in the context of their level of investment attractiveness by the method of k-means and identify their structure according to the level of investment attractiveness in 2019 and 2020 in the context of the COVID-19 pandemic. To verify the correctness of the conclusions, the method of principal components with the rotation of the space of the selected factors by the quartimax technique. Further grouping of regions in the space of selected principal components showed results identical to the application of the cluster analysis method. Potential investors can use the research results to determine priority areas of investment. Also, the results are useful for local self-government bodies, as they provide information on the relative level of investment attractiveness of a specific region compared to other territorial units and also allow identifying weak points in specific areas of activity
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    Assessing the Impact of COVID-19 Pandemic on the Regions’ Socio-Economic Development: The Case of Ukraine
    (2021) Григорук, Павло Михайлович; Хрущ, Ніла Анатоліївна; Григорук, Світлана Сергіївна; Приступа, Л.А.; Горбатюк, К.В.; Hryhoruk, Pavlo; Khrushch, Nila; Grygoruk, Svitlana; Prystupa, Liudmyla; Gorbatiuk, Kateryna
    Solving the problems of regional development belongs to the category of strategic and most important of each country. The COVID-19 pandemic has become the biggest challenge for the world economic system, causing a significant impact on the reduction of key macroeconomic indicators, changes in business conditions, which has raised the issue of assessing the social and economic development of regions. The paper considers the application of composite index assessment technology for the consequences of COVID-19 on the development indicators of Ukraine's regions. The comparison was conducted according to the data of the first two quarters of 2019 and 2020. For the study, eight indicators were selected, which by content feature were divided into a subset of economic indicators and a subset of social indicators. A partial composite development index was designed for each subset. The principal components method was used to calculate the weights of the components. The results of the analysis showed that the COVID-19 pandemic had a greater impact on economic development: for each region, there is a decrease in the value of the indicator. While for a partial composite index of social development such a decrease is less noticeable. The reflection of the regions in the space of these composite indices showed that their structure remained virtually unchanged. The analysis of the common composite index of regional development, designed by the convolution of partial composite indices indicators, also showed a decrease in its values in 2020. The paper analyses the measures taken by the Government of Ukraine to neutralize the effects of the pandemic
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    Assessment of regions' socio-economic development based on non-metric data
    (2021) Григорук, П.М.; Григорук, Павло Михайлович; Hryhoruk, Pavlo; Khrushch, Nila; Хрущ, Н.А.; Хрущ, Ніла Анатоліївна; Григорук, С.С.; Григорук, Світлана Сергіївна; Grygoruk, Svitlana; Hryhoruk, P.; Khrushch, N.; Grygoruk, S.
    Assessment of socio-economic development of both separate territories and countries as a whole, comparison of the received estimations to identify the development disproportions, lacks, and gaps, application of the best practices to decide the revealed problems promotes the development of balanced state regional development policy. Quite common tasks of such assessment are the ranking of regions and their grouping according to some generalized socio-economic development characteristics. The solution to these problems is complicated by the use of a set of indicators of non-numerical nature because traditional statistical methods are unsuitable for their processing. The paper considers the solution to the problem of constructing a consensus rank based on Kemeny's median. To solve the problem of grouping regions, an approach is proposed based on the picture of regions in the space of partial consensus rankings for economic and social development separately, with the subsequent detection of object stratification in this space. The practical implementation of the proposed approach according to partial rankings is given. A heuristic algorithm was used to construct Kemeny's median. The obtained grouping of the regions of Ukraine reproduced as a whole their order following the resulting consensus ranking. Comparison of the obtained results with the known results of solving such tasks, calculated on the set of metric indicators also showed their consistency.
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    Canonical Correlation Analysis in Information Systems for Assessing Economic Growth and Environmental Security Relationships
    (CEUR-WS, 2025) Hryhoruk, Pavlo; Khrushch, Nila; Grygoruk, Svitlana; Ramskyi, Andrii; Григорук, Павло; Григорук, Світлана; Хрущ, Ніла; Рамський, Андрій
    The study presents a comprehensive exploration of canonical correlation analysis applied within advanced information systems for assessing complex interrelations between economic growth indicators and environmental security factors. Leveraging robust computational methodologies and integrated information systems, this research utilizes canonical correlation analysis to quantitatively evaluate relationships between two sets of multidimensional variables: indicators representing economic well being—including GDP per capita, gross fixed capital formation, value-added industrial production, and household expenditures—and variables reflecting environmental threats such as carbon dioxide and greenhouse gas emissions, and natural resource depletion. Data sourced from the World Bank for 136 countries for the year 2020 served as the empirical foundation of the study. The employed computational information system facilitated advanced preprocessing and normalization procedures, essential for ensuring analytical accuracy given substantial variability across datasets. Statistical computations were executed within a structured digital environment, leveraging computational efficiency to identify canonical variables demonstrating maximal correlation. Results indicated a significant canonical correlation coefficient (r = 0.9762), underscoring the robustness of the identified relationships. Further analytical interpretation using Pearson’s pairwise correlation confirmed the validity and significance of these variables within constructed canonical sets. The presented findings reaffirm previous scholarly insights into economic-environmental interdependencies and reinforce the pivotal role of computational analysis supported by sophisticated information systems in elucidating complex socio-economic phenomena. This methodological approach proves indispensable for strategic policy formulation aimed at balancing economic advancement and environmental sustainability, contributing to the broader discourse on achieving sustainable development goals through innovative computational and analytical techniques
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    Managerial decision-making using fuzzy preference relations
    (UTP University of Science and Technology, Bydgoszcz, Poland, 2019) Hryhoruk, P.; Khrushch, N.; Grygoruk, S.; Григорук, П.М.; Хрущ, Н.А.; Григорук, С.С.; Hryhoruk, Pavlo; Khrushch, Nila; Grygoruk, Svitlana
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    Model for Self-assessment of the Internal Quality Assurance System in Context of European Standards and Guidelines Requirements
    (Atlantis Press, Paris, 2019) Григорук, П.М.; Григорук, Павло Михайлович; Hryhoruk, Pavlo; Grygoruk, S.; Григорук, Світлана Сергіївна; Григорук, С.С.; Grygoruk, Svitlana; Hryhoruk, P.; Mazurkiewicz, M.
    The paper deals with the problems of assessing the compliance level of internal quality assurance system with the requirements of European standards and guidelines. The basis of the calculations is the self-assessment procedure based on the composite index evaluation technology. An approach to design a system of initial indicators for calculating the composite index and the procedure for their scaling are proposed. The algorithm for calculating the values of the composite index, which is oriented toward the use of weighted additive convolution, is described. At the same time, it takes into account the nature of the output indicators. The rules for establishing the correspondence between the quantitative and qualitative values of the level of internal quality assurance system are given. Evaluation can be carried out both at the institutional level and at the level of individual academic programme. The article contains examples of indicators and initial indexes that can be used in the assessing procedures for identification the level of internal quality assurance. An example of calculations for the proposed approach is presented. The results of the assessment can be used to identify weak positions in internal quality assurance system, track the dynamics of quality assurance level as a whole, and for its individual components.
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    Modeling structural changes in the regional economic development of Ukraine during the COVID-19 pandemic
    (2021) Григорук, П.М.; Григорук, Павло Михайлович; Hryhoruk, Pavlo; Hryhoruk, P.; Хрущ, Н.А.; Хрущ, Ніла Анатоліївна; Khrushch, N.; Khrushch, Nila; Grygoruk, Svitlana; Grygoruk, S.; Григорук, С.С.; Григорук, Світлана Сергіївна
    The paper investigates the issues of evaluating structural changes in the regions’ economic development based on the comprehensive index assessment technology. The impact of the COVID-19 pandemic on regional development and changes in the regional structure is considered. The authors propose the use of block convolution to design a comprehensive index based on a set of metric initial indicators that characterize the regions’ economic development. Grouping the set of initial indicators is carried out based on the method of an extreme grouping of parameters and the method of principal components. A weighted linear additive convolution was used to develop partial composite indices and an economic development comprehensive index. The practical approbation was carried out for the regions of Ukraine according to the data of 9 months of 2019 and the same period of 2020. To establish the regions’ structure, we used the division of the comprehensive index values into intervals and further distributing regions into classes according to the level of economic development. There is a general decrease in the value of the integrated indicator in 2020, caused by the impact of the COVID-19 pandemic. However, no significant changes in the structure of the regions were detected, which indicates an equally negative impact of the pandemic for all regions of Ukraine
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    Multidimensional statistical analysis of investment attractiveness and regional changes in the COVID-19 pandemic
    (2023) Hryhoruk, Pavlo; Khrushch, Nila; Grygoruk, Svitlana; Ovchynnikova, Olena
    This paper delves into an in-depth exploration of multidimensional statistical analysis techniques aimed at categorizing regions based on their levels of investment attractiveness, while also scrutinizing the evolving regional structures in light of the persistent and adverse effects of the COVID-19 pandemic. Through a comprehensive review of various approaches to assessing investment attractiveness, the study highlights their respective strengths. Notably, the research underscores the underutilization of multidimensional statistical analysis methodologies in the regional grouping context. The authors undertake the task of clustering Ukrainian regions based on their investment attractiveness levels, employing the well-regarded 𝑘-means method. This analysis extends to the identification of the regions’ investment attractiveness structure in both 2019 and 2020, amid the COVID-19 pandemic. Substantiating the validity of their findings, the authors employ the principal component method in conjunction with the quartimax technique to rotate the space of selected factors. Remarkably, the subsequent regional grouping in this transformed principal component space mirrors the outcomes of the cluster analysis method. The research outcomes hold practical value for potential investors, enabling them to pinpoint key investment areas. Furthermore, local self-governing bodies stand to benefit from these findings, gaining insights into specific regions’ relative investment attractiveness levels compared to their counterparts, while also uncovering vulnerabilities in distinct activity domains
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    Post-COVID-19 economic recovery in the context of SDG8 and SDG9: the case of selected Eastern European countries
    (2023) Hryhoruk, Pavlo; Khrushch, Nila; Grygoruk, Svitlana; Ovchynnikova, Olena
    Assessing the economic development of countries in the context of the tasks defined in the UN 2030 Agenda for Sustainable Development is essential from the point of view of determining progress in achieving the SDGs. It becomes especially relevant in periods of global challenges and disturbances, one of which is the COVID-19 pandemic. The goals of SDG8 and SDG9 contain indicators that are determined mainly by the state of development of the country’s economy, so the analysis of trends in their changes is important in the context of identifying trends in economic growth in general, as well as for evaluating progress in achieving these goals. The purpose of the study is to identify the impact of the COVID-19 pandemic on the economic development of countries to achieve sustainable development goals and assess progress trends in the post-pandemic recovery of the economies of Eastern Europe by analyzing quantitative data from official statistical sources. The object of the study is the economic development of Eastern European countries in the conditions of the COVID-19 pandemic. The study period covers the time range from 2017 to 2021 and includes both the pre-pandemic and pandemic periods. Eight countries of Eastern Europe were chosen as research objects. Indicators of official statistics related to SDG8 and SDG9 sub-goals were selected for analysis. The study showed a significant decrease in the values of most indicators, which was caused by the destructive effect of the pandemic. To assess the possible development trajectory, we calculated the estimated value of indicators for 2022 using the Holt-Winters method. The results showed that, despite some progress in 2021, in 2022, the values of the indicators are decreasing. Such estimates correspond to the trends provided by international institutions. We have built a composite indicator to assess the economic development trend comprehensively. The results of the evaluation confirmed the general trend towards a decrease in the level of economic growth in the context of the goals of SDG8 and SDG9 for all the countries of Eastern Europe selected in the study
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    Using a comprehensive index technology to analyze structural changes in the regions’ economic development in a COVID-19 pandemic: the case of Ukraine
    (2021) Григорук, П.М.; Григорук, Павло Михайлович; Hryhoruk, Pavlo; Khrushch, Nila; Хрущ, Н.А.; Хрущ, Ніла Анатоліївна; Григорук, С.С.; Григорук, Світлана Сергіївна; Grygoruk, Svitlana; Hryhoruk, P.; Grygoruk, S.; Khrushch, N.
    The paper investigates the issues of evaluating structural changes in the regions' economic development based on the comprehensive index assessment technology. The impact of the Covid-19 pandemic on regional development and changes in the regional structure is considered. The authors propose the use of block convolution to design a comprehensive index based on a set of metric initial indicators that characterize the regions' economic development. Grouping the set of initial indicators is carried out based on the method of an extreme grouping of parameters and the method of principal components. A weighted linear additive convolution was used to develop partial composite indices and an economic development comprehensive index. The practical approbation was carried out for the regions of Ukraine according to the data of 9 months of 2019 and the same period of 2020. To establish the regions' structure, we used the division of the comprehensive index values into intervals and further distributing regions into classes according to the. There is a general decrease in the value of the integrated indicator in 2020, caused by the impact of the Covid-19 pandemic. However, no significant changes in the structure of the regions were detected, which indicates an equally negative impact of the pandemic for all regions of Ukraine.
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    Using Non-Metric Multidimensional Scaling for Assessment of Regions’ Economy in the Context of Their Sustainable Development
    (2020) Hryhoruk, Pavlo; Grygoruk, Svitlana; Khrushch, Nila; Hovorushchenko, Tetiana; Григорук, П.М.; Григорук, Павло Михайлович; Григорук, С.С.; Григорук, Світлана Сергіївна; Хрущ, Н.А.; Хрущ, Ніла Анатоліївна; Говорущенко, Т.О.; Говорущенко, Тетяна Олександрівна
    Solving the problems of regions’ socio-economic development is strategic and most important for any country. In particular, the implementation of a new, active role of the region as a subject of sustainable development is important for the direct implementation of current regional policy. An important component of such a policy is the assessment of sustainable development of regions, which contributes to the timely detection of internal and external threats, the development of necessary stabilizing measures to prevent their negative impact, the formation of strategies aimed at sustainable regional systems. The economic system is an important subsystem of the region. The article proposes an approach to assessing the regions’ economic development in the context of ensuring their sustainable development. We used the methods of multidimensional nonmetric scaling to solve this problem. The study aims to determine the structure of regions in the context of their sustainable development. Based on non-metric data reflecting the economic development of Ukraine’s regions, two-dimensional space of latent scales was built based on multidimensional measures of proximity between them, and the positioning of regions in this space was carried out. The results received a semantic interpretation, which was improved by using the procedure of rotation of the scale space. The use of multidimensional non-metric scaling confirms its usefulness for the study of economic development of regions in the region and allows for their comparison and dynamics of their structure in the context of sustainable development.