Abstract:Composite indicators as a tool for a ranking become more and more popular, because they illustrate a comprehensive view on a phenomenon that cannot be captured by only one single indicator. Indicators for Europe 2020 are set of indicators used for monitoring targets defi ned by the European Commission in the Strategy of Smart, Sustainable and Inclusive Growth. The main objective of this paper is the comparison of performance of the EU Member States using the composite indicator principles. Within constructing composite indicators several steps have to be made and corresponding methods have to be chosen. There is not only one correct method how to develop a composite indicator. Of course, the choice of the methods manipulates the results. Primarily, normalisation methods, weighting schemes and aggregation formulas are fundamental but very subjective. This paper deals with two types of normalisation (z-score and min-max) and four weighting and aggregation schemes (equal weighting with linear aggregation, principal components analysis, benefi t of doubt method and multi-criteria analysis). European countries ranking is provided according to the seven different scenarios.
The aim of the paper is to provide a ranking of the Czech NUTS 3 regions based onsustainable development indicators. The original list of indicators was published by theCzech Statistical Office in 2008 and reviewedin 2010. In the analysis the same set ofindicators with the latest data was used. The indicators in each pillar are merged by meansof linear aggregation withweights derived from the principal component analysis.Because three pillars of sustainable development (environmental, economic and social)are assumed to be non-compensable, the multiple-criteria decision analysis is applied on apillar level in the final composite indicator. Both two main approaches – Borda andCondorcet were considered. Since the Borda approach leads to the compensability of theindicators, the Condorcet approach was in the spotlight. Advancedrules and adjustmentfor Condorcet approach were employed. Advantages and disadvantages of the methodsare provided. As a result more final rankings exist. The deep discussion about the resultsis provided. The special attention is paid to the capital city Prague, border regions, andindustrial regions. In addition, the correlation between final ranking and other indicatorsis tested.
Evropská komise defi novala novou desetiletou strategii, jež má následovat lisabonskou strategii. Nová strategie se nazývá Strategie pro inteligentní a udržitelný růst podporující začlenění (European Commission 2010b) a defi nuje směr, kterým se mají evropské státy ubírat a cíle, jež mají být dosaženy do roku 2020. Bylo stanoveno pět hlavních cílů:
Measuring of sustainable development seems to be a great issue as there is neither unified set of indicators nor any preferred methodology how to do it. However, attempts to evaluate entities from the point of view of sustainable development regularly occur. The most problematic level according to sustainable development assessment seems to be "lower" regional level, such as LAU 1 (former NUTS 4) level. On one hand there are usually at this level already serious problems with data availability, on the other hand it is almost impossible to regularly perform detailed questionnaire surveys in all LAU 1 regions (77 districts in case of the Czech Republic), as it is done e.g. in cities. The aim of the paper is to decide, how to assess sustainability at this level. Finally we chose useful indicators, though different from indicators used at the national or NUTS 3 level, with data available for all LAU 1 regions. We succeeded in filling all three pillars of sustainable development (economic, social and environmental) with sufficient number of suitable indicators. In the first step we applied cluster analysis to find coherences among regions that are e.g. affected by similar problems. After that we constructed composite indicators in order to create ranking of all 77 districts. Ranking was derived from composite indicator approach. We constructed 10 composite indicators to test different methods of normalisation, weighting and aggregation. The results show the ranking of LAU 1 regions in the Czech Republic from the sustainability point of view, both including and excluding capital city of Prague as an outlying district. A good interconnection between cluster analysis and constructed composite indicators can be seen, which is supported by the discussion of the results.
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