Multi-Criteria Analysis as a Tool for Assessment of District Towns

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F20%3A10245874" target="_blank" >RIV/61989100:27510/20:10245874 - isvavai.cz</a>

Výsledek na webu

<a href="https://munispace.muni.cz/library/catalog/chapter/1632/149" target="_blank" >https://munispace.muni.cz/library/catalog/chapter/1632/149</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5817/CZ.MUNI.P210-9610-2020-21" target="_blank" >10.5817/CZ.MUNI.P210-9610-2020-21</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multi-Criteria Analysis as a Tool for Assessment of District Towns

Popis výsledku v původním jazyce

A technique for Order of Preference by Similarity to Ideal Solution is a multi-criteria decision analysis method used for complex assessment of a set of alternatives. It is often combined with the CV (Coefficient of Variance) method to determine the weight of these criteria to objectify achieved results. Using these methods, we have assessed a group of district towns in the Slovak Republic based on 2016 data by using six budgetary criteria, including maximizing and minimizing ones. The main contribution of this article is the complex assessment of a selected set of territorial administration entities, differences in their results and the importance of selecting the right method to determine weights, which has a significant impact on the overall results. It can be said that there were almost no differences in results among the majority of district towns, there were no significant correlations between the results and the criteria, and there were some common characteristics in the three created clusters. The analysis has confirmed that it is necessary to pay special attention to the selection of criteria and of the method used to determine their weight, as these factors have a significant impact on the overall results of analysis.

Název v anglickém jazyce

Multi-Criteria Analysis as a Tool for Assessment of District Towns

Popis výsledku anglicky

A technique for Order of Preference by Similarity to Ideal Solution is a multi-criteria decision analysis method used for complex assessment of a set of alternatives. It is often combined with the CV (Coefficient of Variance) method to determine the weight of these criteria to objectify achieved results. Using these methods, we have assessed a group of district towns in the Slovak Republic based on 2016 data by using six budgetary criteria, including maximizing and minimizing ones. The main contribution of this article is the complex assessment of a selected set of territorial administration entities, differences in their results and the importance of selecting the right method to determine weights, which has a significant impact on the overall results. It can be said that there were almost no differences in results among the majority of district towns, there were no significant correlations between the results and the criteria, and there were some common characteristics in the three created clusters. The analysis has confirmed that it is necessary to pay special attention to the selection of criteria and of the method used to determine their weight, as these factors have a significant impact on the overall results of analysis.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

XXIII. mezinárodní kolokvium o regionálních vědách : sborník příspěvků = 23rd International Colloquium on Regional Sciences : conference proceedings

ISBN

978-80-210-9610-3

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

166-172

Název nakladatele

Masarykova univerzita

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

17. 6. 2020

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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