In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 2012, Heft 4, S. 49-64
The aim of this study is to identify spatial differences in production potential and the achieved results of individual agricultural production in voivodships. The diversity is shown by the synthetic indicator, whose values were determined for individual voivodships with classical TOPSIS method (Technique for Order Preference by Similarity to an Ideal Solution). The index construction is based on data from the CSO Poland. In order to determine the cause-effect relationships between production potential and efficiency of utilization of production factors the investigation consisting of three stages was conducted. The first stage of the study determined the size of the synthetic indicator describing the productive potential of agriculture for each voivodship, in the second – the size of the measurer describing the efficiency of production factors was set, while the last stage of the study was to determine the condition of agriculture due to the production potential and results of production.
In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 2010, Heft 3, S. 54-67
This paper presents the quantified SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) using the Saaty's method of the analytic hierarchic process (AHP). This method is useful for programming development, especially, for estimation of weaknesses and strengths of an area as well as opportunities and threats of its environment. This is superior over classical (descriptive) method in the quantify possibility of SWOT factor validity, with regard to quality as well as quantity of these elements. The method can be useful over the choice of a growth strategy for any administrative district. This was illustrated by SWOT analysis of the Wielkopolskie voivodship.
In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 62, Heft 8, S. 74-84
The research aims at isolating and describing groups of rural gminas in Wielkopolskie voivodship with comparable financial autonomy and similar internal determinants in 2013. Furthermore, it allows to examine relations between the financial indicators and the socio-economic determinants. The PCA (Principal Component Analysis) biplot was used in the research. Data published by the Local Data Bank of the CSO and the Ministry of Finance was applied as a study informational basis. It was found that the highest level of financial autonomy was observed in the group of rural gminas close to the capital city of the voivodship. These gminas were distinguished by such determinants as net migration, percentage of inhabitants using sewage and gas supply system, as well as density and occupancy rate of accommodation establishments.
In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 61, Heft 2, S. 73-87
Financial independence is an important factor in socio-economic development, especially in rural areas. Rural gminas (communities), mainly located peripherally to larger urban centers, have significantly lower revenue potential. This also means a lower level of financial independence of rural gminas, which in turn can be a barrier in multifunctional rural development. This issue is a priority for the European Union. The main objective of this article is a synthetic assessment of the level of financial independence of rural gminas in the Wielkopolskie voivodship in 2013. The basis of information studies, using the method TOPSIS (Technique for Order Preference by Similarity is an Ideal Solution) to assess the financial condition of municipalities, were data from the Central Statistical Office (Local Data Bank — Public finances for 2013) and Ministry of Finance (Indicators for assessing the financial position of local government units in 2011—2013).