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Statements

Subject Item
n2:RIV%2F61989100%3A27510%2F14%3A86090724%21RIV15-MSM-27510___
rdf:type
skos:Concept n20:Vysledek
rdfs:seeAlso
http://is.muni.cz/do/econ/soubory/katedry/kres/4884317/48596005/004_2014.pdf
dcterms:description
The paper deals with the problem of searching the efficient frontier and group of similar units using two methods – multivariate Cluster Analysis and multicriteria Data Envelopment Analysis. The main aim of the paper is to propose the way how to choose an optimal number of groups coming to empirical analysis. Firstly it´s necessary to find the closest characteristics for a given unit according to a previously specified criterion of similarity. After fulfilment this criterion and creating optimal groups of similar units, it´s possible to evaluate level of efficiency of homogenous NUTS 2 regions within “new” EU Member States based on Regional Competitiveness Index approach; efficiency is thus seen as a mirror of competitiveness. The idea laying behind this approach is that inefficient regions can learn more easily from those, that are more similar; and closer similarity may show for the inefficient regions how to achieve the improvement with less effort. The paper deals with the problem of searching the efficient frontier and group of similar units using two methods – multivariate Cluster Analysis and multicriteria Data Envelopment Analysis. The main aim of the paper is to propose the way how to choose an optimal number of groups coming to empirical analysis. Firstly it´s necessary to find the closest characteristics for a given unit according to a previously specified criterion of similarity. After fulfilment this criterion and creating optimal groups of similar units, it´s possible to evaluate level of efficiency of homogenous NUTS 2 regions within “new” EU Member States based on Regional Competitiveness Index approach; efficiency is thus seen as a mirror of competitiveness. The idea laying behind this approach is that inefficient regions can learn more easily from those, that are more similar; and closer similarity may show for the inefficient regions how to achieve the improvement with less effort.
dcterms:title
NUTS 2 Regions Classification: Comparison of Cluster Analysis and DEA Method NUTS 2 Regions Classification: Comparison of Cluster Analysis and DEA Method
skos:prefLabel
NUTS 2 Regions Classification: Comparison of Cluster Analysis and DEA Method NUTS 2 Regions Classification: Comparison of Cluster Analysis and DEA Method
skos:notation
RIV/61989100:27510/14:86090724!RIV15-MSM-27510___
n3:aktivita
n15:S n15:P
n3:aktivity
P(EE2.3.20.0296), S
n3:dodaniDat
n4:2015
n3:domaciTvurceVysledku
n7:2625903 n7:4892356
n3:druhVysledku
n18:D
n3:duvernostUdaju
n5:S
n3:entitaPredkladatele
n23:predkladatel
n3:idSjednocenehoVysledku
33443
n3:idVysledku
RIV/61989100:27510/14:86090724
n3:jazykVysledku
n16:eng
n3:klicovaSlova
Classification, cluster, cluster analysis, DEA method, efficient frontier, NUTS 2 region, RCI
n3:klicoveSlovo
n6:cluster n6:cluster%20analysis n6:Classification n6:efficient%20frontier n6:NUTS%202%20region n6:RCI n6:DEA%20method
n3:kontrolniKodProRIV
[4594A1EB3852]
n3:mistoKonaniAkce
Hustopeče
n3:mistoVydani
Brno
n3:nazevZdroje
XVII. mezinárodní kolokvium o regionálních vědách : sborník příspěvků : Hustopeče, 18.-20. června 2014
n3:obor
n10:AH
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n17:EE2.3.20.0296
n3:rokUplatneniVysledku
n4:2014
n3:tvurceVysledku
Melecký, Lukáš Staníčková, Michaela
n3:typAkce
n14:EUR
n3:zahajeniAkce
2014-06-18+02:00
s:numberOfPages
9
n21:doi
10.5817/CZ.MUNI.P210-6840-2014-4
n13:hasPublisher
Masarykova univerzita
n19:isbn
978-80-210-6840-7
n9:organizacniJednotka
27510