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Article

Europe 2020 Strategy and 20/20/20 Targets: An Ex Post Assessment Across EU Member States

by
Norbert Życzyński
1,*,
Bożena Sowa
2,
Tadeusz Olejarz
1,
Alina Walenia
3,
Wiesław Lewicki
1 and
Krzysztof Gurba
4
1
Faculty of Management, Rzeszow University of Technology, al. Powstancow Warszawy 12, 35-959 Rzeszow, Poland
2
Faculty of Management, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, Poland
3
Faculty of Economics and Finance, University of Rzeszow, 2 Cwiklinskiej, 35-601 Rzeszow, Poland
4
Faculty of Social Sciences, University of the National Education Commission Krakow, ul. Podchorążych 2, 30-084 Kraków, Poland
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(20), 9030; https://doi.org/10.3390/su17209030 (registering DOI)
Submission received: 23 August 2025 / Revised: 30 September 2025 / Accepted: 4 October 2025 / Published: 12 October 2025
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Abstract

The 2020 Europe Strategy was designed as a comprehensive framework to promote smart, sustainable and inclusive growth in the European Union (EU), particularly emphasising the ‘20/20/20’ targets related to climate protection and energy policy. This study provides an ex post evaluation of the extent to which the strategy’s objectives were achieved in the member states of the EU in the period 2010–2020. The analysis is based on Eurostat data and uses Hellwig’s multidimensional comparative analysis to construct a synthetic indicator of progress. The results show that EU countries have made significant advances in reducing greenhouse gas emissions and increasing the share of renewable energy in gross final energy consumption, with Sweden and Finland identified as leaders, while Malta and Hungary lagged behind. Primary energy consumption overall decreased, although only a minority of the member states reached the planned thresholds. Progress was less evident in research and development (R&D) expenditure, where the average value of the EU remained below the 3% GDP target, and strong disparities persisted between innovation leaders and weaker performers. Improvements in higher education attainment were observed, contributing to the long-term goal of a knowledge-based economy, although labour market difficulties, especially among young people, remained unresolved. The findings suggest that, although the Strategy contributed to tangible progress in several areas, uneven achievements among member states limited its overall effectiveness. The study is limited by the reliance on aggregate statistical data and a single methodological approach. Future research should extend the analysis to longer time horizons, include qualitative assessments of national policies, and address implications for the implementation of the European Green Deal and subsequent EU development strategies.

1. Introduction

The Europe 2020 strategy was conceived as a continuation of the Lisbon Strategy launched at the beginning of the twenty-first century. Its overarching objective was to promote sustainable economic growth within the European Union (EU), defined as the ambition to establish the EU as the most competitive and dynamic knowledge-based economy in the world, capable of sustainable growth, creating more and better jobs, and ensuring greater social cohesion [1,2,3,4,5]. The priorities of the Strategy were shaped by the specific conditions prevailing in the member states, notably the long-term challenges of globalisation, population ageing, and the need for a more rational use of natural resources. As in the Lisbon Strategy, the central aim was to enhance the competitiveness of both individual member states and the EU as a whole, measured by GDP per capita, with particular emphasis on the sustainability of this process. By 2020, the strategy was expected to deliver a knowledge-based and low-carbon economy, foster environmentally friendly production technologies, improve resource efficiency, and create new ‘green’ jobs, while maintaining economic, social and territorial cohesion.
The key assumptions of the Strategy included reducing unemployment and poverty, facilitating the transition to a low-carbon economy, and strengthening the overall competitiveness of the EU economy. The Europe 2020 strategy was also intended to address shortcomings of the previous European growth model by creating conditions for sustainable economic development that promoted social inclusion [6,7]. Within this framework, three mutually reinforcing priorities were established: (i) smart growth, understood as development based on knowledge and innovation; (ii) sustainable growth, defined as the development of a low-carbon economy with efficient resource use; and (iii) inclusive growth, understood as development based on high employment, combined with economic, social, and territorial cohesion. A further priority of the EU was to mitigate the negative impacts of economic activity on the natural environment by adopting policies aimed at reducing greenhouse gas emissions, promoting the sustainable use of energy and encouraging renewable energy sources [8,9,10]. The EU aspired to establish itself as a leader in environmental technologies and in the protection of natural resources. These objectives, commonly referred to as the ‘20-20-20’ targets, were defined as follows: a 20% reduction in greenhouse gas emissions compared to 1990 levels; an increase in the share of renewable energy in total energy consumption to 20%; and a 20% improvement in energy efficiency by 2020.
The intended outcome of the Strategy was the development of a knowledge-based, low-emission economy that promoted environmentally friendly technologies, efficient resource use, and the creation of green jobs while ensuring social cohesion. Collective action across all member states was expected to contribute to the achievement of EU-wide goals, including strengthening the global position. Importantly, these objectives could only be achieved through coordinated action from EU institutions, member states, regional and local authorities, socioeconomic partners and civil society. Implementation at the EU level required the participation of all institutions, while at the national level it depended on the commitment of governments and local stakeholders. Civil society actors also played a crucial role [11,12,13].
Previous research has examined various aspects of the Europe 2020 strategy and its relationship to sustainable development. Balcerzak [13,14] and Dziembała [15] analysed social cohesion and modernisation processes in the EU, highlighting persistent regional disparities. Gasz [16] and Domańska [17] focused on the assumptions of the policy and the early expectations of implementation, while Jasiński [18] discussed strategic continuity with the Lisbon strategy. More recent contributions [19,20] provided comparative evaluations of competitiveness and socioeconomic development between EU member states, highlighting the uneven pace of progress. At the international level, several studies [6,21] placed the strategy within broader debates on competitiveness, the ‘Beyond GDP’ agenda, and the Sustainable Development Goals (SDG).
In these studies, a variety of methodological approaches have been applied, ranging from linear ordering methods used to measure social cohesion [13,14] and socioeconomic modernisation analyses [15] to descriptive and policy-orientated evaluations of the strategy [16,17] and macroeconomic comparisons of competitiveness between member states [18,19,20]. Despite their contributions, these works share certain limitations, because most addressed only selected years or partial policy dimensions such as employment, cohesion, or competitiveness. Additionally, many relied on descriptive statistics or single indicators without integrating multiple objectives into a comprehensive framework. As a result, synthetic comparative measures covering the full implementation horizon of 2010–2020 in all EU member states remain largely absent, underscoring the relevance of the present study.
Against this background, the importance of this research lies in its potential to provide lessons for future EU-level strategies. The findings contribute to the reference value by identifying structural disparities between member states and offering practical guidance for the design of forthcoming frameworks, such as the European Green Deal. Moreover, uniform EU-level targets do not sufficiently reflect national specificities in resource availability, institutional capacity, and socioeconomic conditions, which creates a need for more differentiated approaches.
The present study addresses these gaps in three ways. First, it applies Hellwig’s multidimensional comparative analysis, a method rarely used in this field, to construct a composite indicator of progress. Second, it covers the entire implementation horizon (2010–2020) and all EU member states, providing a systematic and comparable assessment. Third, it generates innovative findings by identifying structural reasons why certain countries consistently outperformed others (e.g., Sweden and Finland), while some lagged (e.g., Malta and Hungary). These results contribute both to the academic literature on EU development strategies and to the policy debate on how to design more differentiated and flexible frameworks for the future.
Given these conditions, the central research problem is to evaluate the extent to which the Europe Strategy achieved its climate protection and energy objectives, commonly referred to as ‘20/20/20’ goals, including the possibility of extending emission reduction targets under favourable conditions. The specific purpose of this article is to assess the degree of achievement of these climate and energy objectives, together with research and development (R&D) expenditure, across individual EU member states. Progress is measured using four indicators—R&D expenditure as a percentage of GDP, greenhouse gas emissions (index with 1990 as the base year), the share of renewable energy in gross final energy consumption and the energy intensity of the economy (approximated as final energy consumption expressed in kilogrammes of oil equivalent relative to GDP at constant prices in millions of euros).
The novelty of this study lies in two main aspects. First, it applies Hellwig’s multidimensional comparative analysis to evaluate progress towards the Europe 2020 targets, a method rarely applied in the context of sustainability and evaluation of EU policies. Unlike single-indicator or purely descriptive approaches, the synthetic indicator derived from Hellwig’s method enables a holistic ranking of EU member states by simultaneously capturing multiple dimensions of progress. Second, the study offers an ex post evaluation covering the entire implementation period of the Europe 2020 Strategy across all EU member states. Whereas most existing contributions have focused on selected years, specific policy dimensions, or a subset of countries, this approach allows for a systematic comparison of achievements and disparities across the Union. By combining methodological innovation with comprehensive coverage, the paper contributes both to the literature on sustainable development monitoring and to the policy debate on the effectiveness of EU strategies.
The main contributions of this study can be summarised as follows:
  • Methodological contribution: the use of Hellwig’s multidimensional comparative analysis to construct a composite indicator, allowing a holistic assessment of progress;
  • Scope of analysis: coverage of the full implementation horizon (2010–2020) across all 27 EU member states, offering the first comprehensive ex post assessment of the strategy’s climate, energy, and R&D goals;
  • Empirical insights: identification of leaders (Sweden, Finland) and laggards (Malta, Hungary), with an explanation of the structural drivers of these disparities, including resource endowments, innovation capacity, and institutional frameworks;
  • Policy relevance: linkage of empirical results to the debate on the European Green Deal, emphasising the need for more differentiated pathways in future EU development strategies.

2. Materials and Methods

The empirical material used in the study was based on 27 EU member states, while the numerical data was sourced from Eurostat. The temporal scope of the investigation covered the years 2010–2020, corresponding to the implementation period of the Europe 2020 strategy. A comparative analysis of indicators was carried out that defines the degree of implementation of the 2020 Europe strategy in EU countries for the years 2010–2020 using Hellwig’s multidimensional comparative analysis [14,22,23]. Hellwig’s development pattern method [24] is a classical taxonomic approach used to construct composite indicators. It defines an “ideal” reference object based on the values of the most favourable indicators. The distance of each country from this ideal is calculated using the Euclidean formula and then normalised to obtain a synthetic score ranging from 0 to 1. Higher values indicate closer similarity to the reference object and thus better performance. This procedure allows multiple indicators to be aggregated into a single measure, enabling cross-country comparison and ranking. The analysis used the classical version of this method, while the synthetic indicator of the implementation of the Europe 2020 strategy was determined on the basis of detailed indicators established by the European Commission to monitor the assumptions of the Strategy. In the classical version of Hellwig’s method, all variables are assigned equal weights. This approach was intentionally applied here to maintain methodological transparency and ensure comparability with other studies using the same framework. It also reflects the structure of the Europe 2020 Strategy, which presented its climate and energy goals as formally equivalent. While we recognise that objective weighting techniques (e.g., entropy, PCA, AHP) may offer valuable insights, such methodological extensions go beyond the scope of this paper. Future research could apply these approaches to complement the present results. Based on synthetic indicators for 2010 and 2020, a ranking of EU countries was created, reflecting the degree of realisation of the Europe 2020 strategy. The decision to compare 2010 and 2020 comes directly from the design of the Europe 2020 strategy. The strategy was officially launched in 2010, which constitutes the baseline year, and its goals were explicitly set for 2020. Intermediate benchmarks were not defined in the official framework, including for the ‘20/20/20’ objectives analysed in this study. For this reason, 2010 and 2020 are treated as the two reference points that allow for a systematic assessment of the implementation horizon. Although Eurostat publishes annual data, presenting all intermediate years would not correspond to the formal evaluation logic of the strategy and could dilute the clarity of the analysis. The synthetic measures calculated using Hellwig’s method made it possible to develop a ranking of countries that by 2020, i.e., at the end of the implementation of the strategy, had achieved the best, average and worst positions in terms of indicators of the long-term development programme. The study using Hellwig’s method was based on Eurostat data published for the years 2010–2020. Although the Europe 2020 Strategy as a whole was monitored by ten official indicators in five overarching goals (employment, R&D, climate and energy, education and poverty reduction), this study deliberately narrows the empirical analysis to four indicators directly related to the “objectives “20/20/20”” in climate and energy, complemented by R&D expenditure. This focus reflects the intention of evaluating the sustainability and innovation dimensions of the Strategy in detail, which constitute its most critical long-term components. However, the social and labour market objectives (employment, education and poverty reduction) are recognised and discussed descriptively in the Results section, but were not incorporated into the synthetic indicator to maintain methodological consistency and avoid diluting the analysis.
The degree of implementation of the Europe 2020 Strategy, which defines the level of social cohesion in individual countries according to the assumptions of the Strategy, is monitored based on ten detailed diagnostic indicators relating to research and development activities, climate protection and energy objectives set out in the individual targets. Target 1 assumed that 75% of the population aged 20 to 64 years should be employed, measured by the employment rate of people aged 20 to 64 years (% share of the population). Target 2 assumed that 3% of European GDP should be invested in research and development, measured by the share of R&D expenditure in GDP. Target 3 included climate protection and energy objectives (“20/20/20”, also covering the possibility of increasing the reduction target under favourable conditions), measured by greenhouse gas emissions (index with 1990 as the base year), the share of renewable energy in gross final energy consumption, and the energy intensity of the economy (an approximate measure of energy savings, estimated as final energy consumption expressed in kilogrammes of oil equivalent relative to GDP at constant prices in millions of euros). Target 4 assumed a high level of education, where the share of people with low education should be below 10% and at least 40% of people aged 30 to 34 years should have higher education or its equivalent, measured by the share of people with low education (% of the population aged 18 to 24 with only primary or vocational education) and the share of people with higher education (% of the population aged 30 to 34 years). Target 5 was poverty reduction, aiming to lift at least 20 million people out of poverty or social exclusion, measured by the percentage of the population at risk of poverty or social exclusion, the share of the population living in households with very low work intensity, and the severe material deprivation rate expressed as a percentage.
To evaluate the degree to which the climate protection and energy objectives (“20/20/20”) were achieved, four indicators were selected: R&D expenditure as a percentage of GDP, greenhouse gas emissions (index with 1990 as the base year), the share of renewable energy in gross final energy consumption, and the energy intensity of the economy (an approximate measure of energy savings, estimated as final energy consumption expressed in kilogrammes of equivalent oil relative to GDP at constant prices in millions of euros).

3. Results and Discussion

3.1. Overview of Strategic Objectives and Indicators

In implementing the assumptions of the Europe 2020 Strategy, the EU member states aimed to reduce greenhouse gas emissions by 20% (or even 30% compared to the 1990 level), while simultaneously increasing energy efficiency by 20% and the share of energy consumed from renewable sources by 20%. The goal of reducing primary energy consumption was achieved, among other things, through systematic improvement of the energy efficiency of production and energy use processes [25,26,27]. Progress in the implementation of the Europe 2020 Strategy was monitored on the basis of a set of indicators assigned to specific development objectives, which were expected to be achieved in 2020 at the EU level (Table 1).

3.2. Comparative Analysis of Member States’ Performance (Hellwig Method Results)

Evaluation of the implementation of the “20/20/20” targets and R&D expenditures, calculated using the Hellwig method, revealed the following value ranges across EU countries between 2010 and 2020:
  • X1—R&D expenditure as % of GDP;
  • X2—GHG emissions index (1990 = 100);
  • X3—Share of renewable energy in total gross energy consumption (%);
  • X4—Primary energy consumption per 100,000 inhabitants (Mtoe).
Table 2 shows the values of these diagnostic variables in 2010 and 2020, highlighting substantial variation between the member states. Eurostat data for 2010–2020 indicate a gradual improvement in most cases, although the pace and stability of progress varied considerably between indicators, reflecting differences in energy mixes, innovation systems, and institutional capacities. For the purposes of this publication, the boundary years 2010 and 2020 were selected to illustrate the extent of change over the full implementation horizon of the Europe 2020 Strategy. For example, Finland consistently recorded high R&D expenditure, whereas Cyprus registered the highest GHG emission index in 2020. Table 2 presents the values of the diagnostic indicators (X1–X4) for 2010 and 2020, corresponding to the baseline and target years of the Europe 2020 Strategy. Intermediate calculations were not included, as the Strategy defined only starting and final benchmarks, and the synthetic indices derived from Hellwig’s method are conceptually meaningful only for the boundary years.
Although descriptive results provide a clear overview of differences among EU member states, further interpretation highlights several structural drivers of these disparities. For example, the consistently high R&D expenditure in Finland, Sweden, and Germany reflects not only their advanced innovation systems but also the strong institutional frameworks supporting research–industry cooperation. In contrast, countries such as Romania and Bulgaria remain constrained by lower levels of investment and weaker innovation ecosystems, which limit their ability to contribute to the EU’s 3% R&D target.
In terms of greenhouse gas emissions, the results suggest that the reductions were more substantial in countries with diversified energy mixes and strong regulatory measures (e.g., Denmark, Estonia), while progress was limited in countries with greater dependence on fossil fuels (e.g., Poland, Greece). This indicates that structural factors such as energy dependency and historical reliance on coal significantly influenced the trajectory of emissions reduction.
The renewable energy indicator shows that the leadership of Sweden and Finland is based on long-standing commitments to bioenergy and hydropower, while the weak performance of Malta and Hungary points to geographic and infrastructure constraints. Importantly, the disparities suggest that common EU targets, while effective in driving progress, do not sufficiently account for national specificities in resource availability, institutional capacity, and socio-economic conditions.
These findings highlight the uneven effectiveness of the Europe 2020 Strategy in the Union. The results not only confirm the general direction of progress, but also underscore the persistence of structural divides between innovation leaders and lagging countries. Such insights contribute to understanding the limitations of uniform EU-level targets and provide valuable lessons for the design of future frameworks such as the European Green Deal, which may require more differentiated and flexible implementation mechanisms.

3.3. Research and Development (R&D) Expenditure

A major challenge for the EU is the need to take action aimed at increasing innovation and the intensity of research and development activities [28,29]. Innovation in companies is also a stimulating factor in building competitive advantages and supporting the competitiveness of the economy [30,31,32]. In 2020, R&D expenditure as a percentage of GDP ranged from 0.47% in Romania to 3.52% in Belgium. The overarching objective of the Strategy, which amounts to 3% of GDP, was achieved by 6 of the 27 member states, namely Belgium, Sweden, Denmark, Austria, Finland, and Germany. The average level of R&D expenditure in the EU countries was approximately 1.5% of GDP, a level not reached by 15 Member States. In Poland, R&D expenditures represented 1.39% of GDP (15th place in the EU). EU countries are characterised by a high degree of differentiation in terms of R&D expenditure. For the EU as a whole, R&D expenditure followed a steady upward trend, rising from 1.97% of GDP in 2010, 2.12% in 2015, to 2.32% in 2020. This gradual increase confirms that the final value in 2020 reflected a consistent process rather than a sudden change (Figure 1).
In 2010, there was a relatively large group of countries (10) where the level of R&D spending did not exceed 1% of GDP. In the same year, relatively high spending was observed in Finland (3.71% of GDP), Sweden (3.17% of GDP) Germany (2.73% of GDP), and France (2.18% of GDP). In 2010, 14 member states did not reach the average EU indicator of 1.5% of GDP. In 2020, the number of European countries where an increase in R&D spending was observed grew. In 2010, only Finland (3.71% of GDP) and Sweden (3.17% of GDP) achieved the 3% level of R&D spending set by the Strategy. By 2020, the 3% target was met in Sweden (3.51%), Germany (3.14%), Denmark (3.03%), Belgium (3.52%) and Austria (3.22%).
In 2020, EU countries remained strongly polarised in terms of R&D expenditure, which is largely linked to differences in the structures of their economies. Alongside innovation leaders, there was a significant group of countries where spending on this purpose was less than 1% of GDP (Bulgaria, Cyprus, Latvia, Malta, Romania and Slovakia) or hovered around 1.5% of GDP (Portugal, Luxembourg, Spain, Italy, and Hungary). By comparing 2010 and 2020, it can be observed that in most EU member states, R&D expenditure increased, although the pace of this growth, with the exception of Greece (0.60% of GDP in 2010 and 1.49% in 2020), was not particularly impressive. A decline in spending in this area was recorded in 2020 compared to 2010 in Luxembourg, Finland, and Ireland [30].
According to Eurostat data, R&D expenditure in the EU increased steadily during the implementation period of the Strategy: from 1.97% of GDP in 2010, to 2.12% in 2015, and 2.32% in 2020. This indicates that the final 2020 value was not an abrupt outcome but the result of a gradual upward trajectory. Nevertheless, large disparities persisted, with Belgium, Sweden, and Germany surpassing the 3% target, while countries such as Romania and Bulgaria remained below 1%. This uneven progress reflects structural barriers in national innovation systems, which limited the collective ability of the EU to reach the headline R&D target [33,34].
Building innovation awareness among European enterprises, introducing incentive systems aimed at increasing business participation in financing R&D expenditure and information technologies, while at the same time reducing previous spending on nontechnological innovations (including training, design, and marketing), is of key importance. In the global economy, competitiveness based on products created through the use of new technologies should be of particular importance, in addition to relatively low labour costs [28,29,35]. The ability to withstand global competition from other regions of the world (USA, Japan, India, China) requires greater public and private funding (both from the EU budget and from individual Member States) for scientific research, particularly applied and developmental, to advance new technologies and renewable energy sources [17,36,37,38,39].

3.4. Trends in Greenhouse Gas Emissions

In the Europe 2020 strategy, the target was set to reduce greenhouse gas emissions by 20% between 1990 and 2018. In 2018, all EU member states together managed to reduce emissions by 11.3%, which represented more than half of the planned change. The reduction in greenhouse gas emissions released into the atmosphere was due to many factors, including, among others, the increase in coal prices (which, together with the fall in gas prices, prompted producers of heat and electricity to substitute fuels), the economic crisis, which led to reduced emissions from industry, transport and construction, as well as the increase in fuel prices, which in the transport sector translated into a significant reduction in their consumption [15,40,41]. In 2010, greenhouse gas emissions were 14% lower compared to 1990, and between 2010 and 2018 they fell by another 2.5%. The largest relative reduction in emissions was recorded in countries with a low or medium share in the total volume of greenhouse gas emissions (13% in Cyprus and 8% in Belgium, Finland and Denmark). In nine member states, emissions increased, including Bulgaria, Lithuania, and Romania, although since 1990 these countries have significantly reduced their overall emissions (Figure 2).
Estonia reported a very favourable situation in terms of greenhouse gas emissions, achieving the lowest indicator value. In total, 20 EU countries recorded lower emissions compared to the base period (1990), including Poland with a dynamic index of 83.32 (12th in the EU) [42], while in eight countries (Austria, Slovenia, Ireland, Greece, Portugal, Spain, Malta and Cyprus) emissions in 2010 were higher than in 1990, with the worst situation in Cyprus (almost 63% above the 1990 level). The Europe 2020 strategy assumed a reduction of 20% between 1990 and 2020, and by 2010 the EU as a whole had achieved an 11.3% decrease, representing more than half of the planned change. In the following years (2010–2018), the reduction was driven by factors such as rising coal prices (encouraging substitution), falling gas prices, the economic crisis that lowered emissions in industry, transport and construction, and rising fuel prices, which reduced consumption in the transport sector [16,24,43]. By 2018, emissions had fallen in 25 EU countries, although they remained a challenge in Malta, Cyprus and Spain. In Poland, by contrast, the indicator slightly increased, resulting in a drop in its EU-27 ranking from 12th in 2010 to 16th in 2018. Overall, by 2018 the EU member states had reduced emissions by 16.3% compared to 1990, thus approaching the 20% target, although Ireland and Portugal failed to meet their reduction commitments [18,44].
The European Environment Agency reports that by 2020 greenhouse gas emissions in the EU-27 had fallen by 31% compared with 1990 levels, thus substantially overachieving the Europe 2020 target of a 20% reduction. The downward trajectory observed between 2010 and 2018 continued in subsequent years, with emissions falling by 4% between 2018 and 2019 and by a further 10% between 2019 and 2020. This sharp decline was driven by the accelerated replacement of coal with gas and renewables in the power sector, reinforced by the economic slowdown during the COVID-19 crisis. Despite this EU-wide success, several countries (e.g., Cyprus, Malta, Ireland) failed to meet their national Effort Sharing targets for 2020, confirming persistent structural differences across member states [45].

3.5. Share of Renewable Energy in Gross Final Energy Consumption

The socioeconomic processes monitored for the entire EU were expected to reach the target values in 2020: the employment rate of people aged 20 to 64 years was set at a minimum of 75%, R&D investment was expected to account for an average of the 3% of EU GDP, and the share of renewable energy in final energy consumption was expected to reach at least 20% [21,46,47]. Considering the important area of climate, it should be noted that the share of renewable energy increased on average by 6% and greenhouse gas emissions by 8.75% (compared to 2010), which means that the absolute differences in the indicators were very high in relation to the assumed targets (a decrease of at least 20%). Positive and high skewness coefficients indicate that in most countries this share was lower than the EU average, equating to 22.4% for renewable energy (2019) and 82.1% for greenhouse gas emissions (2018). In Poland, the share of renewable energy in 2019 was still 3% below the level assumed in the strategy. The EU countries are quite strongly differentiated in terms of the share of renewable energy in gross final energy consumption. The share of renewable energy in Poland cannot be considered significant (96%, 10th place among EU countries) [42,47,48]. The share of renewable energy in gross final energy consumption (%) increased in all EU countries. The average value of this indicator for the EU-27 rose from 14.73% in 2010 to 19.61% in 2020. Eurostat data show that this increase was continuous: The EU share of renewables rose from 14.4% in 2010, 17.8% in 2015 and 19.9% in 2019, to reach 22.1% in 2020. This confirms a stable growth trajectory throughout the implementation period. Poland also recorded an increase in the share of renewable energy in gross final energy consumption, from 8.8% in 2010 to 16.1% in 2020. The EU country in this respect in 2020 was Sweden, with an indicator of 60.1%, followed by Finland (43.8%), while the weakest performers were Malta (10.7%) and Hungary (13.9%) (Figure 3).
The European Environment Agency confirmed that in 2020 the EU achieved a renewable energy share of 21.3% in gross final energy consumption, thereby surpassing the 20% Europe 2020 target. This EU-level result was made possible by significant overachievement in several member states, which offset underperformance in others (e.g., Belgium, France, Poland, Romania, Slovenia). The outcome illustrates the effectiveness of flexibility mechanisms such as statistical transfers, while also highlighting that structural challenges in some countries constrained uniform progress across the Union [45].
In view of the significant progress achieved in implementing the objectives of the strategy in the area of greenhouse gas emissions, the EU is considering the possibility of increasing the reduction target from 20% to 30%. However, achieving this objective would require specific measures, namely adjusting the emissions trading system by withholding part of the allowances intended for auction, rewarding fast-acting entities investing in state-of-the-art emission reduction technologies through additional free allowances, introducing carbon dioxide emission taxes, promoting policies orientated towards emission reductions, and using international credit instruments to encourage the application of best available technologies for emission reduction [33,48,49].

3.6. Primary Energy Consumption

For most countries, the indicator of primary energy consumption per 100,000 inhabitants remained below the European average. In 2020, only eight of the 27 countries reached the goal level of 40. In 2020, the lowest value of this indicator was recorded in Malta (0.74), in Cyprus (2.2 Mtoe per 100,000 inhabitants) and the highest in Germany (262.49), France (208.36) and Italy (132.32 Mtoe per 100,000 inhabitants). Poland, in terms of this indicator, ranked eighth among EU countries (96.53 Mtoe per 100,000 inhabitants). Between 2010 and 2020, there was no significant change in the ranking of countries by the indicator of primary energy consumption per 100,000 inhabitants. Germany and Malta still represented the countries with the highest and lowest values, respectively (Figure 4).
The European Environment Agency indicates that in 2020 the EU-27 reduced primary energy consumption by about 5% and final energy consumption by 2.6% compared with the indicative 2020 targets, thereby achieving and even slightly overachieving the “20/20/20” efficiency goal. This progress was strongly influenced by the COVID-19 pandemic, which limited industrial production and transport demand, but it also built on gradual improvements in energy efficiency throughout the decade. Importantly, in 2019 many Member States were still above their indicative targets, which suggests that the final 2020 achievement was partly crisis-driven. Nevertheless, the outcome demonstrates the feasibility of substantial reductions if reinforced by consistent policy measures [45].

3.7. Summary of Indicator Implementation in 2020

The target results of the strategy (2020) vary depending on the area under study. Analysing the labour market, the employment rate of people aged 20 to 64 in 2020 was 72.4%, R&D expenditure on research and development in the GDP was 2.32%, greenhouse gas emissions (dynamic index 1990 = 100) were 79.2, the share of renewable energy in gross final energy consumption reached 22.09%, the share of early school leavers (aged 18 to 24) was 9.9%, the share of people aged 30 to 34 years with higher education reached 41%, and the rate of severe material deprivation was 13.8% (Table 3).
In addition to the climate and energy goals, the 2020 Europe Strategy also included objectives related to employment (Target 1), education (Target 4), and poverty reduction (Target 5). With regard to employment, the target of a 75% employment rate for the population aged 20–64 was not achieved at the EU level, as the average in 2020 stood at 72.4%. Despite steady improvement compared to 2010, significant disparities persisted, with Northern and Central European countries generally outperforming Southern and Eastern member states. In education, progress was more encouraging: the share of early school leavers dropped to 9.9% (meeting the below 10% target), while the share of people aged 30–34 with tertiary education attainment reached 41%, slightly exceeding the 40% benchmark. These results suggest that the EU was relatively successful in fostering a knowledge-based economy through educational policies, although inequalities remain in access to higher education between countries and regions. In contrast, the poverty reduction target (lifting at least 20 million people out of poverty or social exclusion) was only partially addressed. In 2020, the rate of severe material deprivation was still 13.8%, and progress was uneven, with the economic crisis and subsequent fiscal constraints limiting the effectiveness of poverty alleviation measures in many countries (e.g., Greece, Spain, Italy). This indicates that while the Strategy made notable contributions to education and modest improvements in employment, social cohesion objectives remained the most challenging.
The analysis confirmed that the implementation of the Europe 2020 strategy produced mixed results across EU member states. Significant progress was achieved in reducing greenhouse gas emissions, although the pace varied and several countries failed to meet the intermediate 2018 goals. The share of renewable energy in gross final energy consumption increased across all member states, with Sweden and Finland emerging as leaders, while Malta and Hungary remained the weakest performers. Primary energy consumption generally declined, but only a minority of countries reached the target levels. In terms of research and development expenditure, the EU average remained well below the 3% GDP target, with only six countries achieving this benchmark. Considerable polarisation persisted between innovation leaders such as Belgium, Sweden, Germany, and Austria and lagging countries such as Romania, Cyprus, and Bulgaria. Overall, the results suggest that although notable advances were made in environmental and energy goals, particularly in the reduction of renewable energy and emissions, the objectives regarding R&D expenditure and employment growth proved to be more challenging. Sweden and Finland emerged as leaders due to strong reliance on renewable energy, high investment in R&D, and supportive institutional frameworks. In contrast, Malta and Hungary lagged due to limited resources and structural constraints. These disparities reveal both the achievements and weaknesses of the 2020 Europe strategy: common EU targets encouraged progress but did not sufficiently reflect national differences. Future strategies should therefore adopt more differentiated approaches tailored to regional priorities. The findings point to strong disparities between member states, which limited the overall effectiveness of the strategy in achieving balanced and inclusive progress.
These findings are consistent with previous studies that highlighted persistent asymmetries in the implementation of the Europe 2020 Strategy [14,15,16,50]. In particular, the uneven distribution of progress between member states confirms the concerns expressed in the literature about the difficulty of applying uniform development goals to structurally diverse economies [6,21]. By linking our results with these broader debates, the present analysis demonstrates that while the Europe 2020 framework was effective in setting common objectives, it lacked mechanisms to account for national specificities. Although the Hellwig method provides a transparent and objective means of constructing a composite indicator, it treats all variables as equally important. This may oversimplify the relative significance of different policy dimensions. Future research could address this limitation by applying alternative approaches that incorporate differentiated weighting or multiple criteria, offering a more nuanced assessment of the selected strategy.
From a theoretical perspective, the study advances the understanding of EU sustainability governance by illustrating how composite indicators, such as those derived from Hellwig’s method, can capture multidimensional progress and disparities more effectively than single metrics. From a practical perspective, the results have implications for policy design: they suggest the need for differentiated national pathways under EU-level strategies, more flexible allocation of funding to lagging regions, and greater emphasis on innovation capacity-building in weaker performers. These insights can inform the implementation of the European Green Deal and future development frameworks, ensuring that ambitious EU-wide targets are complemented by mechanisms that address structural divergences between member states.

4. Conclusions

The analysis demonstrates that the Europe 2020 strategy contributed to tangible progress in several areas of sustainable development, particularly in reducing greenhouse gas emissions and increasing the share of renewable energy. However, the achievements were uneven between member states, and the targets related to R&D expenditure and employment proved more challenging to meet. Significant disparities persisted between innovation leaders (e.g., Sweden, Finland, Germany) and lagging countries (e.g., Romania, Bulgaria, Cyprus).
From a policy perspective, these findings underscore the need for more differentiated national trajectories within EU-level frameworks, complemented by targeted support for structurally weaker regions and stronger institutional mechanisms to foster innovation. At the same time, the study remains limited by its reliance on aggregate Eurostat data and the use of a single methodological approach, which may not fully capture national policy contexts or structural differences.
Therefore, future research should adopt mixed-method designs, extend the temporal scope beyond 2020, and apply advanced weighting and analytical techniques to deliver a more comprehensive evaluation. Such efforts will be essential to inform the implementation of the European Green Deal and subsequent EU development strategies.

Author Contributions

Conceptualization, N.Ż. and B.S.; Methodology, T.O., A.W. and K.G.; Validation, W.L.; Formal analysis, T.O., W.L. and K.G.; Resources, T.O., W.L. and K.G.; Writing – original draft, N.Ż., B.S. and A.W.; Writing – review & editing, N.Ż. and B.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Abraham, R.A.; Kumar, K.K. Multidimensional Poverty and Vulnerability. Econ. Political Wkly. 2008, 43, 79–87. [Google Scholar]
  2. Agenda 2030 for Sustainable Development—Implementation in Poland. 2015. Available online: http://www.un.org.pl/files/170/Agenda2030PL_pl-5.pdf (accessed on 18 August 2025).
  3. Aguinis, H.; Gottfredson, R.K.; Joo, H. Best-Practice Recommendations for Defining, Identifying, and Handling Outliers. Organ. Res. Methods 2013, 16, 270–301. [Google Scholar] [CrossRef]
  4. European Union. Ten Priorities for Europe; Publications Office of the European Union: Luxembourg, 2015. [Google Scholar] [CrossRef]
  5. Tusińska, M. International Competitiveness and Socio-Economic Development: The Case of Poland Against the Background of EU Countries; University of Economics in Katowice Press: Katowice, Poland, 2014; pp. 165–184. [Google Scholar]
  6. Aiginger, K.; Vogel, J. Competitiveness: From a Misleading Concept to a Strategy Supporting Beyond GDP Goals. Competitiveness Review 2015, 25, 497–523. [Google Scholar] [CrossRef]
  7. Andriopoulou, E.; Karakitsios, A.; Tsakloglou, P. Inequality and Poverty in Greece: Changes in Times of Crisis. In Socioeconomic Fragmentation and Exclusion in Greece Under the Crisis; Palgrave Macmillan: London, UK, 2018; pp. 23–54. [Google Scholar]
  8. Andriopoulou, E.; Tsakloglou, P. The Determinants of Poverty Transitions in Europe and the Role of Duration Dependence; IZA Discussion Paper No. 5692; Institute for the Study of Labour: Bonn, Germany, 2011. [Google Scholar]
  9. Armengaud, E.; Sams, C.; von Falck, G.; List, G.; Kreiner, C.; Riel, A. Industry 4.0 as Digitalisation over the Entire Product Lifecycle: Opportunities in the Automotive Domain. Systems, Software and Services Process Improvement. In Proceedings of the European Conference on Software Process Improvement, Ostrava, Czech Republic, 6–8 September 2017; Springer: Cham, Switzerland, 2017. [Google Scholar]
  10. Arnania-Kepuladze, T.; Sologashvili, D.; Kepuladze, G. Labour Market: COVID-19 Pandemic and Working Poverty. FBIM Trans. 2021, 9, 1–10. [Google Scholar] [CrossRef]
  11. Artymowska, P.; Kukliński, A.; Żuber, P. (Eds.) The Future of Regions—The Megaspaces of the XXI Century; Ministry of Regional Development: Warsaw, Poland, 2011. [Google Scholar]
  12. Aschhoff, B.; Crass, D.; Cremers, K.; Grimpe, C.; Rammer, C. European Competitiveness in Key Enabling Technologies. 2010. Available online: https://nanonet.pl/wp-content/uploads/2018/02/European-Competitiveness-in-Key-Enabling-Technologies.pdf (accessed on 18 August 2025).
  13. Balcerzak, A.P. Poland’s Position in the Context of the Europe 2020 Strategy: Analysis Using Linear Ordering Methods. Econ. Stud. 2011, 31–41. [Google Scholar]
  14. Balcerzak, A.P. Multidimensional Analysis of Social Cohesion in the European Union Countries in the Context of the Europe 2020 Strategy; University of Warmia and Mazury Press: Olsztyn, Poland, 2015. [Google Scholar]
  15. Dziembała, M. Modernisation and Socio-Economic Cohesion of the EU in the Light of the Europe 2020 Strategy. In Social Inequalities and Economic Growth; Woźniak, M.G., Ed.; University of Rzeszów Press: Rzeszów, Poland, 2011; Volume 18. [Google Scholar]
  16. Gasz, M. Europe 2020 Strategy–Assumptions and Prospects for Implementation. Soc. Inequalities Econ. Growth 2014, 38, 85–97. [Google Scholar]
  17. Domańska, W. The Development Strategy of Europe until 2020. Wiadomości Stat. 2010, 591, 1–7. [Google Scholar]
  18. Jasiński, L. Europe 2020 Strategy. Nowe Życie Gospod. 2010, 2–6, 28–29. [Google Scholar]
  19. Walenia, A.; Wilczyńska, M.; Lew, A.; Lew, G.; Pomykała, M.; Nycz, E. Competitiveness of EU Member States According to the Index Institute of Management Development. Eur. Res. Stud. J. 2024, XXVII, 1610–1628. [Google Scholar] [CrossRef]
  20. Wilczyńska, M.; Walenia, A.; Lew, A.; Rejman, K.; Sowa, B.; Olejarz, T.; Życzyński, N. Indicators of Socio-Economic Development of European Union Member States. Eur. Res. Stud. J. 2025, 28, 489–513. [Google Scholar] [CrossRef]
  21. Kroll, C.; Warchold, A.; Pradhan, P. Sustainable Development Goals (SDGs): Are We Successful in Turning Trade-Offs into Synergies? Palgrave Commun. 2019, 5, 140. [Google Scholar] [CrossRef]
  22. Barroso, J. Europe 2020 Strategy; EUR-Lex: Brussels, Belgium, 2019; Available online: https://eurlex.europa.eu/LexUriServ/LexUriServ (accessed on 18 August 2025).
  23. Cousineau, D.; Chartier, S. Outliers Detection and Treatment: A Review. Int. J. Psychol. Res. 2010, 3, 58–67. [Google Scholar] [CrossRef]
  24. Hellwig, Z. The Application of the Taxonomic Method to the Typological Division of Countries According to the Level of Development and Resources and the Structure of Qualified Personnel. Stat. Rev. [Przegląd Stat.] 1968, 4, 307–327. [Google Scholar]
  25. Coyle, D. GDP: A Brief but Affectionate History–Revised and Expanded Edition; Princeton University Press: Princeton, NJ, USA, 2015. [Google Scholar] [CrossRef]
  26. Delgado, M.; Ketels, C.; Porter, M.E.; Stern, S. The Determinants of National Competitiveness; NBER Working Paper No. 18249; National Bureau of Economic Research: Cambridge, MA, USA, 2012. [Google Scholar]
  27. Diamond, P. National Debt in a Neoclassical Growth Model. Am. Econ. Rev. 1965, 55, 1126–1150. [Google Scholar]
  28. Dicken, P. Global Shift: Mapping the Changing Contours of the World Economy, 5th ed.; The Guilford Press: New York, NY, USA, 2007. [Google Scholar]
  29. Dinçer, H.; Yüksel, S.; Martínez, L. Collaboration-Enhanced Hybrid Fuzzy Decision-Making Approach to Analyse the Renewable Energy Investment Projects. Energy Rep. 2021, 8, 377–389. [Google Scholar] [CrossRef]
  30. Piwowar-Sulej, K.; Sołtysik, M.; Jarosz, S.; Pukala, R. The Linkage between Renewable Energy and Project Management: What Do We Already Know, and What Are the Future Directions of Research? Energies 2023, 16, 4609. [Google Scholar] [CrossRef]
  31. Pukala, R. Use of Neural Networks in Risk Assessment and Optimisation of Insurance Cover in Innovative Enterprises. Eng. Manag. Prod. Serv. 2016, 8, 43–56. [Google Scholar] [CrossRef]
  32. Ishchuk, S.; Sozanskyy, L.; Pukala, R. Optimisation of Structural Parameters of the Industry by the Criterion of Product Innovation. Eng. Manag. Prod. Serv. 2021, 13, 7–24. [Google Scholar] [CrossRef]
  33. European Commission. Science, Technology and Innovation Key Figures Report: 2020/2021. 2021. Available online: http://ec.europa.eu/invest-in-research/monitoring/statistical01_en.htm (accessed on 18 August 2025).
  34. Statistics Poland. Europe 2020 Strategy Indicators. 2021. Available online: https://stat.gov.pl (accessed on 18 August 2025).
  35. Okoń-Horodyńska, E.; Piech, K. The Lisbon Strategy and the Possibilities of Building a Knowledge-Based Economy in Poland—Conclusions and Recommendations [Strategia Lizbońska a Możliwości Budowania Gospodarki Opartej na Wiedzy w Polsce—Wnioski i Rekomendacje]; Polish Economic Society: Warsaw, Poland, 2005; pp. 7–8. [Google Scholar]
  36. Dorrego, P.F.; Costa, R.V.; Fernandez, C.F.-J. Product Innovation and Relational Capital: Evidence from Portugal. Electron. J. Knowl. Manag. 2013, 11, 295–308. [Google Scholar]
  37. Drozdowicz-Bieć, M. Basic Concepts and Definitions of International Competitiveness. Res. Pap. Mater. Inst. Econ. Dev. SGH 2006, 77, 9–31. [Google Scholar]
  38. UNDP. Human Development Report 2019. Beyond Income, Beyond Averages, Beyond Today: Inequalities in Human Development in the 21st Century. United Nations Development Programme: New York, 2019. Available online: https://hdr.undp.org/system/files/documents/hdr2019.pdf (accessed on 18 August 2025).
  39. Woźniak, M.G. New Structural Economics in the Context of Integrated Development. Nierówności Społeczne A Wzrost Gospod. 2018, 54, 34–52. [Google Scholar] [CrossRef]
  40. Dzikowska, M.; Gorynia, M.; Jankowska, B. The Global Economic Crisis: An Attempt to Measure Effects for Individual Countries. Ekonomista 2015, 6, 733–759. [Google Scholar]
  41. EPSCO. Employment, Social Policy, Health and Consumer Affairs Council. 2022. Available online: https://www.consilium.europa.eu/en/council-eu/configurations/epsco/ (accessed on 18 August 2025).
  42. Różański, J. Innovation of Polish Enterprises against the Background of European Innovation Systems. Przegląd Organizacji 2020, 9, nr251. [Google Scholar]
  43. Gebelein, H.; Schiller, B.R. The Economics of Poverty and Discrimination. ILR Rev. 1998, 27, 641. [Google Scholar] [CrossRef]
  44. Kowalski, A.M. Global South–Global North Differences. In Encyclopedia of the UN Sustainable Development Goals; Leal Filho, W., Azul, A., Brandli, L., Lange Salvia, A., Özuyar, P., Wall, T., Eds.; Springer: Champaign, IL, USA, 2020. [Google Scholar] [CrossRef]
  45. European Environment Agency. Trends and Projections in Europe 2021. EEA Report No 13/2021; Publications Office of the EU: Luxembourg, 2021. [Google Scholar] [CrossRef]
  46. Kowalski, A.M. The Impact of the Economic Crisis on Processes of Cooperation and Competition. Cent. Eur. Manag. J. 2011, 19, 30–42. [Google Scholar]
  47. OECD. Growth, Building Jobs and Prosperity in Developing Countries. Department for International Development: Great Britain. 2008. Available online: https://www.oecd.org/derec/unitedkingdom/40700982.pdf (accessed on 18 August 2025).
  48. Sabir, H.; Tahir, S. Impact of Different Macroeconomic Variables on Poverty in Pakistan. Interdiscip. J. Contemp. Res. Bus. 2010, 3, 788–799. [Google Scholar]
  49. European Union. Reduction of Greenhouse Gases by 2020. 2008. Available online: http://europa.eu/legislation_summaries/energy/european_energy_policy/en0008_pl.htm (accessed on 18 August 2025).
  50. Wysocki, F. Taxonomic Methods in Identifying Economic Types of Agriculture and Rural Areas; Poznań University of Life Sciences: Poznań, Poland, 2010. [Google Scholar]
Sustainability 17 09030 g001
Figure 1. Expenditure on research and development (R&D)—as % of GDP. Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 February 2022).
Figure 1. Expenditure on research and development (R&D)—as % of GDP. Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 February 2022).
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Sustainability 17 09030 g002
Figure 2. Greenhouse gas emissions (dynamic index 1990 = 100). Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 June 2025).
Figure 2. Greenhouse gas emissions (dynamic index 1990 = 100). Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 June 2025).
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Sustainability 17 09030 g003
Figure 3. Share of renewable energy in gross final energy consumption (%). Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 June 2025).
Figure 3. Share of renewable energy in gross final energy consumption (%). Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 June 2025).
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Sustainability 17 09030 g004
Figure 4. Primary energy consumption in Mtoe (million tonnes of oil equivalent) per 100,000 inhabitants. Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 June 2025).
Figure 4. Primary energy consumption in Mtoe (million tonnes of oil equivalent) per 100,000 inhabitants. Source: www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 20 June 2025).
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Table 1. Objectives and selected key indicators of the Europe 2020 Strategy for the EU in achieving the 20/20/20 targets and R&D expenditure.
Table 1. Objectives and selected key indicators of the Europe 2020 Strategy for the EU in achieving the 20/20/20 targets and R&D expenditure.
Overarching Objectives of the StrategySelected Main Indicators
Allocate 3% of EU GDP to R&D investmentsR&D expenditure (% of GDP)
Obtain “20/20/20” climate and energy goals: 20% reduction in GHG emissions (vs. 1990), 20% share of renewables, 20% increase in energy efficiencyGHG emissions (1990 = 100); Share of renewables in gross final energy consumption (%); Primary energy consumption (in Mtoe)
Source: own elaboration based on https://ec.europa.eu/regional_policy/pl/newsroom/news/2015/02/europe-2020-indicators-comparing-member-states-performance (accessed on 7 July 2025).
Table 2. Values of the main indicators of the implementation of the Europe 2020 Strategy in EU countries in 2010 and 2020 in terms of achieving the 20/20/20 targets and R&D expenditure.
Table 2. Values of the main indicators of the implementation of the Europe 2020 Strategy in EU countries in 2010 and 2020 in terms of achieving the 20/20/20 targets and R&D expenditure.
Country/YearX1X2X3X4
Austria20102.73109.1931.2132.86
20203.22102.6636.5429.73
Belgium20102.0592.636.0153.31
20203.5282.671343.88
Bulgaria20100.5759.7413.9217.4
20200.8657.1623.3217.19
Croatia20100.7487.5125.18.86
20201.2775.2331.027.76
Cyprus20100.44161.526.162.67
2020 0.85153.8116.882.2
Czechia20101.3371.0710.5142.54
20201.9964.8217.337.47
Denmark20102.9290.8921.8819.97
20203.0370.6931.6415.32
Estonia20101.5852.324.755.56
20201.7949.9830.184.81
Finland20103.71107.1132.1635.44
20202.9481.4143.829.8
France20102.1894.7812.62254.44
20202.3583.119.11208.36
Germany20102.7376.6411.66315.15
20203.1470.4419.31262.49
Greece20100.6114.5810.0727.24
20201.4990.8421.7519.68
Hungary20101.1369.4312.7424.62
20201.6267.8213.8523.89
Ireland20101.6112.475.7514.71
20201.23113.616.1613.43
Italy20101.22100.4317.02167.28
20201.5484.4120.36132.32
Latvia20100.6147.630.744.56
20200.745.9542.134.26
Lithuania20100.7843.4419.646.67
20201.1742.6426.776.23
Luxembourg 20101.5102.382.854.61
20201.1394.1619.673.94
Malta20100.59118.849.973.93
20200.6696.1410.724.74
The Netherlands20101.7993.9271.72
20202.2988.5813.9958.58
Poland20100.7287.19.2896.56
20201.3987.4216.196.53
Portugal20101.54118.9624.1522.65
20201.58118.933.9819.54
Romania20100.4650.1122.8332.95
20200.4746.8424.7330.92
Slovakia20100.6163.259.0916.66
20200.9259.1617.3415.15
Slovenia20102.05105.222.087.03
20202.1594.35256.13
Spain20101.36106.2113.78123.01
20201.41119.7421.22105.03
Sweden20103.1791.8246.0948.34
20203.5175.2860.1241.82
Source: own elaboration based on https://ec.europa.eu/eurostat (accessed on 7 July 2025).
Table 3. Implementation of the indicators.
Table 3. Implementation of the indicators.
Strategic Indicator2020 Result
Employment rate (age 20–64)72.4%
R&D expenditure (% of GDP)2.32%
GHG emissions index (1990 = 100)79.2
Share of renewables in final energy consumption22.09%
Early school leavers (age 18–24)9.9%
Obtainment of tertiary education (age 30–34)41%
Severe material deprivation13.8%
Source: own elaboration based on www.stat.gov.pl/gus/5840_12681_PLK_HTML.htm (accessed on 2 June 2025).
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Życzyński, N.; Sowa, B.; Olejarz, T.; Walenia, A.; Lewicki, W.; Gurba, K. Europe 2020 Strategy and 20/20/20 Targets: An Ex Post Assessment Across EU Member States. Sustainability 2025, 17, 9030. https://doi.org/10.3390/su17209030

AMA Style

Życzyński N, Sowa B, Olejarz T, Walenia A, Lewicki W, Gurba K. Europe 2020 Strategy and 20/20/20 Targets: An Ex Post Assessment Across EU Member States. Sustainability. 2025; 17(20):9030. https://doi.org/10.3390/su17209030

Chicago/Turabian Style

Życzyński, Norbert, Bożena Sowa, Tadeusz Olejarz, Alina Walenia, Wiesław Lewicki, and Krzysztof Gurba. 2025. "Europe 2020 Strategy and 20/20/20 Targets: An Ex Post Assessment Across EU Member States" Sustainability 17, no. 20: 9030. https://doi.org/10.3390/su17209030

APA Style

Życzyński, N., Sowa, B., Olejarz, T., Walenia, A., Lewicki, W., & Gurba, K. (2025). Europe 2020 Strategy and 20/20/20 Targets: An Ex Post Assessment Across EU Member States. Sustainability, 17(20), 9030. https://doi.org/10.3390/su17209030

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