An Attempt to Assess the Implementation of the Circular Economy in the EU-27 as an Important Element of Sustainable Development

Abstract

The development and implementation of appropriate measurement tools is a prerequisite for the effective introduction of the concept of a circular economy at every level of management. Fundamental to this system is the establishment and adoption of indicators, which are a monitoring tool to diagnose, model, and forecast the circular economy. The full identification of indicators and the degree of their implementation provide the necessary knowledge for a comprehensive assessment of the state of change and the prospects for closed-loop circuits in EU countries. The main objective of the research conducted was an attempt to assess the implementation of the circular economy in the EU-27 countries. The research used indicators of the circular economy, analyzed the relative taxonomic measure of development, and established a ranking of EU countries. In this research, three questions formulated were as follows: do average circular economy indicators in EU countries show an increasing trend over the last decade? Is the circular economy development gap decreasing in EU countries? In which countries are the biggest barriers to circular economy implementation? Based on the research questions posed in this way, two hypotheses were adopted: in the last decade, there has been a slow transition from a linear to a circular economy in EU countries; there is a wide variation in circular economy indicators among EU countries. Achieving the main objective required recognizing the issue of natural resource management, characterizing the changes in individual conditions affecting the possibility of realizing the assumptions of the closed-loop economy, and assessing changes in the possibility of implementing the circular economy in individual EU countries over a period of 10 years. The analysis of the dynamics of change over the past 10 years in the 27 EU countries indicates a slow process of transition from a linear to a circular economy. The study shows that only 8 EU countries have seen an increase in the development measure.

1. Introduction

The circular economy (closed-loop economy—CLE) is the opposite of the linear model used until now. The linear model of the economy assumed activities that are now referred to as a robbery of the environment (“take, produce, consume, and throw away”). Although the concept of the CLE has appeared in studies from the 1970s, no single universal definition of the term has been developed [1,2,3,4,5,6,7]. Thus, the CLE is seen as a general concept and a paradigm of conduct.

Corporate sustainability should involve a break with the functioning model of natural resource use in favor of the circular economy. For many companies involved in manufacturing or processing, the CLE brings enormous challenges and heralds far-reaching changes, especially since the linear model of resource management dominates the global economy [8,9,10,11,12]. For several decades, the European Union has been consistently preparing solutions to push companies to use natural resources more consciously [13,14,15,16,17,18,19]. The most important EU orders in this regard include the following:

• The communication “EUROPE 2020: A strategy for smart, sustainable and inclusive growth” [20];
• The communication “Roadmap for a Resource-Efficient Europe” [21];
• The economic report on the potential of the CLE model “Towards the Circular Economy” [22];
• The communication “Closing the loop—the EU action plan for a circular economy” [23];
• The statement “Manifesto for a resource-efficient Europe” [24].

Support for activities focused on closed-loop products is also evident in the ESG (E—environment; S—society; G—corporate governance) reporting system. Among environmental indicators, one can point to activities dedicated to reducing the exploitation of natural resources, combating environmental pollution, and minimizing excessive energy consumption [25,26,27,28].

According to the CLE Action Plan, regulatory changes cover virtually all sectors. Among them, the key areas are the following:

• Plastics and packaging—Europe’s 2030 strategy addresses reusing or recycling every plastic package, reducing their single-use consumption, and ending the use of microplastics [29].
• Textiles—the EU’s strategy for sustainable, closed-loop textiles by 2030 includes tougher water consumption standards and encourages a shift to quality, durability, longer use, repair, and reuse, among other things [30].
• Electronics—the directive incorporating the Ecodesign Action Plan requires products to be more energy efficient and have a longer life cycle [31].
• Food and water—halving food waste by 2030 as part of a farm-to-table strategy [32].
• Batteries and vehicles—among other things, the materials of all batteries should have a low carbon footprint [33].
• Construction—increasing material reuse and energy renovation rates for buildings [34].
• Waste management—regulations to increase high quality recycling, move away from landfill, and minimize waste incineration [35].

The legal aspects of the issue of the CLE have been regulated so far. Worth mentioning here is the law on waste electrical equipment, counteracting food waste, or the law on packaging and packaging waste management. The various legal acts impose obligations on entrepreneurs and the risk of sanctions in case of failing to comply with them. Implementing the postulates arising from the CLE is important for companies, as extending the life of products means reducing manufacturing expenses and energy consumption [36,37,38,39,40,41].

The closed-loop economy should be implemented at every stage of a product life cycle [42,43,44,45,46,47,48,49]. The cradle-to-cradle (C2C) model of operation, defined as “from the cradle of the previous product to the cradle of the next product”, considers the following stages [50,51,52,53,54]:

• The product design phase—takes into account resource conservation, ecological design, and the prevention of product obsolescence;
• The production phase—involves the significant reduction of production waste, maximizing the efficiency of technological processes by introducing innovative solutions, monitoring the energy efficiency of machinery and buildings, an eco-management and audit system, and the verification of environmental technologies;
• The use phase—concerns raising public awareness of the rational consumption of goods by, among others, government agencies and entrepreneurs whose expenditures on pro-environmental campaigns can count as tax-deductible expenses;
• The waste management phase—involves the use of various types of solutions that give products a “second life”, i.e., recycling or up cycling, which maximize the usefulness of once-obtained resources.

An example of an activity that is part of the CLE concept could be the generation of energy from renewable sources (e.g., photovoltaics, wind turbines) or the purchase of energy from suppliers under contractual agreements.

The CLE also contributes very much to climate protection [31,39]. Reusing the same products multiple times and extending their life cycle saves natural resources. This, in turn, brings a reduction in environmental pollution and threats to living organisms [1,2,3,4,5,6,7]. Less industrial production means a lower carbon footprint and reduced energy consumption, and the use of renewable energy sources lowers the use of conventional fuels (coal, wood) [1,13,16,55,56]. The challenges faced by entrepreneurs in this regard are usually economic in nature and imply the need to implement new technologies and a new business model. In the broader perspective, however, such activities are profitable. There is no doubt that the creation of smoothly operating CLE mechanisms requires not only extensive legislative measures, but also significant financial outlays on the part of entrepreneurs as well [57,58,59,60,61,62].

Under the current financial outlook until 2027, a number of measures are planned to support micro-, small-, and medium-sized enterprises in the implementation of CLE principles [63]. Within the framework of the European Funds for Social Development (EFSD) program, a number of activities are being organized (e.g., “CLE–it pays”) to support businesses in developing green economy competencies in the area of low carbon or the CLE. Popularizing the best circular economy solutions (products, business models) aimed at achieving environmental effects and economic, managerial, and social benefits is also a very important issue.

At present, the concept of sustainable development is of great importance in the development of world civilizations. This development seeks to ensure sustainable improvement in the quality of life of generations through the formation and realization of appropriate proportions of economic, human, and natural capital [64,65,66]. The internal balance of the systems, namely environment, economy, and society, within the framework of sustainable development is determined by the formation of appropriate orders: the ecological order is shaped in the environment by human interaction with natural environmental processes, the economic order is shaped in the specific territory of the state, while the social order is understood as the organization of social life. These orders function in an integrated macrosystem. Determining these orders with circular economy indicators makes it possible to determine the current condition and to draw a forecast for the circular economy.

Table 1. The direct impact of the circular economy on achieving the sustainable development goals.

Nr	Name of the Objective	Impact of a Closed Circuit Economy	Power
6.	Clean water and sanitary sanitation	The reduction of waste and negative externalities throughout the product life cycle. Reducing waste and increasing recycling and reuse. The development of technology and the sustainable management of water resources. Keeping raw material in circulation for as long as possible.	strong
7.	Clean and accessible energy	The use of renewable energy sources and increasing their share in the energy mix. Reducing negative effects, e.g., CO2 emissions.	strong
9.	Innovation, industry, infrastructure	Improving material and energy efficiency (cogeneration). Cooperation between enterprises in the management of waste generated in the production process. Increasing innovation.	strong
11.	Sustainable cities and communities	Reducing excessive consumerism. The use of public transport.	strong
12.	Responsible consumption and production	The extension of the product life cycle, the reduction of waste, reuse, and the rational management of scarce natural resources.	strong
13.	Climate action	The closed cycle of raw materials, the reduction of waste, the introduction of RES. The reduction of the impact of human activities on climate change and the environment.	strong
14.	Life under water	The reduction of marine pollution levels. The reduction of food waste going into the sea. The sustainable use of water resources.	strong
15.	Life on land	The protection and enhancement of plant and animal diversity in the ecosystem. Improving the quality of forest areas and increasing their size. The sustainable management of forests and the use of terrestrial ecosystems.	strong

Source: own compilation based on http://www.un.org.pl/ [accessed on 8 May 2025].

shows the impact of the implementation of the circular economy on the achievement of the sustainable development goals and an assessment of the impact of CLE. The circular economy will have the strongest impact on the achievement of goals 6, 7, 9, 11, 12, 13, 14, and 15.

Based on the research in this thesis, a clear link can be made between the results obtained and goal 12 (Responsible consumption and production) and goal 13 (climate action) of the UN Agenda 2030 for Sustainable Development. Goal 12 promotes the reduction of resource consumption, the reduction of waste, and the efficient management of materials throughout the life cycle of products. The study uses a number of indicators that directly reflect progress in this area:

X₁—the material footprint—the lower it is, the more efficient the consumption of raw materials; this indicator acts as a destimulant, i.e., its increase reduces the value of the CLE index.

X₂—resource productivity—the number of euros generated per unit of raw material consumed; acts as a stimulant of the CLE index.

X₄, X₅, X₇—per capita waste indices—less waste means greater efficiency and reduced waste.

Thus, countries with a low material footprint and high resource productivity (e.g., Germany, France, and the Netherlands) achieved the highest CLE index values, indicating a direct correlation of performance with the achievement of goal 12.

Objective 13, on the other hand, includes measures to reduce greenhouse gas (GHG) emissions, promote renewable energy sources, and increase the resilience of the economy to climate change. This is captured in the study through the following indicators:

X₂₀—greenhouse gas emissions per capita from production activities—acts as a destimulant; lower emissions improve the value of the CLE index.

X₁₉—consumption footprint—indirectly reflects the pressure of consumption on the environment.

X₁₃—closed-loop material use rate—the increased use of secondary materials reduces emissions associated with the extraction and processing of primary raw materials.

Thus, countries with a high level of secondary material use and low GHG emissions (e.g., France—5612 kg/capita, against an EU average of 7183 kg/capita) achieved higher CLE index rankings, indicating a convergence of performance with the decarbonization goal (included in goal 13). A high CLE index value is strongly associated with countries that reduce their consumption of primary materials, manage raw materials efficiently, and have developed recycling and low GHG emissions. In contrast, countries with a low CLE index (e.g., Finland, Malta) do not achieve high compliance with goals 12 and 13, despite ambitious environmental policies, indicating a gap between strategy and practice. The study found that meeting CLE targets requires not only technology and investment, but also a change in the structure of the economy and consumption patterns.

The advantages of more advanced sustainable development and the closed-loop economy at a global level comprise the optimization of the use of materials, innovative revenue sources, the improvement of relations with stakeholders, and the lowering of risks [67,68,69,70,71,72,73].

Critical raw materials (CRMs) are very important in the production of various goods [74,75,76,77]. The transition to a digital, highly energy-efficient, and climate-neutral economy will lead to a greater demand for CRMs. Technologies requiring CRMs and electric motors are key to achieving the goals set out in the Paris Agreement. The EU is increasingly reliant on the raw materials needed for the digital and green transition to materials needed for batteries, renewable energy technologies, and electrical and medical devices. Therefore, investments are needed to recycle products containing critical raw materials. The diversification of and increase in recycling and domestic extraction should be pursued to support the EU’s autonomous and sustainable supply of raw materials for key technologies.

The EU needs a strategy to increase strategic autonomy and resilience with regard to the CRM supply by creating a secondary market using recycled resources. New materials should be sourced from the EU, and their sources ought to be diversified. EU member states should be required to build up strategic stocks, as focusing on recycling will not be enough to meet the growing demand for CRMs. The recommendations stem from the sustainable sourcing of raw materials in the member states that have them. They also recommend streamlining and increasing the transparency of approval processes for exploration and mining projects, without lowering environmental standards. What is also growing significantly is the importance of the role of recycling waste (such as electrical equipment) that contains CRMs. EU member states should increase their efforts to properly collect and recycle end-of-life products containing CRMs as well. There is a need to control the export of key waste containing CRMs from the EU, too. Thus, EU member states should strive to stockpile CRMs in order to secure their supplies and enter into EU agreements containing specific free trade and partnership provisions [78,79,80].

Research, in recent years, has revealed a variety of approaches to CLE implementation at local, regional, and global levels. Kirchherr et al. [81] conducted an extensive survey of industry representatives in Europe, identifying the main barriers to CLE implementation—such as a lack of regulatory support, financial difficulties, and limited understanding of the concept among decision-makers. The authors emphasize that the CLE is not only about recycling, but also about changing business models and mentalities [81]. In contrast, the study by Geissdoerfer et al. [3] focused on the relationship between the CLE and sustainable development. The literature review showed that although the CLE has the potential to support sustainable development goals, it does not guarantee their automatic achievement. How it is implemented and how social and economic aspects are taken into account is crucial [3]. In contrast, Lieder and Rashid proposed a model for integrating the CLE into production systems, based on a case study from the automotive industry. Their findings indicate that the transformation towards the CLE requires cross-sectoral collaboration, the digitization of processes, and designing products with reuse and disassembly in mind [6]. In an urban context, a study by Prendeville et al. [82] analyzed the development of circular cities in Europe. The authors showed that the success of the CLE in cities depends on synergies between public policy, citizen involvement, and innovative technologies. Cities such as Amsterdam and Glasgow can be models of large-scale implementation [82]. At a global level, Korhonen et al. [83] highlight the challenges of assessing the effectiveness of the CLE, pointing to the need to develop uniform indicators and methods to measure its impacts. Their research shows that the CLE can have paradoxically negative environmental impacts if the entire life cycle of products is not taken into account [83]. Thus, research indicates that successful implementation of the CLE requires a holistic approach, combining technology, education, regulation, and models of cooperation between stakeholders. It is also necessary to develop evaluation tools and monitor the actual impact of implemented strategies.

The main objective of the study was to attempt to assess the implementation of the circular economy in individual EU countries as an important element of sustainable development. The study took into account circular economy indicators, analyzed the relative taxonomic measure of development, and prepared a ranking of 27 EU countries. Achieving the main goal required the realization of specific objectives, which included the following: recognizing the issues of natural resource management, characterizing the changes in the conditions affecting the implementation of the assumptions of the circular economy, determining the level at which the implementation of such an economy is possible, and assessing the changes in the implementation of the CLE in individual EU countries over a decade.

2. Study Materials

The research was based on data obtained from Eurostat for 2013–2022 [84]. The EU economy is characterized by a high variation in the level of countries’ development. This problem is particularly evident in the juxtaposition of developing and highly developed countries. However, highly developed countries are not a homogeneous group either, and the degree of variation in the level of their economic development is so significant that one can identify leaders, as well as countries, that are considerably far behind. An extensive network of trade and investment ties, integration processes, and the flow of production factors and technology between highly developed countries should lead to a blurring of the differences between them.

Table 2. The breakdown of monitored areas by the CLE indicators.

Areas of the CLE Monitoring	Monitoring Sub-Indicators the CLE	Unit
Production and consumption	X1—material footprint	t/person
	X2—resource productivity	Euro/kg
	X3—waste generation per capita	kg/person
	X4—waste generation excluding mineral waste per unit of GDP	kg/thousand euro
	X5—municipal waste generation per capita	kg/person
	X6—food waste	kg/person
	X7—generation of packaging waste per capita	kg/person
	X8—waste generation per capita of plastic packaging	kg/person
Waste management	X9—recycling rate of municipal waste	%
	X10—recycling rate for all waste excluding major mineral waste	%
	X11—recycling rate of packaging waste by type	%
	X12—WEEE recycling rate of waste electrical equipment	%
Secondary raw materials	X13—use of materials in a closed loop	%
	X14—share of recycled materials in raw materials demand—end-of-life recycling rates (EOL-RIR)	%
	X15—trade in recyclable raw materials	million t
Competitiveness and innovation	X16—private investment and gross value added in the CLE sectors	million Euro
	X17—people employed in the CLE sectors	thousand FTE
	X18—patents related to recycling and recyclable raw materials	per million people
Global sustainability and resilience	X19—consumption footprint	%
	X20—greenhouse gas emissions from production activities	kg/person
	X21—dependence on imported materials	%
	X22—EU self-sufficiency in raw materials	%

Source: own study.

presents the authors’ own breakdown of monitored areas, taking into account the CLE indicators that were used in further research.

This study was carried out with convergence in mind. Real convergence is understood as the convergence of countries in terms of the level of economic development, most often analyzed through changes in the GDP per capita measured in purchasing power parity. The assessment of the process of the convergence of the CLE variables between countries can be made by analyzing the change in the level of dispersion over time. This type of convergence is referred to as sigma (σ) convergence. In contrast, beta (β) convergence occurs when countries with a lower initial level of economic development are characterized by a higher growth rate than the more developed countries. The result is a process of catching up with initially more developed countries by underdeveloped countries.

Describing EU countries by multiple characteristics causes problems in assessing the similarities between these countries and, thus, also in classifying them. Belonging to the field of statistical multivariate analysis, taxonomic methods are used to classify objects described by multiple features. This type of classification refers to the division of a set of objects into subsets according to an established criterion. As the literature suggests, the classification used in this study featured the following properties:

• The sum of the extracted subsets was the same as the set subject to division (adequacy condition);
• The individual typological groups could not contain any common elements (the condition of separability of typological groups);
• Each class contained at least one object;
• Objects in a given group were as similar to each other as possible;
• Objects in different groups were as dissimilar to each other as possible.

The degree of similarity between EU countries was determined using similarity measures, among which, distance measures were the most commonly used. Their construction is based on the principle that the more similar the objects to each other are, the more similar the values of the characteristics describing them are. The distance measure is a quantity normalized in the range from 0 to 1. Values of the distance measure close to 1 mean that the objects are not very similar to each other due to the adopted set of characteristics, and values close to 0 indicate a high degree of their similarity. This study used a taxonomic measure of development, which was presented as functions of diagnostic variables. The construction of the measure used 18 diagnostic variables categorized as indicators of a circular economy.

3. Research Methodology

Due to the availability of Eurostat data, the analysis was limited to the period 2013–2022 [84]. The time range adopted covers a decade, i.e., a time frame in which the changes and trends taking place can be observed. The set of predetermined diagnostic variables was subjected to statistical verification for their variability and mutual correlation, in order to eliminate those that only slightly differentiate the countries under analysis or duplicate information. The critical value of the coefficient of variation was set at 0.1. This led to the possibility of eliminating some indicators (the share of recycled materials in end-of-life demand for raw materials, the recycling rate of all waste excluding major mineral waste, food waste, and EU self-sufficiency in raw materials) because their discriminatory abilities were too weak. On the other hand, the analysis of the mutual correlation of variables was carried out based on the inverse correlation coefficient matrix method, assuming a critical value of 10. It did not give grounds for rejecting the remaining variables.

The spread of individual trait varieties among the studied collective units was examined to describe the structure. A static analysis was carried out using the basic measures of central tendency and classical variation, while positional measures were used for asymmetry.

Variables X₁ and X₁₁–X₁₈ were treated as stimulants of development, while variables X₂–X₉ and X₁₉–X₂₂ were treated as destimulants. The arithmetic mean ($\overline{x_j}$), median, coefficient of variation (V%), and extreme values (x_min and x_max) were calculated for these variables.

The taxonomic measure of development was constructed in the following stages:

(1)

The values (x_ij) of the diagnostic variables formed an n × p observation matrix, X, where

• n = 27 (the number of EU countries), i = 1, 2, …, n.
• p = 18 (the number of diagnostic features), j = 1, 2, …, p.

(2)

The values of the X matrix were standardized, that is, transformed into the values (z_ij) of the Z matrix of dimensions 27 × 18, according to the formula

$$z_{ij}={\displaystyle \frac{x_{ij}-\overline{x_j}}{s_j}}$$

in which

• $\overline{x_j}$—the arithmetic mean calculated for each diagnostic variable on the basis of n = 27.
• s_j—the standard deviation calculated for each diagnostic variable, according to the formula

$$s_j=\sqrt{{\displaystyle \frac{{\sum }_{i=1}^n{(x_{ij}-\overline{x_j})}^2}{n}}}$$

(3)

The values of z_ij were the basis for determining the pattern of development, which was an object with coordinates z₀₁, z₀₂, …, z_0j, where z_0j = max{z_ij}. A higher value means a better situation for the object in the case of variables called stimulants, z_0j = min{z_ij}. A lower value means a better situation for the object in the case of variables called destimulants.

(4)

The distance from the benchmark (d_i) was determined for each object, according to the formula

$$d_i=\sqrt{{\sum }_{j=1}^p{\left(z_{ij}-z_{0j}\right)}^2}$$

The higher the value of the obtained d_i index, the lower the degree of development of the object.

(5)

Based on the d_i index, the values of the relative taxonomic measure of the CLE development (z_i) were calculated for each of the studied facilities, according to the formula

$$z_i=1-{\displaystyle \frac{d_i}{d_0}}$$

in which

$$d_0=\overline{d}+2s_d,$$

where

• $\overline{d}$—the arithmetic mean, calculated on the basis of n = 27 d_i values;
• s_d—the standard deviation, calculated on the basis of n = 27 values of d_i, according to the formula in point 2.

The relative taxonomic measure of development (z_i) takes values from 0 to 1. The higher the value obtained by the studied country, the higher the level of the development of the circular economy in the EU country was. The values of the indicator in question were used to classify objects, according to the rule

• I group, a very good situation when $\overline{z}$ +$s_z$ < $z_i$;
• II group, a good situation when $\overline{z}$ < $z_i$ ≤ $\overline{z}$ +$s_z$;
• III group, a sufficient situation when $\overline{z}$ − $s_z$ < $z_i$ < $\overline{z}$;
• IV group, an insufficient situation when $z_i$ ≤ $\overline{z}$ − $s_z$.

Research with indicators was carried out in the direction of assessing the level of the CLE development in EU countries and preparing a ranking of these countries.

4. Results and Discussion

Analyzing the descriptive characteristics of the partial indicators of the CLE in 2022 (Table 2) belonging to the five monitored areas, one can notice that most of them are characterized by high variability. In Area I, production and consumption, to which variables X₁–X₇ belong, very strong variability was achieved by indicators of the waste generation per unit of GDP excluding mineral waste (variable X₄) of 114%, with the EU average of 99 kg/thousand (

Table 3. Values of selected characteristics of 18 circular economy indicators in the EU-27 in 2022.

Circular Economy Indicators	Selected Characteristics
	$\overline{\mathit{x}}$	Me	V%	Xmin (Country)	Xmax (Country)
X1—Material footprint	19.3	16.9	45.8	8.3 The Netherlands	50.6 Finland
X2—Resource productivity *	1.9	1.6	59.9	0.3 Bulgaria	4.7 The Netherlands
X3—Waste generation per capita	6291	4604	82.6	1330.0 Latvia	19,950 Finland
X4—Waste generation excluding mineral waste per unit of GDP	98.7	70	114	20 Ireland	500 Bulgaria
X5—Municipal waste generation per capita	533.3	488	23.6	303.0 Romania	803 Austria
X7—Generation of packaging waste per capita	138.2	163.2	26.1	78.8 Bulgaria	2333.8 Ireland
X8—Waste generation per capita of plastic packaging	33.2	31.8	27.6	19.3 Croatia	66.8 Ireland
X9—Recycling rate of municipal waste *	41.1	41.2	36.9	12.3 Romania	69.2 Germany
X11—Recycling rate of packaging waste by type *	62.2	64.9	18.4	31.8 Malta	80.4 Belgium
X12—Recycling rate of waste electrical equipment *	80.7	81.8	10.1	56.6 Portugal	92.8 Czechia
X13—Closed-cycle material use *	10.3	8.8	67.9	1.3 Romania	30.6 The Netherlands
X15—Trade in recyclable raw materials * in million t	1.5	0.9	112.2	0.003 Malta	5.8 The Netherlands
X16—Private investment and gross value added in the CLE sectors *	4176.5	1081	168.3	51.0 Cyprus	31,507 Germany
X17—People employed in the circular economy sectors * in thousand	154.8	66.3	124	8.1 Malta	771.8 Germany
X18—Patents related to recycling and secondary raw materials *	8.0	4	139.7	0.0 Slovakia, Malta, Cyprus	46 Germany
X19—Consumption footprint	111.2	108	10.4	90.0 Ireland	144 Malta
X20—Greenhouse gas emissions from production activities	7183	6841	33.2	3971 Sweden	12,913 Denmark
X21—Dependence on imports of materials	39.9	36.8	48	9.9 Romania	90 Luxemburg

* CLE stimulants. Source: author’s own elaboration based on Eurostat data, 2025.

). The strong dispersion is due to the differences that existed in waste generation across EU countries, with the highest EU rate of waste generation recorded in Bulgaria (500 kg/thousand euros) and the lowest in Ireland (20 kg/thousand euros). Also, a very strong variation of 82.6% occurred in the production of waste per capita in EU countries (X₃). The difference between the highest EU waste-generation rate in Finland (19,950 kg per capita) and the lowest rate of 1330 kg per capita in Lithuania was 18,620 kg/EU resident. With regard to waste generation, the country’s development level matters: those that were better developed, with a more extensive consumption model, recorded higher waste generation. A significant increase in waste production was also observed in small countries with high tourist traffic.

In Area II of closed-loop waste management, which is characterized by variables X₈–X₁₀, we observed a much lower strength of dispersion in waste recycling rates. A moderate variation of 37% occurred for municipal waste recycling rates (variable X₈). However, in the case of the other indicators (variables X₉, X₁₀), their variability was less than 20%, and the values of the EU waste recycling average coincided with the median values of the indicators, which indicates a symmetrical distribution of the variables in the area of waste management. The highest municipal waste recycling values were observed in Germany, at 69.2%, and in Slovenia, Austria, and the Netherlands. These countries have already met the target set for 2025 (55%). The recycling of municipal waste should start at the level of separate collection in households. An important element is also the formation of society’s environmental awareness, which is a multi-year and multi-generational process that requires multi-faceted changes.

The lowest variability was found for the recycling rate of waste electrical equipment (variable X₁₀) and the consumption footprint (X₁₆). The Netherlands recorded the lowest indicator (X₁) for their material footprint and the highest resource productivity (X₂), closed-loop material use (X₁₁), and recyclable raw materials trade (X₁₂) indicators in the EU.

In circular economy Area III, monitoring the EU’s closed-loop management of secondary raw materials, very strong variation occurred for variable X₁₅—trade in recyclable raw materials 112% and variable X₁₃—use of closed-loop materials 68%. For both variables, the Netherlands recorded the highest EU rates in the area of monitoring the management of recyclable raw materials (5.8 million tonnes) and in the trade of recyclable raw materials (EU median—0.9 million tons), as well as a 30.6% use of closed-loop materials. Half of the EU countries attained a closed-loop material use rate of at least 8.8% in 2022.

In the fourth area, which monitors the CLE competitiveness and innovation (variables X₁₆–X₁₈), there was the highest dispersion in all the areas examined (from 124% to 168%). The maximum EU values were achieved by Germany in the case of private investment and the gross value added (X₁₆), the number of people employed in the CLE sectors (X₁₇), as well as the number of implemented patents related to recycling and secondary raw materials (variable X₁₈). A lack of implemented patents in Slovakia, Malta, and Cyprus translated into the lowest level of EU private investment and gross value added in the CLE in Cyprus (EUR 5.1 million) and the lowest number of people employed in the CLE sectors in Malta.

Research and development (R&D) activity is particularly important for accelerating economic growth as it increases innovation and the competitiveness of the economy and can also support activities aimed at improving the efficiency of resource use in the economy or reducing the negative impact of human activity on the environment.

Increasing spending on R&D is one of the EU’s priorities, which also requires the involvement of the private sector in R&D investment. Increasing the share of the business sector in funding R&D contributes to relieving the burden on national budgets and increasing the applicability of research results. High- and medium-technology production and knowledge-intensive services require high-quality labor resources that are scarce on the labor market. The knowledge of a highly skilled workforce determines competitiveness and innovation. The number of patent applications filed reflects the ability to adapt knowledge and innovation in economic practice. Patents form the basis for efficient knowledge management in the technical and technological sphere and support the development potential of an innovative economy. The research and innovation spheres are better developed in Western European and Scandinavian countries, where there are greater funding opportunities, compared to Central and Eastern Europe.

In Area V, monitoring global balance and stability (variables X₁₉–X₂₁), similarly to Area II, i.e., waste management, a much weaker dispersion strength was observed. The highest variation of 48% occurred for the dependence of EU countries on material imports (variable X₂₁). The study found that Luxembourg was the country with 90% dependence on material imports. The dispersion of GHG emissions from production activities in EU countries (indicator X₂₀) was 33%. The highest GHG emissions from manufacturing activities were recorded in Germany (12,913 kg/person), against an EU average value of 7183 kg/person. GHG emissions are positively correlated with the GDP size. In terms of GHG emissions from production activities, the Baltic States have made good progress by investing in the energy market, among other things. The lowest variability in Area V in the EU countries was found for the consumption footprint (X₁₉). The lowest consumption footprint was recorded in Ireland (90%) and the highest in Malta (144%).

The values of the relative measure of the CLE development calculated for the EU-27 countries and an assessment of their situation are presented in

Table 4. Relative taxonomic development indicator value and assessment in 2013 and 2022.

Development Level	Indicator Value zi (2013)	Indicator Value zi (2022)
Very good	France (0.455), Germany (0.443), Italy (0.434), Spain (0.397), The Netherlands (0.354)	France (0.475), Italy (0.394), Spain (0.351), Germany (0.343)
Good	Belgium (0.281), Sweden (0.277), Austria (0.267), Poland (0.266), Czech Republic (0.255)	Poland (0.289), The Netherlands (0.279), Sweden (0.246), Czech Republic (0.232), Croatia (0.214), Slovakia (0.206), Belgium (0.205)
Sufficient	Hungary (0.223), Croatia (0.210), Latvia (0.208), Slovakia (0.197), Greece (0.194), Slovenia (0.183), Romania (0.168), Ireland (0.163), Lithuania (0.163), Cyprus (0.160), Denmark (0.156), Bulgaria (0.135), Portugal (0.133)	Denmark (0.129), Ireland (0.169), Estonia (0.131), Greece (0.193), Cyprus (0.171), Portugal (0.133), Latvia (0.181), Austria (0.159), Lithuania (0.165), Romania (0.168), Slovenia (0.143), Hungary (0.191)
Unsatisfactory	Finland (0.108), Malta (0.083), Luxembourg (0.055), Estonia (0.005)	Bulgaria (0.106), Finland (0.092), Malta (0.060), Luxembourg (0.001)

Source: author’s own elaboration based on Eurostat data, 2025.

. In EU countries, the average value of the relative taxonomic measure of the CLE development in 2022 was 0.2018 and the standard deviation was 0.1009. The ranges obtained from the calculations were used to classify the EU countries in terms of the degree of implementation of the circular economy: Group I—the most favorable situation—is a relative measure of the CLE development of z_i > 0.303. Group II—a favorable situation of 0.202 < z_i ≤ 0.303. Group III—a less favorable situation of 0.101 < z_i < 0.202. Group IV—the least favorable situation of z_i ≤ 0.101.

Receiving between 0.475 and 0.343 index values on a scale of (0, 1), respectively, France, Italy, Spain, and Germany enjoyed the most favorable situation in terms of CLE implementation among the 27 EU countries surveyed in 2022 (Figure 1).

These countries had (on average per group) the lowest material footprint of 12.3 t/person, the highest resource productivity of 3.1 euro/kg, and a closed-loop material use of 15.2% (

Table 5. Average circular economy indicators in EU countries in four development classes in 2022.

Circular Economy Indicators	Group I	Group II	Group III	Group IV	Total
Material footprint t/person	12.3	15.6	20.4	29.4	19.3
Resource productivity * euro/kg	3.1	2.1	1.5	2.0	1.9
Waste generation kg/person	3843	5803	4928	13,681	6291
Waste generation excluding mineral waste per unit GDP kg/thousand euro	53.7	83.3	103.5	156.0	98.7
Generation of municipal waste kg/person	523.3	492.4	535.8	587.3	533.3
Generation of packaging waste kg/person	207.7	137.9	154.9	153.6	138.2
Generation of plastic packaging waste kg/person	39.0	28.8	35.2	28.9	33.2
Recycling rate of municipal waste * %	50.6	45.7	37.6	33.9	41.1
Packaging waste recycling rate * %	69.3	67.4	58.7	56.8	62.2
WEEE recycling rate of waste electrical equipment * %	79.0	83.3	78.7	83.7	80.7
Closed-loop material use * % recycling rate	15.2	13.9	6.8	9.3	10.3
Trade in raw materials for recycling * million t	3.9	1.9	0.83	0.1	1.5
Private investment and gross value added in the CLE sectors * million euro	17,611	3417	1366	504	4176
People employed in the CLE sectors * thousands FTE	561.2	133.1	69.8	41.7	156.8
Patents related to recycling and secondary raw materials * per 1 million people	28.9	6.8	2.1	4.3	8.0
Consumption footprint %	107.5	112.6	107.4	124.0	111.2
Greenhouse gas emissions kg/person	5612	6844	7378	8764	7183
Material import dependency %	41.9	45.5	32.9	48.8	39.9

* CLE stimulants. Source: own calculations.

). The average private investment and gross value added in the CLE * sectors in Group I amounted to EUR 17,611 million and differed significantly from the other groups. Also, the highest number of people were employed in the CLE sectors and the highest number of patents related to recycling and secondary raw materials were implemented—28.9 per million people. Although developed countries (Group I) achieved the highest average rate of packaging waste of 207.7 kg/person and plastic packaging of 39 kg/person, they also achieved the highest average recycling rate, both of packaging waste (69.3%) and municipal waste (50.6%). It should be noted that Group I also had the lowest average annual greenhouse gas emissions of 5612 kg/person.

A favorable situation (Group II) in circular economy adaptation was observed in seven countries, the Netherlands, Belgium, Sweden, Poland, Slovakia, Croatia, and the Czech Republic, which obtained index values ranging from 0.289 to 0.205. The average values of most the CLE indicators were found to be less favorable than in Group I but more favorable than in Group III. The exceptions were the generation of municipal waste (492.4 kg/person) and the generation of packaging waste and plastic packaging (28.8 kg/person), which proved more favorable in Group II than in Group I. The Netherlands had the lowest EU indicator (X₁) of the material footprint and the highest resource productivity (X₂), closed-loop material use (X₁₃), and trade in recyclable raw materials (X₁₅).

Barriers to the transition from a linear to a circular economy (Group III) were observed in 12 EU countries. This group proved to be the most numerous and included Denmark, Ireland, Estonia, Greece, Cyprus, Portugal, Latvia, Austria, Lithuania, Romania, Slovenia, and Hungary. The indicator values obtained in this group ranged from 0.193 to 0.129. The lowest average values in all the groups were found for resource productivity (1.5 euro/kg) and the use of closed-loop materials (6.8%). In addition, these countries implemented the fewest patents related to recycling and secondary raw materials (2.1 per million people), which translated into the lowest recycling rate of waste electrical equipment in the groups.

The greatest difficulties in implementing the CLE among the EU countries surveyed in 2022 were observed in four countries (Group IV): Bulgaria, Finland, Luxembourg, and Malta. The value of this indicator ranged from 0.106 to 0.001. In the case of Finland, the lowest EU circular economy indicators occurred in the group monitoring production and consumption. The highest EU waste production per capita of 19,950 kg, with an EU median of 4604 kg, and the highest material footprint of 50.6 t/capita, with an EU average of 19.3 t/capita resulted in the highest average values of these indicators in Group IV. In contrast, Malta’s score was the worst in the case of indicators relating to competitiveness and innovation, with the fewest people employed in the CLE sectors and a lack of patents related to recycling and secondary raw materials resulting in the lowest recycling rate of packaging waste (31.8), against an EU average of 62.2. Bulgaria recorded the lowest resource productivity in the EU at 0.3 Euro/kg, against an EU average of 1.9 Euro/kg. Luxembourg, on the other hand, was the most dependent (90%) on imported materials. Luxembourg is a country with a high level of socio-economic development and a service economy, but the dynamics of change proved too weak compared to other countries.

The case of Finland—a country considered a leader in environmental policy—is particularly interesting. In spite of its advanced environmental policy, Finland scored among the lowest in the survey of the level of the development of the closed-loop economy (CLE). Among the main reasons for this are the high material intensity of the economy, the highest per capita waste generation in the EU, and the dominance of raw materials and heavy industry sectors. Although environmental policies are advanced, the structure of the economy based on, among others, forestry, cellulose production, energy, and mining is highly material-intensive. This study does not ignore this fact, but its impact is directly reflected in indicators such as material footprint and waste production. The example of Finland shows that advanced environmental policy does not always translate into high CLE rates if it is not accompanied by restructuring economic sectors, the reduction of material intensity in industry, and the increased use of secondary raw materials. CLE policies should be complementary to industrial and energy policies and not operate in isolation from them. Otherwise, even environmentally friendly countries may perform poorly in comparisons if they are dominated by energy- and material-intensive sectors.

Analyzing the dynamics of change over the last 10 years in the EU-27, a slow development was observed in the transition from the linear to the circular economy. Only 8 of the 27 countries showed an increase in their development index (Figure 2). Among the countries from Group I of the CLE development in 2022 (the most favorable situation in the EU countries), only France recorded a 4.5% increase in the indicator. In Group II (a favorable situation), which included seven countries, an increase in the development indicator occurred in the case of three countries: Poland—8.5%; Slovakia—2.3%; and Croatia—2.3%. This was the most numerous group.

Group III (a less favorable situation), an increase in the development index of the circular economy occurred for 4 out of 12 countries. The highest increase in the CLE in the 10-year period under review was seen in Estonia. An increase in Group III also took place in Cyprus, of 6.8%, and in Ireland, of 3.8%, and there was a slight 1% increase in Lithuania. In contrast, in 2022, there was no incline in the CLE indicator in the countries from Group IV (the least favorable situation).

Analyzing the changes that took place over the decade in the EU countries, based on the synthetic indicator of the CLE development, one could observe a transition of some countries to neighboring development groups (Figure 3). A move to a higher development group was seen in the case of Estonia. The transition was from Group IV (the value of the indicator was 0.005 in 2013) to Group III (the value of the indicator went up to 0.127 in 2022). A similar situation took place in the case of Slovakia and Croatia, where there was a transition from development Group III (2013) to Group II in 2022 (a favorable situation). In contrast, a decrease to a lower development group in 2022 was recorded in the case of the Netherlands, which was a Group I country in 2013. In contrast, Austria recorded a decrease from Group II in 2013 to Group III. Bulgaria joined Group IV in 2022.

The inequality of development is a challenge for EU cohesion. The results show a significant development gap between Group I–II countries (France, Germany, the Netherlands, and Italy) and Group III–IV (Bulgaria, Malta, Latvia, Poland, and the Czech Republic). Such polarization threatens the political cohesion of the European Union, exacerbates economic inequalities, and undermines the effectiveness of common the CLE and Green Deal policies. Hence, the following policy recommendations are suggested for Group III and IV countries (Central and Eastern Europe): the creation and implementation of national CLE strategies (taking into account the national specificities of the construction, energy, and agricultural sectors), priority support for innovation and eco-technology, investment in environmental education and awareness, the expansion of waste infrastructure and selective collection, and policies targeting the material-intensive sector. This primarily involves support for green building, efficient agriculture and energy transition, and the introduction of taxes on primary resources or incentives for the use of secondary raw materials. In order for Group III and Group IV countries to successfully narrow the CLE development gap, they need to move from adapting EU solutions to their own integrated transformation policies. Specific financial and technological support mechanisms are needed, taking into account their starting point. The future of the CLE in the EU depends on a parallel political, educational, and infrastructural—not only economic—transformation.

Over a period of 25 years, differences in the GDP per capita among the EU’s “28” decreased by 18 percent. However, the financial crisis of 2008–2010 reduced the pace of differences. The outbreak of the COVID-19 pandemic in 2020, on the other hand, even reversed this trend, and differences began to widen again. The blurring of developmental differences is mainly due to the rapid growth of the economies of countries from Central and Eastern Europe. These countries grew at an annual rate of 3.1 percent between 1995 and 2020, more than three times faster than Central Europe. The Baltic countries recorded the highest growth. The situation is different in the southern countries, whose stagnation has contributed to the emergence of a “two-speed Europe”.

The indicators used in the study show a statistical picture, but understanding their deeper causes requires taking into account structural, institutional, and technological determinants that are key to understanding the actual pace of circular transformation in EU countries. These should include structural differences between economies as a root cause of performance, inconsistencies and variations in national CLE policies, technological and innovation barriers as brakes on transformation, and the problem of reverse causality. The results of the CLE index reflect, to a large extent, structural conditions, the availability of technology, and the level of political commitment but do not always allow for a clear attribution of causality. Therefore, the assessment of progress in the circular economy should be complemented by qualitative analyses that take into account national CLE strategies, sectoral structures, real investment and technological opportunities, and the social and educational contexts.

This study covered 27 EU countries and showed significant variation in the level of the CLE implementation and the slow progress of the transformation over a decade (2013–2022). The results are in line with the observations of Kirchherr et al. [81], who highlighted the systemic barriers and uneven pace of CLE adaptation in Europe. In contrast, Geissdoerfer et al. [3], in their review, highlighted that CLE implementation does not automatically translate into the achievement of sustainable development goals. The convergent studies described in this thesis indicate that only a small number of countries have shown significant progress, and that the level of convergence in the EU remains low—suggesting the poor integration of the CLE into development policy at the community scale. In contrast, Lieder and Rashid proposed a model of industrial transformation based on the CLE, requiring high levels of innovation. The research conducted by the authors of this article confirms this relationship, with the countries with the highest levels of investment in the CLE sector and the highest number of patents (e.g., Germany) obtaining the highest values for the development measure. The roles of environmental education and citizen engagement were also highlighted. Similar conclusions were reached by Prendeville et al. [82], indicating that the effectiveness of CLE implementation depends on the synergy between technology, policy, and public awareness. In contrast, Korhonen et al. [83] highlighted the risk of superficial CLE implementation, without considering the product life cycle. Therefore, in this study, the authors have included a more holistic view of the CLE, through an extensive analysis of indicators (including the material footprint, CO₂ emissions, and employment).

The study carried out in this thesis on assessing the implementation of the circular economy in the EU-27 finds significant support in the global literature, confirming both the methodologies undertaken and the variations observed. This paper uses a relative taxonomic measure of development based on Eurostat indicators and beta and sigma convergence analyses. This quantitative, comparative methodology finds a parallel in the research of Lieder and Rashid, who also advocated the creation of comprehensive systems for assessing CLE implementation based on production and environmental indicators [6].

In contrast, Geissdoerfer et al. pointed out that the transition to the CLE can support sustainable development but does not guarantee it [3]. The convergent study in this thesis indicates that the transition is slow, and differences between countries are widening, limiting the effectiveness of common policies. Prendeville et al. [82] analyzed circular cities and highlighted the role of synergies between public policies and innovation. Similar conclusions were drawn from an analysis of the performance of the group of countries with the highest the CLE rates, where innovation and private investment are significantly higher [82]. In contrast, Kirchherr et al. [81] identified barriers to CLE implementation, including a lack of regulatory support and limited awareness among policy makers—these are also factors identified in this article when discussing the lowest ranked EU countries (Malta, Bulgaria, and Luxembourg). Korhonen et al. [83] highlighted the need for uniform indicators and life cycle assessments. This concept was also applied in this study through a taxonomic analysis of 18 differentiated variables, including material efficiency, recycling, greenhouse gas emissions, and employment in the CLE sector. The results show that countries such as France, Italy, and Germany have the highest degree of CLE implementation (high resource productivity, the number of patents, a low material footprint), while Malta, Finland, and Bulgaria have the lowest. At the same time, the authors, as advocated by Geissdoerfer and Korhonen [3,83], emphasize the need for national roadmaps and multi-level policy coordination.

However, the taxonomic method used in this research has limitations. The limitations of future research on the circular economy include the large variation in the level of development between EU countries (the results showed significant differences in the CLE indicators, which makes it difficult to generalize and formulate uniform strategies for the whole EU), the lack of uniform methods to measure the effectiveness of the CLE (there is a need for the further development of indicators to enable a comprehensive assessment and the comparability of progress), the low level of development convergence (despite the common EU policy, increased processes of polarization rather than the levelling of CLE development were observed), limitations of the statistical data (some variables were excluded from the analysis due to too little variation or low information values), and low levels of innovation in some countries (a lack of patents and weak R&D activity limit the potential for transformation towards the CLE).

At the same time, there are opportunities for future research concerning, for example: the differentiation of transformation strategies, the use of more comprehensive statistical models, research from a regional and local perspective, and the integration of social and technological aspects (future research may combine the CLE with digitalization, social innovation and environmental education).

Among the application possibilities of the study carried out are: the ranking of EU countries (the developed taxonomic indicator allows us to assess the degree of progress of the CLE and can be used as a benchmarking tool for policy makers), public policy making (the results of the study can support the EU and member states in creating tailored financial and regulatory interventions), support for small and medium enterprises (the results indicate the need to support these enterprises in adapting to the CLE requirements, e.g., through grants or training programs), indicators for monitoring the effectiveness of public investments (they can be used to assess the effectiveness of the use of EU funds for circular transformation), and strategic planning (the results indicate the need to support these enterprises in adapting to the CLE requirements, e.g., through subsidies or training programs), indicators to monitor the effectiveness of public investments (can be used to assess the effectiveness of the use of EU funds for circular transformation), and strategic planning (the models developed can be used by national and local authorities to design sustainable economic development plans).

A closed-loop economy has the potential to significantly reduce GHG emissions by reducing the extraction and processing of primary raw materials (which are carbon intensive), the production of new materials (e.g., steel, concrete, plastics), international transport and complex supply chains, and food and energy waste (which contribute to methane and CO₂ emissions).

The studies discussed here capture GHG emissions as a key destimulant in the construction of the CLE index. A lower per capita emissions value (X₂₀) translates directly into a higher level of sophistication of the circular economy. Examples include France (5612 kg CO₂/person) and the Netherlands (6000 kg/person), both of which achieved high CLE rankings due to, among other things, effective emission reduction strategies in industry and waste management.

The European Commission is undertaking a number of policies that closely link the CLE to decarbonization (and GHG emission reductions); in particular, these are the European Green Deal (target: climate neutrality by 2050), the Fit for 55 Package (aims to reduce GHG emissions by at least 55% by 2030 from 1990 levels), and the Circular Economy Action Plan (provides for digital product passports, extended producer responsibility, and the promotion of markets for secondary raw materials). The CLE influences the reduction of the carbon footprint by promoting shorter production and consumption cycles, lower primary energy consumption, and less need for emitting materials (cement, steel, plastics). The per capita GHG emission factor included in the study (X₂₀) is one of the measurable components of a country’s carbon footprint. The EC is trying to combine climate and raw material policies (e.g., through the Green Deal) to reduce the carbon footprint not only of the energy sectors but also of the materials and manufacturing sectors. CO₂ per capita indicators can serve as a measure of the effectiveness of national circular and climate policies.

5. Summary

The research shows that changes occur at different rates and scales in different EU countries. One indicator of these changes may be the development of the circular economy. The lowest variability was found for the recycling rate of waste electrical equipment (variable X₁₂) and the consumption footprint (X₁₉).

Based on the CLE indicators, there are significant differences in the level of development of EU countries. These differences are due to a number of factors influencing the possibilities for raising funds and the directions in which they are spent. Due to the different levels of development of the countries studied, a separate circular economy development strategy should be built for each of them. An analysis of the disparities and the familiarity with strengths and weaknesses can guide action to develop the circular economy in the countries studied. In the EU27, France achieved the highest level of the CLE development (0.475 index value) and Luxembourg the lowest (0.001 index value).

The calculated values of the relative taxonomic measure of the CLE development indicate that the EU-27 countries are mostly characterized by a sufficient level of circular economy development. Moreover, the differentiation characterizing the EU countries is widening, as the polarization processes occurring are more extensive compared to diffusion processes. Reducing development disparities within the EU should be a priority for the EU authorities. EU countries need to be supported to a greater extent by transfers from the EU budget to develop and fulfil tasks assigned to them. The budget revenues received determine the financial capacities of states, mainly in terms of investment expenditure. This is all the more important as countries are poorly equipped with infrastructure facilities, which results in the need for specific investment expenditures to improve living conditions in rural areas and increase investment attractiveness and competitiveness.

The economies of the EU member states are different from each other, and as a result, there is not just one right model for the transformation towards the CLE suitable for all of them. Therefore, the conclusions of the June 2016 meeting of EU Environment Ministers proposed that member states (following the European Commission) should develop national programs for the transformation towards the CLE. This is essential if such an economic development model is to be implemented at all levels, from the EU, through the member states, to the provinces and municipalities. The aforementioned document should be a mandatory scope of action at the national level. In the case of Poland, the national map for the development of the circular economy is one of the strategic projects (the so-called Strategy for Responsible Development—SOR) and is part of the overall vision of the country’s development. These include the imbalance of raw material markets and price competition among exporters, which may lead to weakening the development dynamics of the global economy. The EU actions should aim for creating opportunities for the development of the circular economy in the poorest countries in order to even out development disparities at the EU level. CLE indicators should also be used for modeling rural areas, so that the development carried out there could, to a large extent, reflect the implementation of sustainable development principles.

6. Conclusions

This study found significant differences between the EU27 countries in terms of the level of progress in implementing the circular economy (CLE). Western European countries (France, Germany, and Italy) are best developed in this respect, while Central and Eastern Europe and peripheral countries (e.g., Bulgaria, Malta, and Luxembourg) lag behind. Only 8 of the 27 member states have recorded an increase in the CLE development index, confirming the slow pace of transition from a linear to a circular model. Given the considerable economic and structural diversity, the authors recommend building separate CLE development strategies for each member state, tailored to its potential and barriers. The highest values of the CLE indicators were found in countries characterized by high R&D expenditures, a high number of patents, and high employment in the CLE sector, indicating a direct link between innovation and the effectiveness of circular transformation.

The use of a relative taxonomic measure of development and β- and σ-type convergence analyses provided an objective, comparable picture of changes in the CLE, while offering a tool for ranking and public strategies. This study showed that polarization processes dominate over diffusion processes in the implementation of the CLE in the EU, implying a widening gap between developed and less-developed countries. The authors identified areas such as raw material efficiency, recycling, packaging waste management, and greenhouse gas emissions as key to successful CLE implementation and requiring further legislative and investment support.