Profile of Country-Clusters According to Globe Dimensions of Cultur

2013 ◽  
Vol 2013 (2 (155)) ◽  
Author(s):  
Marcin Komor
Keyword(s):  
Country Clusters

Understanding Economic and Health Factors Impacting the Spread of COVID-19 Disease (Preprint)

2020 ◽  
Author(s):  
Aleksandr Farseev ◽  
Yu-Yi Chu-Farseeva ◽  
Yang Qi ◽  
Daron Benjamin Loo
Keyword(s):  
Public Health ◽  
Quantitative Research ◽  
Health Indicators ◽  
Initial Study ◽  
Disease Spread ◽  
Factors Affecting ◽  
Country Level ◽  
Development Scenarios ◽  
Health Factors ◽  
Country Clusters

UNSTRUCTURED The rapid spread of the Coronavirus 2019 disease (COVID-19) had drastically impacted life all over the world. While some economies are actively recovering from this pestilence, others are experiencing fast and consistent disease spread, compelling governments to impose social distancing measures that have put a halt on routines, especially in densely-populated areas. Aiming at bringing more light on key economic and public health factors affecting the disease spread, this initial study utilizes a quantitative statistical analysis based on the most recent publicly-available COVID-19 datasets. The study had shown and explained multiple significant relationships between the COVID-19 data and other country-level statistics. We have also identified and statistically profiled four major country-level clusters with relation to different aspects of COVID-19 development and country-level economic and health indicators. Specifically, this study has identified potential COVID-19 under-reporting traits as well as various economic factors that impact COVID-19 Diagnosis, Reporting, and Treatment. Based on the country clusters, we have also described the four disease development scenarios, which are tightly knit to country-level economic and public health factors. Finally, we have highlighted the potential limitation of reporting and measuring COVID-19 and provided recommendations on further in-depth quantitative research.

scholarly journals Closed-Loop Supply Chain: A bibliometric and visualization analysis

2021 ◽  
Vol 234 ◽  
pp. 00011
Author(s):  
Liudmyla Saher ◽  
Liubov Syhyda ◽  
Olena Korobets ◽  
Tamara Berezianko
Keyword(s):  
Supply Chain ◽  
Reverse Logistics ◽  
Closed Loop ◽  
Scientific Production ◽  
Closed Loop Supply Chain ◽  
Visualization Analysis ◽  
Current State ◽  
Country Clusters ◽  
Scopus Database ◽  
Productive Authors

Nowadays, enterprises have to be good for society, to take care of the environment, and to achieve profit at the same time. And the closed-loop supply chain helps them being so. However, there is a lack of bibliometric and visualization research in the area of “Closed-Loop Supply Chain”. Thus, this research aims to present a bibliometric overview to define the current state of scientific production regarding “Closed-Loop Supply Chain”. The review of 807 publications from the Scopus database (1995–2020) was conducted. Two combinations of words with the logical operator (“supply chain” AND “reverse logistics”) were used. The “title, abstract, keywords” field of search in the Scopus database was done. The visualization of the results was made using VOSviewer program to graphically map the material. The study used the co-occurrence of keywords and co-authorship (country) analyses. As a result, the most productive authors and journals were defined. The most cited studies were determined. Country clusters and keywords (co-occurrence) clusters were represented. The obtained results of the analysis and graphical presentations are relevant, and they form the basis for a better understanding of the concept of Closed-Loop Supply Chain.

Clustering of host countries to facilitate learning between similar international construction markets

2019 ◽  
Vol 27 (1) ◽  
pp. 66-82
Author(s):  
Beste Ozyurt ◽  
Irem Dikmen ◽  
M. Talat Birgonul
Keyword(s):  
Cluster Analysis ◽  
Construction Projects ◽  
Lessons Learned ◽  
Extensive Literature ◽  
Host Countries ◽  
Related Factors ◽  
Content Type ◽  
International Construction ◽  
Country Factors ◽  
Country Clusters

Purpose In the global construction industry, experience gained in various countries is a major source of competitive advantage. By transferring the knowledge gained in previous projects using an effective knowledge management strategy, they can increase their competitiveness by adopting best practices and by not repeating the same mistakes under similar conditions. The purpose of this paper is to demonstrate how similar countries can be clustered to facilitate learning in global markets. Design/methodology/approach Initially, country factors that can affect success in international projects and can be used to assess the similarity of markets were identified by an extensive literature review and prioritised by a web-based questionnaire. A country evaluation form was prepared to collect country-specific data to be used in the cluster analysis of 39 countries where the Turkish contractors have been frequently working since the last 45 years. Cluster analysis was performed with SPSS 23.0. Findings Three country clusters were obtained and validated. Ultimately, how obtained country clusters may be used to facilitate learning from international construction projects was demonstrated by using an illustrative example. Research limitations/implications The findings depend on the experience and perspective of Turkish contractors doing business abroad. Thus, the identified clusters are not generic. Moreover, country clusters were not identified considering only the country factors such as economy, culture, politics, etc.; thus, countries in the same cluster do not necessarily represent “similar” countries in terms of macro-factors. Clusters were identified so that the lessons learned can be effectively transferred within the same cluster considering construction and project-related factors as well as country-related factors. Although the findings cannot be generalised and clusters are not static, it is believed that the methodology used in this research is repeatable for different countries considering different timeframes. Originality/value Theoretical contributions include the identification of factors that can be used for similarity assessment of countries for transferring lessons learned as well as a methodology for clustering. Findings may also have a practical value for the Turkish contractors.

scholarly journals Listener Modeling and Context-Aware Music Recommendation Based on Country Archetypes

2021 ◽  
Vol 3 ◽  
Author(s):  
Markus Schedl ◽  
Christine Bauer ◽  
Wolfgang Reisinger ◽  
Dominik Kowald ◽  
Elisabeth Lex
Keyword(s):  
Recommendation System ◽  
State Of The Art ◽  
Music Listening ◽  
Context Aware ◽  
Music Recommendation ◽  
Music Preferences ◽  
User Models ◽  
Gating Mechanism ◽  
Country Clusters ◽  
Country Specific

Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a considerable extent, in country-specific music listening profiles. Previous work has already identified several country-specific differences in the popularity distribution of music artists listened to. In particular, what constitutes the “music mainstream” strongly varies between countries. To complement and extend these results, the article at hand delivers the following major contributions: First, using state-of-the-art unsupervized learning techniques, we identify and thoroughly investigate (1) country profiles of music preferences on the fine-grained level of music tracks (in contrast to earlier work that relied on music preferences on the artist level) and (2) country archetypes that subsume countries sharing similar patterns of listening preferences. Second, we formulate four user models that leverage the user’s country information on music preferences. Among others, we propose a user modeling approach to describe a music listener as a vector of similarities over the identified country clusters or archetypes. Third, we propose a context-aware music recommendation system that leverages implicit user feedback, where context is defined via the four user models. More precisely, it is a multi-layer generative model based on a variational autoencoder, in which contextual features can influence recommendations through a gating mechanism. Fourth, we thoroughly evaluate the proposed recommendation system and user models on a real-world corpus of more than one billion listening records of users around the world (out of which we use 369 million in our experiments) and show its merits vis-à-vis state-of-the-art algorithms that do not exploit this type of context information.

scholarly journals Comparative prevalence of COVID–19 in european countries: a time window at second wave

2020 ◽  
Vol 9 (6) ◽  
pp. 196-207
Author(s):  
José M. Tallon ◽  
Paulo Gomes ◽  
Leonor Bacelar–Nicolau
Keyword(s):  
Time Window ◽  
European Countries ◽  
Multivariate Statistical ◽  
Daily Lives ◽  
Cumulative Score ◽  
Incidence And Mortality ◽  
Country Clusters ◽  
And Cluster Analysis ◽  
Wave Methods ◽  
Second Wave

Introduction: The pandemic generated by COVID–19 completely changed people's daily lives, their relationship with family and friends, unexpectedly disrupted their working conditions and enhanced the need for an enduring resilience to face yet a second wave of the disease. It is crucial to keep continuously updating our knowledge about COVID–19 prevalence and incidence evolutions over large connected territories, where the disease is striking in alarming proportions. Objective: The main objective of this research is to identify and describe COVID–19 prevalence, incidence and mortality profiles in EU and EEE/EFTA countries, seven months after the start of the pandemic in Europe, and more recent tendencies, probably associated to the beginning of a second wave. Methods: This COVID–19 study covers thirty–one European countries. Six epidemiological variables where analyzed per 100 000 inhabitants on October 25 2020, two of them evaluated over the seven previous days. A multivariate statistical exploratory analysis based on rank principal components and cluster analysis was applied. Results: A COVID–19 prevalence typology of six country clusters was identified regarding 31 countries (EU, UK and three EEE/EFTA countries). The five epidemiological variables and number of tests revealed a wider dispersion with outlier observations. The rank transformation of data and their multivariate statistical analysis allowed us to construct a rational to better discriminate and describe these clusters, identifying specific behaviours related to the global prevalence from March until the end of October or highlight recent evolutions of COVID–19 incidence in the context of a second wave of pandemic. In fact we pinpointed country clusters where COVID–19 reached alarming levels which persist, or have even worsen, at the beginning of the second wave. Additionally, two other clusters were identified: one with countries that seems to be evolving into a situation under control, and another cluster of countries very weakly struck on the first wave, but are now facing a very complex surge, that will test their health systems capacity and timely response regarding covid and non–covid patients. Finally, the worst and more dramatic situation occurred in countries where the number of deaths per 100 000 inhabitants attained an impressive cumulative score.

scholarly journals Job Security Across Europe

Intersections ◽  
2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Denisa Fedakova ◽  
Alberto Veira-Ramos
Keyword(s):  
Research Question ◽  
Social Indicators ◽  
Explanatory Power ◽  
Job Security ◽  
European Social Survey ◽  
Social Expenditure ◽  
Current Period ◽  
Northern Country ◽  
Country Clusters ◽  
Southern Country

According to OECD statistics the unemployment rate in 2011 varied across Europe 10–20 per cent. At that time, European Social Survey Round 5 data was collected which showed that job security was highest in northern country cluster, moderate in southern country cluster, and lowest in the Visegrad country cluster. Our first research question addressed whether general, aggregated social indicators (unemployment and employment rate, and social expenditure) determine perceived job security in the three country clusters. The overall sample was comprised of three southern countries, four Visegrad countries, and four northern countries and consisted of people aged 20-60 who reported to be in paid work and working more than 30 hours a week. The main aim of the current paper was to examine the predictors of job security in the context of all three country clusters. Results indicated that the proposed model of job security predictors showed the best fit for the southern country cluster, explaining over 30 per cent of the variance of perceived job security (background characteristics explained there most of the variance there). Variation in the explanatory power of the job security variable in the northern country cluster was mainly explained by both job and organizational characteristics, while in the Visegrad country cluster it was mainly explained by job characteristics. The paper is a contribution to the discussion about job security in the current period of recession in Europe.

Correlation between human rights promotion and health protection: a cross country analysis

2019 ◽  
Vol 13 (1) ◽  
pp. 72-92
Author(s):  
Sedef Akgungor ◽  
Kamiar Alaei ◽  
Weng-Fong Chao ◽  
Alexandra Harrington ◽  
Arash Alaei
Keyword(s):  
Cluster Analysis ◽  
Human Rights ◽  
Health Outcomes ◽  
Regression Model ◽  
Political Rights ◽  
Cross Sectional ◽  
Content Type ◽  
Cultural Rights ◽  
Proxy Variables ◽  
Country Clusters

Purpose The purpose of this paper is to explore the correlation among health outcomes, and civil and political rights (CPR) and also economic, social and cultural rights. Design/methodology/approach The study uses cross-sectional data from 161 countries. The authors use health outcomes and human rights variables in the model. In order to combine dimensions of human rights, this paper uses factor analysis and obtains proxy variables that measure economic, social and cultural rights and CPR. The two proxy variables are used as independent variables to explain variations in health in a regression model. The paper then classifies countries by cluster analysis and explores the patterns of different components of human rights and health outcomes across country clusters. Findings The regression model demonstrates that the economic, social and cultural rights variables explain variations in all health outcomes. The relationship between CPR and health is weaker than that of the economic, social and cultural rights. Cluster analysis further reveals that despite the country’s commitment to CPR, those that highly respect economic, social and cultural rights lead to superior health outcomes. The more respect a country has for economic, social and cultural rights, the better the health outcomes for the citizens of that country. Practical implications National policies should consider equal emphasis on all dimensions of human rights for further improvements in health. Originality/value The sole promotion of CPR such as democracy and empowerment, absence of adequate support of economic, social and cultural rights such as rights to housing, education, food and work can only contribute partially to health.

Changes in the level and structure of food expenses in the European Union in the context of increasing household incomes

2020 ◽  
pp. 709-731
Author(s):  
Ryszard Kata ◽  
Magdalena Cyrek ◽  
Piotr Cyrek
Keyword(s):  
European Union ◽  
Food Consumption ◽  
Eu Enlargement ◽  
Income Level ◽  
Consumption Patterns ◽  
The European Union ◽  
Income Differences ◽  
Eu Countries ◽  
Country Clusters ◽  
The Eu

Changes in the consumption model are inherent in the processes of socio-economic development the indicator of which is the enrichment of the population. Such changes include the emergence of new proportions in the consumption of particular categories of goods and services, and, according to the regularities observed by Engel, lower the share of expenditure on a broadly understood category of food. Increasing incomes are also linked to changes in the internal structure of food consumption. This study is to assess the changes in the level and structure of food expenses resulting from the enrichment of the European Union (EU) societies. The study covered the co-occurrence of differences in food consumption with households' income differences in the EU countries. The analyses presented in the study relate to the period after the EU enlargement in 2004 and are based on the Eurostat data. The research allows for a positive verification of the thesis that the higher the incomes, the more balanced the structure of food expenses. In more affluent economies, the consumption of a more diversified basket of goods is observed. This finding is supported by the high negative correlation between the structure concentration ratio for food expenditure and the households' income level. In addition, the identification of country clusters based on consumption expenditure broken down into food categories makes it possible to confirm the thesis that there are income differences between economies with different consumption models. It is confirmed by the variance analysis concerning income level for countries in three groups: the South Europe with the highest food expenses, the Central and Eastern Europe with the most limited spending and the lowest income, and the affluent "old" EU members with high expenses on luxuries consumed for social reasons. However, the analyses presented here do not allow for validation of the thesis that food consumption patterns among the EU countries become similar, but rather point to the predominance of the consumption divergence processes, which occur despite the declining income differences. This claim is based on the observation of increasing average Euclidian distance between food expenses in the EU countries in 2005 and 2015. Nevertheless, some signs of shift towards Mediterranean consumption patterns may be found for many societies.

scholarly journals Worlds, Families, Regimes: Country Clusters in European and OECD Area Public Policy

2008 ◽  
Vol 31 (1-2) ◽  
pp. 321-344 ◽  
Author(s):  
Francis G. Castles ◽  
Herbert Obinger
Keyword(s):  
Public Policy ◽  
Country Clusters
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