In this research, it was aimed to examine relationship between regional inequalities in the provision of emergency health services and other health services in Turkey. The values of the number of ...emergency services and the population per emergency service for the years 2002-2021 were taken from the most up-to-date database published by the Ministry of Health in 2022 and were chosen as the dependent variables of the study. The "regional price level indices for consumption expenditures (PLI)" and "gross domestic product per capita, Statistical Regions Level 2 (PcGDP)" data compiled by TURKSTAT were used as independent variables. Number of emergency stations were significantly correlated with TR31 (İzmir) (r = 0.903; P < .01), TR32 (Aydin, Denizli, Muğla) (r = 0.771; P < .01), TR42 (Kocaeli, Sakarya, Düzce, Bolu, Yalova) (r = -0.798; P < .01), TR62 (Adana, Mersin) (r = 0.837; P < .01), TR63 (Hatay, K.Maraş, Osmaniye) (r = -0.749; P < .01), TR72 (Kayseri, Sivas, Yozgat) (r = -0.719; P < .01), TR83 (Samsun, Tokat, Çorum, Amasya) (r = 0.873; P < .01), TRA2 (Ağri, Kars, Iğdir, Ardahan) (r = -0.873; P < .01), TRB2 (Van, Muş, Bitlis, Hakkari) (r = -0.736; P < .01), TRC2 (Şanliurfa, Diyarbakir) (r = 0.697; P < .01), and TRC3 (Mardin, Batman, Şirnak, Siirt) (r = 0.574; P < .01). In total, 11 of 26 were significantly correlated with inequalities. Although the number of emergency services has increased since 2002 and the population density per emergency room has tended to decrease, regional inequalities also have an impact on the delivery of emergency services today.
Applying sustainable development into practice is an important national and regional policy goal in Slovenia; in addition, the country’s membership in the European Union further commits it to the ...goals of sustainable development. The research presented in this article is based on the use of a set of 32 economic, social and environmental indicators of sustainable development and the calculation of a synthetic indicator of sustainable regional development for all twelve Slovenian NUTS-3 regions in the period 2015–2019. In the final step, a synthetic assessment of the possibilities for implementing sustainable development in individual Slovenian regions is given, in which regions are classified into four different types. A comparison with the previous five-year period showed that Slovenia achieved progress in most of the socio-economic aspects of sustainable development analyzed, while the situation deteriorated with respect to environmental aspects. The largest differences among Slovenian regions were calculated in the economic area, and the smallest in the environmental area, which is also in line with the findings of previous research. There continues to be a development divide between the more prosperous western part of the country and the eastern part, which lags behind and for the most part also has poorer prospects for sustainable development. This trend is unfavorable for the balanced as well as sustainable development of Slovenian regions.
Within the context of EU efforts to achieve the objectives of sustainable development, this article presents the findings of a study that uses a selection of thirty-two economic, social, and ...environmental indicators to evaluate the extent of achieving these objectives in Slovenian statistical regions from 2010 to 2014. Based on the favorable or unfavorable state and trends established, the indicator values are assigned scores that make it possible to calculate the average values for individual development areas and their total average (i.e., the indicator of sustainable regional development). The calculations confirmed the hypothesis that the differences between Slovenian regions are the greatest with regard to economic issues and the smallest with regard to environmental issues. Both in Slovenia and in the EU in general, unfavorable environmental trends resulting from unsustainable use of energy and natural resources persist, even though Slovenia’s environment remains above average in terms of its conservation.
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The 2009 global economic crisis also affected the economic development of Slovenia’s statistical regions. Its impact can be measured in terms of the intensity of stress, and post-shock development ...can be measured in terms of the intensity of recovery. The study of regional economic resilience belongs to the concept of evolutionary economic geography and is based on an analysis of selected indicators that define the socioeconomic composition of the regions. In terms of shock impact and intensity of recovery, the regions are divided into four types with ascribed socioeconomic characteristics.
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The development period between 2007 and 2013 had a historical significance for Hungary as the funds that were provided by the European Union and were supplemented by the domestic and public sectors ...naturally offered great possibilities for the country’s sub-statistical regions and regions to inspire their development and innovation. In order to use these funds efficiently it is essential to incorporate the developments into the area’s capabilities, to harmonize them and to increase the role of the sub-statistical regions and regions. This study ranks the sub-regions of the Southern Great Plain Region in terms of their economic characteristics and identifies the most disadvantageous ones. Using as an example a specific sub-region it determines the local effects of EU payments with the application of different statistical methods.
Due to their above average growth, dynamic enterprises contribute significantly to general economic growth, especially in the field of job creation and the investment cycle. Therefore this article ...presents the potential of dynamic enterprises for the creation of jobs in selected Slovenian statistical regions. The empirical findings are divided into three different researched periods, namely for the period between 2006 and 2010, the period between 2007 and 2011, and the period between 2008 and 2012 on a population of 4,511, 4,380, and 3,725 dynamic enterprises respectively, taken from the entire national statistics database managed by AJPES (Agency of the Republic of Slovenia for Public Legal Records and Related Services) on the basis of 13 previously determined criteria. The objective of this article is twofold: In the first stage, it aims to present the dispersion of dynamic enterprises in different Slovenian regions based on a previously conducted qualitative and quantitative study, and in the second stage to show their potential for job creation. All in all, it was established that the analysed dynamic enterprises created all the net new jobs in the Slovenian national economy during the crisis (in the period between 2009 and 2012).
The aim of the paper is to analyse the number and proportion of employees, unemployment rates and theirterritorial trends in Latvia, and to compare them with those in Estonia and Lithuania. The paper ...analyses the number ofemployees at the main job, its proportion in the private sector, and unemployment rates in the Baltic countries and statisticalregions of Latvia. In 2000–2007, employment and its proportion in the private sector was on the increase. In 2008, an upwardtrend in Estonia and Lithuania started to decrease, but in Latvia number of employees and its proportion in the private sectoralready had dropped. In 2009, the number of employees continued to decline. The unemployment rate grew from 1998 to2000 and from III quarter 2008 to I quarter 2010. From 2001 to II quarter 2008, during an economic boom, it decreased to aminimum. A faster economic growth means a higher proportion of employees in the private sector; however, during theeconomic crisis, it creates more instability in the labour market than in the public sector, especially at the beginning. As thecrisis deepens, unemployment in the private sector begins to stabilize; however, it increases in the public sector.
The development period between 2007 and 2013 had a historical significance for Hungary as the funds that were provided by the
European Union and were supplemented by the domestic and public sectors ...naturally offered great possibilities for the country’s sub-statistical
regions and regions to inspire their development and innovation. In order to use these funds efficiently it is essential to incorporate the
developments into the area’s capabilities, to harmonize them and to increase the role of the sub-statistical regions and regions. This study ranks
the sub-regions of the Southern Great Plain Region in terms of their economic characteristics and identifies the most disadvantageous ones.
Using as an example a specific sub-region it determines the local effects of EU payments with the application of different statistical methods.
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