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Results in Journal Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu: 6,016

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Zofia Jarka, Tomasz Pachowicz, Tomáš Kalina, Martin Jurkovič
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 65, pp 28-45; https://doi.org/10.15611/pn.2021.1.03

Agata Olechnowicz-Szewczyk, Elżbieta Babula
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 65, pp 102-113; https://doi.org/10.15611/pn.2021.2.07

Adam Płachciak, Sabina Zaremba-Warnke
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 65, pp 114-126; https://doi.org/10.15611/pn.2021.2.08

Aneta Ewa Waszkiewicz
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 64, pp 97-108; https://doi.org/10.15611/pn.2020.2.08

Joanna Perzyńska
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 64, pp 100-118; https://doi.org/10.15611/pn.2020.9.08

Abstract:
The author presents the possibilities of using artificial neural networks in a multidimensional analysis – cluster analysis. The empirical example using districts of the Zachodniopomorskie (West Pomeranian) Voivodeship is the illustration of theoretical considerations. The study used statistical data from many areas related to socio-economic development: demography, labour market, natural environment, recreation, culture, social and technical infrastructure, and the economy. The aim of the study was to divide the voivodeship into disjointed typological groups of districts using Kohonen networks (Self-Organizing Maps). Several networks differing in structure of the output layer were constructed and trained. Selected diagnostic features of socio-economic development of districts were their input values. Using verified Kohonen networks, various sets of groups of the researched objects were created, and confirmed them are a useful tool for identifying clusters of districts similar to each other in terms of the level of socio-economic development.
Barbara Kryk
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 64, pp 71-86; https://doi.org/10.15611/pn.2020.9.06

Abstract:
There is huge controversy around the issue of the impact of the 500+ benefit program on the labour market in Poland, especially on the professional activity of women. The effects in this area are not only relevant for the country but also for the European Union as a whole, as they determine the achievement of the employment goal of the Europe 2020 strategy. It was, therefore, decided to examine this issue more closely. The main goal of the article is to investigate how the 500+ benefit affects the supply of female labour force and the achievement of the employment target of the Europe 2020 strategy. The specific objectives: (1) what were the goals of the Polish government in the area of the labour market at the beginning of the implementation of the EU strategy, and what goals are currently in the Strategy for Responsible Development (SOR)? (2) what were the dynamics of female labour supply compared to the changes in the labour market ? (3) what is the significance of the 500+ program for the trends in the labour market ? (4) what loss (if any) for the economy resulted from the reduction of women’s employment generated? The subject of the study is women’s labour supply/employment, and the subject of research is the Polish economy. To achieve the study goals, the desk research method, time series and indicator analysis, and GDP gaps were used. The research period is 2010-2019, with particular emphasis on the period after the introduction of the benefit in 2016. The research conducted shows that adverse changes in the labour force supply of women caused by the 500+ benefits, were offset by the return to the labour market of previously unemployed or inactive people. Thus, the strategic goal related to employment was achieved.
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 64, pp 60-73; https://doi.org/10.15611/pn.2020.7.05

Abstract:
The increasing use of advanced technologies by enterprises increases the importance of the advanced technology sector in national economies. For this reason, the purpose of the research presented in the study was to determine the competitive potential of the advanced technology sector on the intra-EU market in recent years. The evaluation was conducted using the labour productivity index, labour costs and the share of the number of high technology sector enterprises in the total number of enterprises in the EU sector. Based on partial indicators, a synthetic indicator was built which allowed for the precise determination of the potential of each of the countries studied. Enterprises in countries with a strong and stable economy have higher potential, are more developed and more easily tackle the new challenges that occur in the economy. Enterprises with low competitive potential are located primarily in smaller countries with smaller support possibilities. The decisive factor was, above all, the high productivity of work.
Maciej Oesterreich
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 64, pp 102-117; https://doi.org/10.15611/pn.2020.7.08

Abstract:
The article analyses the level of propensity to use the Internet in 28 countries of the European Union in 2010 and 2019 and assesses its dynamics of changes in this period. For this purpose, information available in the databases of Eurostat and the World Bank regarding the ways in which the Internet was used by citizens and households. The study omitted issues related to the commercial use of the Internet potential by enterprises. For individual years, taxonomic synthetic measures were constructed based on a set of diagnostic features, using the TOPSIS method. These measures determine, respectively: the level of willingness to use the network by citizens and households of individual EU countries as well as the rate of changes in the analysed period. The research shows that the highest propensity to use the Internet was characteristic of citizens of Northern European countries and the lowest was in Southern Europe. The R environment and the Statistica package were used for the calculations.
Cyryl Kotyla
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu, Volume 64, pp 143-159; https://doi.org/10.15611/pn.2020.1.12

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