Bu çalışmada ülkemizde faaliyet gösteren önemli iş arama web sitelerinde 2017-2018 döneminde yayınlanan bilişim sektörü iş ilanlarının niteliksel analizinin yapılması hedeflenmiştir. Bu kapsamda NVivo programı ile nitel veri analizinin bir alt unsuru olan içerik analizi çalışması yapılmıştır. Bir yıl içerisinde bilişim sektöründe faaliyet gösteren firmaların ihtiyaç duyduğu işgücüne ait verilerin sergilendiği bilişim ilanları üzerinden gerçekleştirilen kodlama ve analiz çalışması ile sektörün istihdam yapısı incelenmiştir. Çalışmanın ileride gerçekleştirilecek bilişim sektörü işgücü piyasası düzenlemelerine kaynak oluşturacağı değerlendirilmektedir.
Esports athletes are undoubtedly the most critical element of the esports sector, which embodies a growing economy all over the world. In the literature, there are yet no researches on the professional expectations and career prospects of those who build their career on professional esports athlete. Therefore, this study aims to examine the impact of future expectations of professional esports players in Turkey on their career planning behaviors with factors career adaptability, career optimism, and Perceived knowledge of the job market. The data collected by the survey method were analyzed with computer-aided statistics and Partial Least Square-Structural Equation Model (PLS-SEM) software. According to the results, there is a positive and meaningful relationship in the same direction with the future expectations of Turkish professional esport athletes and their career futures and planning attitudes. The future expectations of esport athletes positively affect their career compatibility and career optimism moderately, their perceptions towards the esports Job market weakly. In this sense, the sample group has a perception of a career future suitable for the esports ecosystem for a sustainable esports career.
This study aims to investigate the impact of macroeconomic indicators on Not in Education, Employment, or Training (NEET) population in Brazil, India, Indonesia, South Africa, and Turkey accepted as Fragile Five countries and Russia 2005-2018 period by using the panel data analysis method. Gross Domestic Product Per Capita (GDP), Inflation Rate (Consumer prices, INF), Adjusted savings for education expenditure (% of Gross National Income, S), Foreign Direct Investment (FDI), HDI index data were used for explaining the NEET for selected countries. The relationship between variables was analyzed using the Panel Data Methods via Fixed-Effects Model. Therefore, according to the findings of Driscoll and Kraay Estimator-One-Way Fixed Effects Model, "HDI, GDP, FDI and S" variables have a statistically significant effect on NEET as the dependent variable. According to findings, while a 1% increase in HDI and FDI respectively give rise an increase of 2.14% and 0.03% on NEET, a 1% increase in GDP, and S resulted in a decrease of 0.77% and 0.38% on NEET. The findings of the correlation matrix of residuals revealed that the correlation between countries was highest between India and Brazil and the lowest between Russia and Indonesia. According to preliminary results requirement for human development indicators and attraction to FDI should be directed to rural areas for reducing the NEET rates in FFC.
Socioeconomic issues in countries all over the world affect the entrepreneurship ecosystem. The impact of socioeconomic issues and developments on individuals' lives conceptualizes welfare. In this sense, the relationship between the welfare of the countries and the entrepreneurial climate is the object of interest. This study aims to investigate the impact of socioeconomic welfare on entrepreneurial climate in OECD countries with the PLS-SEM method by using OECD's Better Life Index and World Bank Ease of Doing Business Index for 2020. This study contributes to previous literature by reversing the analysis of the relationships between entrepreneurship and well-being. The model established with the assumption that all sub-indicators of the better life index positively impact the ease of doing business, only correlated with income, employment, and education indicators. However, there is only a positive and significant relationship between the education variable of better life and ease of doing business at p <,001 level among these correlations. According to results, the duration in education, education level of the working-age population, and the increase in the PISA averages of the countries increase the ease of doing business in terms of entrepreneurship climate.
This study aims evaluating the mediating role of psychological resilience in the effect of intolerance to uncertainty on unemployment anxiety, particularly in terms of nursing, other departments of health sciences, and social sciences. Data of this descriptive/cross-sectional study was collected between October and December 2020 via online survey method. Totally 634 students participated. Data were analysed with SmartPLS SEM software. Descriptive statistical analysis, confirmatory factor analyzes, structural equation modeling, mediation, and reliability analyses were performed. The positive and significant relationship was found between intolerance to uncertainty and unemployment anxiety and the negative and significant relationship was determined between these two variables and psychological resilience. University students were examined according to the departments; the positive impact of psychological resilience on unemployment anxiety was higher in nursing students compared to the others. Psychological resilience appears to be important for managing anxiety-related problems such as intolerance of uncertainty and unemployment anxiety. It can be thought that educational content should be created in a way that will increase the psychological resilience of other students as well as nursing students.
This study aims to investigate the effect of education, unemployment and not-in-education employment or training (NEET) population on human development in the EU-28 countries during the 2004-2018 period by using panel data analysis. According to the panel data analysis results with Common Correlated Effects Mean Group (CCEMG) estimator, the variables unemployment (UNE) and education (EDU) are statistically significant in explaining Human Development Index (HDI) across the panel. In contrast, the variable NEET is found to be not statistically significant, but the obtained coefficient is in the expected direction. In this case, a 1% increase in the UNE variable decreases HDI by 0.01%, and a 1% increase in the EDU variable increases HDI by 0.30%. The model appears to be statistically significant. According to the regression estimation results based on for each country, the coefficients vary quantitatively and statistically. Still, it is noteworthy that the NEET variable, which is statistically insignificant throughout the panel, varies statistically from unit to unit. These results confirm that NEET and HDI are negatively correlated in Czechia, Denmark, Finland, and Germany, while positively correlated in France, Poland, and Portugal.
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