Proposal for a Dynamic Composite Indicator: Application in a Comparative Analysis of Trends in the EU Member States Towards the Europe 2020 Strategy

Landaluce-Calvo, M. Isabel; Gozalo-Delgado, Mariola

doi:10.1007/s11205-020-02547-w

Cited by 6 publications

(8 citation statements)

References 16 publications

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“…This approach allows presenting the ranking of the analysed countries based on the aggregate measure value of all the indicators (diagnostic features) illustrating the implementation level of the individual priorities as well as the EU and national targets of the Europe 2020 Strategy. This approach is presented in the studies by, e.g., [5][6][7][8][9][10][11][12][13][14][15]; • aggregate approach taking into account the EU-level targets, in which national values of the individual monitoring indicators are referred to their target values defined for the European Union (EU-level targets 2020). Following this approach, achieving more favourable monitoring indicators by a given country than the EU-level targets 2020 is not included in the analysis (values that are more favourable for the national monitoring indicators are replaced with their target values set out for the entire European Union).…”

Section: The Purpose Of the Papermentioning

confidence: 99%

“…The application of aggregate measures in assessing the level of the Europe 2020 Strategy implementation is presented, i.e., in the studies by [5][6][7][8][9][10][11][12][13][14][15].…”

Section: Literature Reviewmentioning

confidence: 99%

“…A dynamic approach based on the exploratory factor analysis and clustering technique was proposed by Landaluce-Calvo i Gozalo-Delgado [15]. It focuses on the construction of the composite (synthetic) indicators merging both the spatial and the time dimension of the data.…”

Section: Literature Reviewmentioning

confidence: 99%

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Assessment of the Europe 2020 Strategy: A Multidimensional Indicator Analysis via Dynamic Relative Taxonomy

2021

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Since 2010, the European Union countries have been implementing the objectives of the Europe 2020 Strategy aimed at smart, sustainable, and inclusive growth. The Strategy formulates nine indicators that are systematically monitored and assessed. Not all the indicators of the Europe 2020 Strategy could be used in the analysis in a direct way. Due to the limited availability and comparability of statistical data, this problem is presented in detail in part 2 of the article. The assessment of the achievement level of the Europe 2020 Strategy targets, both at the level of the entire European Union (the EU-level targets approach) and its individual Member States (the national-level targets approach) is the primary research purpose of the study. The composite index proposed and constructed on the basis of a dynamic relative taxonomy was used in the conducted research to present the diversified distance of the individual European Union countries in relation to the EU-level targets as well as the national-level targets of the Europe 2020 Strategy. The research methodology allows conducting the analysis taking into account the missing data. Most methods of ordering objects based on aggregate measures are compensatory in nature. This problem was significantly reduced by taking into account the geometric mean in the construction of the aggregate measure. The research findings revealed that in the years 2010–2019 an ongoing improvement in the implementation of both the EU and the national targets of the Europe 2020 Strategy was observed. In addition, the differences existing between the European Union Member States were reduced. However, none of the countries achieved the EU-level targets. Their highest implementation level was recorded in Denmark, Sweden, Austria, and Finland. The achievement level of the strategic goals regarding the national-level targets was influenced by the choice of one of the two approaches indicated in the study and adopted by the individual EU Member States in determining the set target values of the indicators, i.e., either prudential or optimistic.

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Section: The Purpose Of the Papermentioning

confidence: 99%

“…The application of aggregate measures in assessing the level of the Europe 2020 Strategy implementation is presented, i.e., in the studies by [5][6][7][8][9][10][11][12][13][14][15].…”

Section: Literature Reviewmentioning

confidence: 99%

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Assessment of the Europe 2020 Strategy: A Multidimensional Indicator Analysis via Dynamic Relative Taxonomy

2021

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“…There have been a number of publications on Europe 2020 strategy in the last few years. In many publications, the authors suggest comparable composite indicators to assess the performance of the Member States with respect to implementation of the goals described by the Europe 2020 strategy-see, for example, [2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Research methods most often used in articles are as follows: statistical methods [2,9,14,15,17,19,20], multiple-criteria decision making [4,8,10,11], the DEA (data envelopment analysis) method [3,18], and fuzzy goal programming [7].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Europe 2020 Strategy Implementation Using Interval Entropy and Cluster Analysis for Interrelation between Two Groups of Headline Indicators

Kosareva

Krylovas

2021

Entropy

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The research analyzes the progress of Member States in the implementation of Europe 2020 strategy targets and goals in 2016–2018. Multiple criteria decision-making approaches applied for this task. The set of headline indicators was divided into two logically explained groups. Interval entropy is proposed as an effective tool to make prioritization of headline indicators in separate groups. The sensitivity of the interval entropy is its advantage over classical entropy. Indicator weights were calculated by applying the WEBIRA (weight-balancing indicator ranks accordance) method. The WEBIRA method allows the best harmonization of ranking results according to different criteria groups—this is its advantage over other multiple-criteria methods. Final assessing and ranking of the 28 European Union countries (EU-28) was implemented through the -cut approach. A -means clustering procedure was applied to the EU-28 countries by summarizing the ranking results in 2016–2018. Investigation revealed the countries–leaders and countries–outsiders of the Europe 2020 strategy implementation process. It turned out that Sweden, Finland, Denmark, and Austria during the three-year period were the countries that exhibited the greatest progress according to two headline indicator groups’ interrelation. Cluster analysis results are mainly consistent with the EU-28 countries’ categorizations set by other authors.

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Towards an Impartial Evaluation of Cities’ Smartness: A Multivariate Statistical Approach

Uskoković

Maričić

Jeremić

2022

Marketing and Smart Technologies

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Proposal for a Dynamic Composite Indicator: Application in a Comparative Analysis of Trends in the EU Member States Towards the Europe 2020 Strategy

Cited by 6 publications

References 16 publications

Assessment of the Europe 2020 Strategy: A Multidimensional Indicator Analysis via Dynamic Relative Taxonomy

Assessment of the Europe 2020 Strategy: A Multidimensional Indicator Analysis via Dynamic Relative Taxonomy

Assessing the Europe 2020 Strategy Implementation Using Interval Entropy and Cluster Analysis for Interrelation between Two Groups of Headline Indicators

Towards an Impartial Evaluation of Cities’ Smartness: A Multivariate Statistical Approach

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