scholarly journals INDICATORS OF UKRAINIAN INDUSTRIES’ COMPETITIVENESS CONSIDERING FACTOR OF HUMAN CAPITAL

2021 ◽  
Vol 1 (15) ◽  
pp. 60-65
Author(s):  
Ihor Oleksiv ◽  
◽  
Diana Mirzoieva ◽  
Keyword(s):  
Cluster Analysis ◽  
Human Capital ◽  
Economic Activity ◽  
Statistical Data ◽  
Value Added ◽  
Hierarchical Cluster ◽  
Labor Intensity ◽  
Current State ◽  
Export Competitiveness ◽  
Export Product

The aim of the article is to determine the types of economic activity of Ukraine with high export competitiveness, taking into account human capital. The stages of creation of an export product were elaborated, the main resource of which is human capital, the indicator of its efficiency – labor intensity, the results – the volume of output and the share of value added in output, and the foreign economic result – the share of exports. As a result of hierarchical cluster analysis, five clusters were defined, the current state of which was characterized by statistical data. In particular, outpacing coefficients were calculated for each cluster. As the result, recommendations were provided for clusters and the Ukrainian economy as a whole

scholarly journals Cluster analysis of the economic activity of Slovak companies regarding potential indicators of earnings management

2021 ◽  
Vol 92 ◽  
pp. 07018
Author(s):  
Marek Durica ◽  
Lucia Svabova
Keyword(s):  
Cluster Analysis ◽  
Earnings Management ◽  
Economic Activity ◽  
Value Added ◽  
Hierarchical Cluster ◽  
Financial Data ◽  
Earnings Manipulation ◽  
Economic Activities ◽  
Financial Characteristics ◽  
Manipulation Detection

Research background: All over the world, any information about the earnings manipulation is very important for all the stakeholders of the companies. Therefore, it is necessary to detect this situation in a certain way. The global practice has shown that it is appropriate to create detection models and it would be very useful to specify individual sectors or the groups of sectors of economic activities of companies. Purpose of the article: The article aims to the financial ratios of Slovak companies that are globally used in the detection of earnings management. Based on hierarchical cluster analysis we identify groups of economic activities (according to the international NACE classification) with similar financial characteristics. Methods: For efficient earnings manipulation detection, high-quality and up-to-date financial data is required. We used financial data of real Slovak companies from the year 2018 obtained from international database Amadeus. After a precise pre-preparation of the dataset, we use the standard clustering procedures. Using the analysis of the dendrogram, the groups of the companies with their economic activities are identified. Findings & Value added: The results of the analysis show that there exist logical groups of NACE categories of economic activity of companies with similar characteristics. Regarding potential earnings manipulation, companies in these groups are as similar as possible. Therefore, financial characteristics can be analyzed together, and more accurate detection models could be created for them.

Reassessing the Export Competitiveness of Vietnam

2019 ◽  
Vol 5 (5) ◽  
pp. 539-549
Keyword(s):  
Human Capital ◽  
Comparative Advantage ◽  
Value Added ◽  
Industry Trade ◽  
Export Competitiveness

In this paper, primarily the export specialisation pattern of Vietnam has been examined from the perspective of domestic value added exports. In addition, an effort has been made to identify presence of exaggeration in gross exports measures of industries level competitiveness. Empirical findings suggest that the export specialisation of Vietnam has reversed, and there is presence of exaggeration in the estimates of comparative advantage of ‘human capital and technology intensive’ industries that has also caused in ballooning up their shares in gross exports. Such pattern has arisen because intra-industry trade has become increasingly significant in Vietnam. Received 11th March 2019; Revised 17th October 2019, Accepted 20th October 2019

scholarly journals The Importance of Globalisation and Learning Capital for Economic Growth

2021 ◽  
Vol 92 ◽  
pp. 08002
Author(s):  
Mária Antalová
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Slovak Republic ◽  
Value Added ◽  
One Dimension ◽  
Negative Consequences ◽  
Daily Lives ◽  
Current State ◽  
Political Dimensions ◽  
The Empirical Analysis

Research background: In our paper, we focus on two important phenomena that are currently culminating and bringing their positive as well as negative consequences. They are globalization and the learning capital. In research, experts are primarily oriented on globalization, which we perceive so intensely in our daily lives. There exist extensive studies developed on a theoretical, methodological as well as empirical basis. Experts are intensively dealing also with the human capital and, above all, with its impact on various socio-economic phenomena. However, they are paying less attention to the learning capital, which we consider one dimension of the human capital. Purpose of the article: Link between the human capital and the economic growth has long been clarified, but the relation between the learning capital is not remained at forefront of the research intentions. For this reason, we have decided to examine the interconnectedness between globalization and the learning capital in selected EU countries and to determine its contribution to the economic growth. Methods: In quantification of globalization, we use the overall KOF Globalization Index, which consists of 3 components: the economic, social and political dimensions. There does not exist uniform procedure for examining the learning capital. For this reason, we rely on Human Development Index data. Findings & Value added: In the empirical analysis, we focus on the evaluation of the current state of globalization as well as the learning capital in the Slovak Republic and verify the established hypotheses concerning the interconnection of these two phenomena and their impact on the economic growth.

scholarly journals Cluster analysis of the impact of blockchain technologies upon the development of the sectors of national economy

2021 ◽  
pp. 15-28
Author(s):  
Marat Rashitovich Safiullin ◽  
Azat Rafikovich Sharapov ◽  
Leonid Alekseevich Elshin
Keyword(s):  
Cluster Analysis ◽  
Russian Federation ◽  
National Economy ◽  
Economic Activity ◽  
Business Models ◽  
Value Added ◽  
Economic Environment ◽  
Economic Sectors ◽  
The Russian Federation ◽  
The Impact

Prospects for the development of national economy in the context of integration of blockchain technologies into the system of economic processes testify necessitate elaboration of the methods and algorithms for formalized assessment of their impact upon the key parameters of socioeconomic dynamics. If within scientific-and-expert space, one may occasionally come across the works dedicated to separate aspects of this scientific methodological problem, the questions of the impact of blockchain technologies upon individual economic sectors are yet to be explored within the information-analytical and scientific space. The methods of empirical research of the impact of blockchain technologies upon the parameters of economic development currently did not find their consolidated solution, and are of fragmentary nature. This research is an attempt to strengthen the positions of formalized approaches towards examination of the articulated scientific and practical problem. The subject of this research is the economic relations of economic agents pertaining to implementation of blockchain technologies in the economic activity and formation of the new business models. The object is the types of economic activity of the national economy of the Russian Federation and their sensitivity to the diffusion of blockchain technologies. The article offers an algorithm for studying the dynamics of gross value added of the economic sectors of the Russian Federation through the prism of possible transformation of the key parameters of functionality of the financial and real sectors of the economy as a result of diffusion of blockchain technologies. Leaning on the advanced hypotheses, the author builds co-integration models for the indicated types of economic activity, which reveal the contribution of exogenous factors that are being adjusted under the pressure of infiltration of the distributed data storage technologies into the economic environment to the degree of incremental value added. This allows conducting cluster analysis of the economic sectors under review in accordance of their sensitivity to institutional changes caused by integration of the blockchain technologies into the economic environment.

Human Capital in Self‑Employed Persons’ Economic Activity – Determinant or Barrier to Achieving Success

2016 ◽  
Vol 41 (3) ◽  
pp. 11-27
Author(s):  
Anna Bagieńska
Keyword(s):  
Human Capital ◽  
Economic Activity ◽  
Statistical Data ◽  
Education Level ◽  
The Self ◽  
University Graduates ◽  
Market Knowledge ◽  
Knowledge And Skills ◽  
Material Resources

In economic activity of all entities on the market, knowledge and skills are of great importance, since they allow entrepreneurs to properly use the potential of various material and non‑material resources. The determinant of success is, among others, human capital, both the owner’s and the employees’. The statistical data confirm an increasing education level of the self‑employed. The entrepreneurs who are university graduates play the most important role in creating work places. Moreover, thanks to their education, the entrepreneurs’ actions are more effective in terms of maintaining and developing the activity which they conduct. The growing problem of acquiring employees with adequate qualifications is becoming a barrier to the development of company

scholarly journals FUZZY APPROACH TO DISCRETE DATA REDUCTION: AN APPLICATION IN ECONOMICS FOR ASSESSING THE SKILL PREMIUM

2015 ◽  
Vol 17 (3) ◽  
pp. 414-429 ◽  
Author(s):  
Abdul SULEMAN ◽  
Fátima SULEMAN ◽  
Elizabeth REIS
Keyword(s):  
Cluster Analysis ◽  
Human Capital ◽  
Fuzzy Clustering ◽  
Hierarchical Cluster ◽  
Skill Premium ◽  
Monetary Incentives ◽  
Fuzzy Approach ◽  
Original Dataset ◽  
The Impact ◽  
Methodological Comparison

Measures of stock of skills alternative to human capital have raised fresh difficulties, especially in data managing. We propose to empirically compare the efficiency of a hierarchical cluster analysis and a fuzzy clustering in reducing discrete skill data. The outcomes of both methods are subsequently used to measure the impact of skills on earnings in addition to human capital. The proposed methodological comparison was made using an original dataset of retail bankers’ skills assessed by supervisors. Empirical evidence shows that the fuzzy approach is more efficient than the hierarchical clustering: the resulting clusters are fewer and easier to interpret. Furthermore, the earnings equation enriched with skill variables allowed us to correct the education premium, and provides information on monetary incentives related to individual skills. Our paper attempts to raise researchers’ and practitioners’ awareness of data reducing methods, and their implications for wage determinants.

scholarly journals Reduction Of An Economy's Raw Material Dependence And The Human Capital Of A Country

2017 ◽  
Vol 20 (1) ◽  
pp. 53-73 ◽  
Author(s):  
Viacheslav Perepelkin ◽  
Elena Perepelkina
Keyword(s):  
Human Capital ◽  
Economic Activity ◽  
Oil And Gas ◽  
Resource Curse ◽  
Value Added ◽  
Gas Production ◽  
Dutch Disease ◽  
The Other ◽  
Raw Material ◽  
Oil And Natural Gas

This paper evaluates the raw material dependence of two export-oriented oil and gas extracting countries. We find evidence of presence of the Dutch disease in both countries and of the resource curse in Russia. Reduction of volumes of crude oil and natural gas production and exports, compensated by the growth of value added in other kinds of economic activity, suggests that Norway is gradually overcoming the Dutch disease by means of expanded reproduction of human capital. On the other hand, extraction of hydrocarbons may remain a driver of the Russian economic growth.

Cluster Analysis of Industrial Transfer Park Based on Carbon Emission Intensity

2013 ◽  
Vol 291-294 ◽  
pp. 1550-1555 ◽  
Author(s):  
Jia Feng Fan ◽  
Hao Xu ◽  
Juan Yuan ◽  
Bang Zhu Zhu
Keyword(s):  
Cluster Analysis ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Value Added ◽  
Guangdong Province ◽  
Hierarchical Cluster ◽  
Industrial Transfer ◽  
Leading Industry ◽  
Emissions Intensity

The carbon emission control of Industrial Transfer Park is analyzed from four aspects. Metrics of these four aspects are energy consumption per industrial value added of leading industry, carbon emissions intensity of buildings, carbon emissions intensity of transportation and carbon sinks. On this basis, 36 industrial transfer parks in Guangdong province are analyzed with the method of Hierarchical cluster in order to explore practical measures to reduce carbon emissions in the parks.

DRSA: a non-hierarchical clustering algorithm using k-NN graph and its application in vegetation classification

2015 ◽  
pp. 125-138 ◽  
Author(s):  
I. V. Goncharenko
Keyword(s):  
Cluster Analysis ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Clustering Algorithms ◽  
Protein Structures ◽  
Hierarchical Cluster ◽  
Vegetation Classification ◽  
K Nearest Neighbor ◽  
Neighbor Graph ◽  
Nearest Neighbor Graph

In this article we proposed a new method of non-hierarchical cluster analysis using k-nearest-neighbor graph and discussed it with respect to vegetation classification. The method of k-nearest neighbor (k-NN) classification was originally developed in 1951 (Fix, Hodges, 1951). Later a term “k-NN graph” and a few algorithms of k-NN clustering appeared (Cover, Hart, 1967; Brito et al., 1997). In biology k-NN is used in analysis of protein structures and genome sequences. Most of k-NN clustering algorithms build «excessive» graph firstly, so called hypergraph, and then truncate it to subgraphs, just partitioning and coarsening hypergraph. We developed other strategy, the “upward” clustering in forming (assembling consequentially) one cluster after the other. Until today graph-based cluster analysis has not been considered concerning classification of vegetation datasets.

Estimation of economic specialization of Ukrainian regions in the context of global trends

2019 ◽  
pp. 24-31
Author(s):  
Svitlana Ishchuk ◽  
Lyubomyr Sozanskyy
Keyword(s):  
National Economy ◽  
Economic Activity ◽  
Commodity Prices ◽  
Value Added ◽  
High Tech ◽  
Agricultural Commodity ◽  
Macroeconomic Factors ◽  
Gross Value Added ◽  
Its Regions ◽  
Economic Specialization

The scale and deep heterogeneity of the national economy of Ukraine in the regional context make the relevance of scientific research in this thematic area. The purpose of the article is to determine the economic specialization of the regions of Ukraine by key economic activities contributing to the formation of gross value added, as well as outlining the potential risks to the national economy, taking into account the situation on world commodity markets. The results of the research showed that one of the consequences of the unstable dynamics of industrial production in Ukraine under the influence of geopolitical and macroeconomic factors is the reduction of industrial specialization of the economy of a number of Ukrainian regions. Thus, in 2017 the manufacturing was the leading economic activity (with the highest share in the gross value added created) in 11 regions, compared to 15 in 2012. So Poltava, Donetsk, Dnipropetrovsk and Zaporizhzhya regions are considered to be “highly industrial”. At the same time, the agrarian specialization of the economy of Ukraine and its regions deepened – in 2017 agriculture became the leading type of economic activity in 11 regions (compared to 7 in 2012). The most “agrarian” in Ukraine (with a share of agriculture in gross value added over 30%) in 2017 became the Kherson, Kirovohrad and Khmelnytsky regions. Increasing the level of “agrarianization” of the national economy in the context of volatility of agricultural commodity prices on the world markets poses significant risks for the socio-economic development of Ukraine and its regions. These risks are exacerbated by the high amplitude of fluctuations in the volume and structure of domestic agricultural products and the low degree of processing of raw materials. To improve the structure of domestic commodity exports (in the direction of increasing its share of products with a higher degree of processing) and to deepen its diversification, a number of measures should be carried out aimed at stimulating export activity of enterprises (industrial and agro-industrial), carrying out technical and technological re-equipment of industrial and export production bases, creation of new high-tech industries on the basis of the implementation of powerful innovation and investment projects.

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