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  1.  

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    $a DANUBE $e Law, Economics and Social Issues Review $v Vol. 9, no. 2 (2018)
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    $a E-procurement as the ICT innovation in the public services management: case of Slovakia $f Mária Murray Svidroňová, Tomáš Mikuš
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    $1 001 umb_un_cat*0297178 $1 011 $a 1535-0118 $1 200 1 $a Journal of Public Procurement $v Vol. 15, no. 3 (2015), pp. 317-340 $1 210 $a Bingley $c Emerald Group Publishing $d 2015
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    $a Methodology of industry statistics: averages, quartiles, and responses to atypical values $f Martin Boďa, Vladimír Úradníček
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    $a The paper notices troublesome aspects of compiling industry statistics for the purpose of inter-enterprise comparison in corporate financial analysis. Whilst making a caveat that this issue is unbeknownst to practitioners and underrated by theorists, the goal of the paper is two-fold. For one thing, the paper demonstrates that financial ratios are inclined to frequency distributions characteristic of power-law (fat) tails and their typical shape precludes a simple treatment. For the other, the paper explores different approaches to compiling industry statistics by considering trimming and winsorizing cleansing protocols, and by confronting trimmed, winsorized as well as quantile measures of central tendency. The issues are empirically illustrated on data for a great number of Slovak construction enterprises for two years, 2009 and 2018. The empirical distribution of eight financial ratios is studied for troublesome features such as asymmetry and power-law (fat) tails that hamper usefulness of traditional descriptive measures of location without considering different possibilities of handling atypical values (such as infinite and outlying values). The confrontation of diverse approaches suggests a plausible route to compiling industry statistics that consists in reporting a 25% trimmed mean alongside 25% and 75% quantiles, all applied to trimmed data (i.e. data after discarding infinite values). The paper also highlights the sorely unnoticed fact that the key ratio of financial analysis, return on equity, may easily attain non-sense values and these should be removed prior to compiling financial analysis; otherwise, industry statistics is biased upward regardless of what measure of central tendency is made use of.
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    $a Was there a significant difference in sleep shifts in the high school population due to the COVID-19 pandemic depending on chronotype? A nationwide cross-sectional study $f Pavol Pivovarniček, Ľudmila Jančoková ... [et al.]
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    $a The aim of this study was to detect whether the COVID-19 pandemic has caused changes in the sleep cycle (subjective sleep shifts) of high school students divided into a sample of young women – W (n = 1999, age = 17.65 ± 2.39 y) and young men – M (n = 1094, age = 17.49 ± 1.74 y) in Slovakia depending on circadian preference in comparison with the term before COVID-19. The present cross-sectional study employed a self-reported standardized questionnaire (Morningness-Eveningness Questionnaire) to study circadian preference, which was complemented by a question focused on subjective sleep shifts before and during the pandemic. The results revealed significant strong dependence between circadian preference and subjective sleep shift in both W (χ2(8) = 153.1, p < .01, Cramer’s V = .20, p < .01) and M (χ2(8) = 98.3, p < .01, Cramer’s V =.21, p < .01). The delay of the sleep cycle has mainly become apparent in the case of definite evening types (W: 75.7%; M: 71.8%) and moderate evening types (W: 83.1%; M: 70.3%). The delay also prevailed in the intermediate types (W: 61.9%; M: 53.8%). Subjective sleep shifts were not confirmed (W: 93.8%; M: 35.3%) in the definite morning type. The sleep cycle was changed to earlier hours of definite morning types (W: 6.3%; M: 52.9%). It is necessary to focus on definite and moderate evening types and regulate the unsuitable state to time shift of the sleep cycle.
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