scholarly journals Assessment of Sustainable Socioeconomic Development in European Union Countries

2020 ◽  
Vol 12 (5) ◽  
pp. 1986 ◽  
Author(s):  
Viktorija Skvarciany ◽  
Daiva Jurevičienė ◽  
Gintarė Volskytė
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Socioeconomic Development ◽  
Scientific Literature ◽  
Hierarchical Cluster ◽  
The Third ◽  
Factors Influencing ◽  
European Union Countries ◽  
Current Article ◽  
The Eu

There are still debates in the scientific literature about the factors influencing countries’ sustainable socioeconomic development. Therefore, the current article aims at determining the factors of sustainable socioeconomic development and assessing its level in the EU countries. The following methods were employed for the research: an evaluation based on distance from average solution (EDAS) and hierarchical cluster analysis (HCA). EDAS was used to reveal which countries have the highest level of sustainable socioeconomic development, and which have the lowest. The ranking was done based on the appraisal score, which is an outcome of EDAS. Hierarchical cluster analysis (HCA) was used for clustering the countries based on the appraisal scores in order to distinguish groups of countries having a similar level of sustainable socioeconomic development. The results revealed that the highest level of sustainable socioeconomic development is in Germany, and the lowest in Portugal. Based on HCA, the countries were divided into three groups. The first cluster’s countries have the weakest sustainable socioeconomic development, and countries assigned to the third cluster have the best. In the current research, the third cluster consists of one country, Germany, which supports the results obtained with the EDAS method, i.e., Germany is the country with the highest level of sustainable socioeconomic development in the EU.

scholarly journals The Human Resources as an Important Factor of Regional Development

2021 ◽  
Vol 21 (3) ◽  
pp. 1464-1478
Author(s):  
Dana Jašková ◽  
Katarína Havierniková ◽  
Katarína Havierniková
Keyword(s):  
Cluster Analysis ◽  
Human Resources ◽  
Statistical Methods ◽  
Hierarchical Cluster Analysis ◽  
Socioeconomic Development ◽  
Slovak Republic ◽  
Hierarchical Cluster ◽  
Human Resources Development ◽  
Development Potential ◽  
Resources Development

The human resources present the key aspect of socioeconomic development, prosperity and competitiveness of each region due to the fact that contribute to increasing of employment, to the development of working places and improving the life standard of inhabitants. The main aim of the paper is the quantification of human resources development potential in Slovak regions. To meet this aim, the authors concentrated attention mainly on the evaluation of the level and variability of the selected indicators that were observed within four descriptors. The crucial contribution of the evaluation is the ranking of regions, based on the evaluation in each descriptor and drawing the overall ranking of human resources development potential in the Slovak Republic. To determine the order of regions, the relevant statistical methods were used: the characteristics of location and variability, hierarchical cluster analysis and its method of complete linkage. The results showed the dominance of Bratislava region that is following by Trnava and Žilina region.

scholarly journals #Dark inspiration: Eudaimonic entertainment in extremist Instagram posts

2020 ◽  
pp. 146144481989962
Author(s):  
Lena Frischlich
Keyword(s):  
Cluster Analysis ◽  
Content Analysis ◽  
Prosocial Behavior ◽  
Hierarchical Cluster Analysis ◽  
Qualitative Content Analysis ◽  
Hierarchical Cluster ◽  
Digital Data ◽  
Mixed Methods Case Study ◽  
Current Article

Eudaimonic entertainment, which motivates a reflection on topics such as virtue or meaning, has many benefits, such as fostering wellbeing and inspiring prosocial behavior. Yet, it may also have a darker side when Islamic extremists use accordant elements in online propaganda. So far, this “dark inspiration” has attracted little scholarly interest. The current article fills this gap via a mixed-methods case study of an Islamic extremist influencer on Instagram. The study combined a qualitative content analysis of the account’s postings from 2016 to 2018 ( n = 301 posts), with a hierarchical cluster analysis and digital data on aggregated user response to these posts. I found four types of post, ranging from calls for conservativism to calls for violent jihad. Different eudaimonic cues were used in all four types. Likes and comments varied as a function of type, with the violence promoting posts motivating the largest number of user responses.

Extraordinary circumstances: Covid-19 – Italian Serie A scenario

2021 ◽  
pp. 175433712110192
Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Round Robin ◽  
The Past ◽  
Novel Approach ◽  
Round Robin Tournaments

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.

scholarly journals Detection of drought events in Greece using daily precipitation

2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Daily Precipitation ◽  
Hierarchical Cluster ◽  
Seasonal Distribution ◽  
Drought Severity ◽  
Severe Drought ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
Insight Into

In this study a method proposed by Byun & Wilhite, which estimates drought severity and duration using daily precipitation values, is applied to data from stations at different locations in Greece. Subsequently, a series of indices is calculated to facilitate the detection of drought events at these sites. The results provide insight into the trend of drought severity in the region. In addition, the seasonal distribution of days with moderate and severe drought is examined. Finally, the Hierarchical Cluster Analysis method is used to identify sites with similar drought features.

An investigation on conceptual understanding about cosmology

2019 ◽  
Vol 15 (S367) ◽  
pp. 397-399
Author(s):  
Arturo Colantonio ◽  
Irene Marzoli ◽  
Italo Testa ◽  
Emanuella Puddu
Keyword(s):  
High School ◽  
Cluster Analysis ◽  
High School Students ◽  
Conceptual Understanding ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Content Area ◽  
School Students ◽  
Convenience Sample ◽  
Teaching Activities

AbstractIn this study, we identify patterns among students beliefs and ideas in cosmology, in order to frame meaningful and more effective teaching activities in this amazing content area. We involve a convenience sample of 432 high school students. We analyze students’ responses to an open-ended questionnaire with a non-hierarchical cluster analysis using the k-means algorithm.

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