1. Introduction
Climate change, resource scarcity, and rising energy prices drive economic actors, especially businesses, to focus on efficiency and sustainability. In response to these concerns, in 2015, the European Commission implemented its first action plan for a Circular Economy. This plan aimed to transform the traditional linear economic model into a circular model, promoting the recycling and reuse of products to generate environmental benefits, reduce negative externalities, and enhance business benefits.
Economic growth in recent decades has been described as unsustainable (Ghisellini et al., 2016), largely because it is based on a linear model. This type of model uses resources and raw materials discarded at the end of the production process, leading to a very negative environmental impact. By contrast, the Circular Economy model aims to replace the linear economy in production and consumption systems, replacing the ‘use and throw away’ approach with one that seeks to minimize waste as much as possible (Christis et al., 2019; Turcu and Gillie, 2020).
This Circular Economy concept is closely aligned with several of the Sustainable Development Goals (SDGs) adopted in 2015 by UN member countries, such as SDG 12, Responsible production and consumption’, and SDG 13, ‘Climate action,’ in which both producers and consumers play a crucial role. Indeed, the Circular Economy is a key instrument for achieving these goals.
However, achieving a Circular Economy requires a series of changes in production processes, either by increasing energy efficiency or reusing materials. The transition from a linear to a Circular Economy has become a political priority at both the international and local levels, and this has led to the enactment of legislation to drive companies to change their production processes.
The Circular Economy Action Plan initially focused on ecological and economic issues (
European Commission, 2015, 2020). Nevertheless, the European Union currently finds itself in a complex geopolitical landscape (Baldassarre, 2025). As a result, some industries have been experiencing a scarcity of basic resources and problems with their energy supply in recent years. In response, the European Parliament reacted to The Critical Raw Materials Act (
European Parliament and Council, 2024).
The business sector is responding accordingly, both to comply with current legislation and to reduce costs, prompted by growing awareness of the need for environmental sustainability and to reduce their dependence on international suppliers. In this context, it is especially important to understand the companies’ current situation, to identify the initiatives they are implementing, the obstacles they face in the transition towards sustainable production, and, above all, whether environmental administrations and legislation act as facilitators or barriers to achieving sustainable economic growth.
In this study, we focus on small and medium-sized enterprises (SMEs) in countries that comprise EU-27. Although European SMEs have limited environmental impact at the individual level, they account for 63.3% of the total CO2 emissions in Europe, according to the European Commission’s annual report on European SMEs 2021/22 (2022b).
Understanding business behavior in this area and the difficulties and challenges they face is essential to implement appropriate policies to incentivize the reduction of these negative externalities.
Studies on SMEs and sustainability, such as Chatzistamoulou and Tyllianankis (2022), identify factors that influence firms to implement and commit to renewable efficiency actions. A similar approach was adopted by Vasilescu et al. (2023), although their study focused on entrepreneurship and the supply of green products and services.
Unlike studies that analyze the factors that influence companies’ decisions to adopt more environmentally sustainable policies, this study focuses on the current situation. As such, it has a twofold objective: on the one hand, to analyze the responses of companies by country to the environmental measures proposed in the EU regulation, and on the other hand, to categorize companies in terms of the actions taken in response to these environmental measures on a country-by-country basis.
The remainder of this paper is organized as follows. In Section 2, we examine the methodology used; this, in turn, is divided into two parts. First, we set out the database used and the descriptions of the sample, and then we analyzed the clustering methodology used to categorize the companies. In Section 3, we consider the results, and in Section 4, we present the discussion and conclusions.
2. Methodology
In this study, we used data from the latest wave of the ‘SMEs, resource efficiency, and green markets’ survey, selecting European Union member states. This data is published as Flash Eurobarometer 498. SMEs, Resource Efficiency and Green Markets, wave 5 (2022a) First, we provide a descriptive overview of the survey data. We then identified the variables to be analyzed before performing a K-mode clustering analysis to categorize the companies.
2.1. Description of the data
We used the ‘SMEs, resource efficiency, and green market surveys as the basis for our analysis of European SMEs. The data used were from the latest wave of the survey, the fifth wave, which covers November and December 2021.
We selected companies from 27 European Union member states. After the database was cleaned, 14,008 enterprises were included in the sample. The survey data were weighted according to the SME population in each country. Below, we can see the main characteristics of the data used: distribution of the number of companies by country, age of the companies, main productive sector by country, distribution of the size of the companies by country and, finally, the type of client they target.
Table 1 shows the distribution of the number of companies in the database by country.
Table 1. Number of companies per country that have answered the survey.
| Country | No. Firms | Country | No. Firms | Country | No. Firms | Country | No. Firms |
|---|
| Austria | 509 | Finland | 498 | Latvia | 503 | R. of Cyprus | 252 |
| Belgium | 587 | France | 599 | Lithuania | 499 | Romania | 609 |
| Bulgaria | 514 | Germany | 560 | Luxembourg | 248 | Slovakia | 496 |
| Croatia | 546 | Greece | 601 | Malta | 255 | Slovenia | 554 |
| Czechia | 596 | Hungary | 529 | Netherlands | 602 | Spain | 597 |
| Denmark | 492 | Ireland | 472 | Poland | 607 | Sweden | 593 |
| Estonia | 505 | Italy | 599 | Portugal | 586 | | |
With regard to the age of the companies, we can observe that in 52% of the EU countries, the companies established after 2010 (considered the youngest) constitute the majority of respondents to the survey. The longest-established companies represented only 4% of the base, as shown in
Table 2.
Table 2. Percentage of companies in the base by date of creation.
| Established before 1970 | Established between 1970 and 1990 | Established between 1990 and 2010 | Established after 2010 |
|---|
| 4%
| 15%
| 30%
| 52%
|
The survey allowed us to distinguish between the different production sectors. We can see that the predominant sector is G (wholesale and retail trade and repair of motor vehicles and motorbikes) across all countries except Sweden and Estonia, where C (manufacturing) predominates.
Table 3 shows the percentages for each productive sector.
Table 3. Productive sector by percentage.
| PRODUCTIVE SECTOR |
% |
|---|
| B - Mining and quarrying | 1.05% |
| C – Manufacturing | 20.21% |
| D - Electricity, gas, steam and air conditioning supply | 1.86% |
| E - Water supply, sewerage, waste management and remediation activities | 1.51% |
| F – Construction | 17.25% |
| G - Wholesale and retail trade, repair of motor vehicles and motorcycles | 28.16% |
| H - Transportation and storage | 7.25% |
| I - Accommodation and food service activities | 6.49% |
| J - Information and communication | 5.14% |
| K - Financial and insurance activities | 3.17% |
| L - Real estate activities | 2.38% |
| M - Professional, scientific and technical activities | 5.54% |
We analyzed the invoicing of companies in the survey from a triple perspective. First, we looked at the sums invoiced; second, we looked at the recipients – that is, who is being invoiced – and, third, at what is being invoiced (whether it is a service, a production, or both).
Regarding the sums invoiced, we observe in
Table 4 that in countries such as Sweden, Denmark, and Belgium, there is a significant presence of companies invoicing more than 50 million.
Table 4. Distribution of companies by country with a turnover of over 50 million euros.
| Country | No. Firms | % of firms
< 2 m € (1840 firms) | % overall on each country |
|---|
| Greece | 424 | 5% | 71% |
| Latvia | 406 | 5% | 81% |
| Malta | 188 | 2% | 74% |
| Romania | 461 | 6% | 76% |
| Slovakia | 361 | 4% | 73% |
|
TOTAL
|
1840
|
23%
| |
In contrast,
Table 5 shows the countries with the smallest companies, with an average turnover of less than 2 million.
Table 5. Distribution of firms by country with turnover below 2 million euros.
| Country | No. Firms | % over those >50 m € (433 firms) | % overall in each country |
|---|
| Belgium | 54 | 12% | 9.2% |
| Denmark | 55 | 13% | 11.2% |
| Sweden | 55 | 13% | 9.3% |
|
TOTAL
|
164
|
38%
| |
The geographical concentration of the companies with the highest turnover is noteworthy. The 164 companies with a turnover of more than €50 million were located in Sweden, Denmark, and Belgium, although only 1% (164/14008) of the entire base of companies surveyed accounted for 38% (164/433) of all companies with a turnover above this amount. For example, in Sweden, 9.3% of all companies surveyed reported a turnover of more than €50 million, constituting 13% of all European companies with a turnover of more than €50 million.
Regarding the companies reporting the lowest turnover (below €2 million), those in Greece, Latvia, Malta, Romania, and Slovakia accounted for 13% (1840/14008) of the surveyed company base, as shown in
Table 5, while they accounted for 23% (1840/8069) of all companies with a turnover below this amount. For example, in Latvia, 81% of the surveyed companies had a turnover below EUR 2 million, but only 5% of all European companies had a turnover below this threshold.
For the typology of customers, we studied companies according to their main client base. The questionnaire answer options were as follows: all to the public administration; all to other companies; to other companies and the public administration; directly to consumers; directly to consumers and the public administration; directly to consumers and other companies; directly to consumers; and to other companies and the public administration.
We find that, across all countries, a higher percentage of companies do not have the government as a customer. However, this distribution was not symmetrical.
Figure 1 shows that in Finland and Sweden, the percentage of companies that have public administration as a customer is as high as 40%, while in Portugal and Bulgaria, this percentage is less than 20%.
Figure 1. Percentage of businesses by country contracting with public administration.
Source: Own elaboration.
Finally, in terms of invoicing,
Table 6 shows an even distribution between companies that sell only products, only services, or both.
Table 6. Number of companies that sell products, services or both.
| OUTPUT | No. Firms | % |
|---|
| Both products and services | 4669 | 33.33% |
| Products | 4416 | 31.52% |
| Services | 4923 | 35.14% |
| TOTAL | 14008 | 100% |
The distribution across the countries is shown in
Figure 2. For each country, the distribution of enterprises according to whether they sell products, services, or both, is shown as a percentage. Thus, Croatia and Finland companies that sell both services and products dominate. Italy and Portugal show a higher percentage of firms selling services only, while Malta and Cyprus stand out for selling products.
Figure 2. Distribution of the type of output sold by enterprises by country.
Source: Own elaboration.
2.2. Methodology
In the second stage, a clustering analysis is performed based on the distribution of the companies’ responses in each of the countries included in the database. This study identifies groups of companies according to their environmental policies and business characteristics using categorical variables. For this, we use the K-modes method,1 although in a different way to studies such as Gomonov et al. (2021), which use the K-means method. The K-mode clustering algorithm (Cao et al., 2009), an adaptation of the K-means algorithm, was specifically designed for clustering categorical data. The K-mode clustering method is an unsupervised machine learning technique used to group a set of data objects into a specific number of groups based on qualitative variables. The algorithm is called ‘K-modes’ because it uses modes (i.e., the most frequent values) instead of means or medians to represent the groups.
The qualitative business variables that we take into account for the K-modes analysis are six variables that characterize the companies (country and productive sector in which they operate, size, level of growth, type of product, and type of customer) and nine variables that reflect the environmental actions implemented by the 14008 companies in the database (all the variables are described in section 3.1).
In the third stage, we analyze the problems and requirements of firms to become more environmentally sustainable. This information is valuable for the optimal design of environmental policies. As such, we use the answers given by the companies in the survey to the following questions: “Did your company encounter any of the following difficulties when trying to set up resource efficiency actions?” and “Which of the following will help your company the most to be more resource efficient?”
3. Results
This section presents the results of this study. First, the analysis of the environmental actions carried out by the companies in the sample, taking into account the country in which they operate, allows us to identify in which country each action predominates. Second, we analyze the clustering results by identifying groups of companies and their characteristics. Finally, we detect the difficulties experienced by companies and support that they need to be sustainable and identify the differences between the clusters.
3.1. Environmental actions carried out by companies in each country
We then analyzed the actions that companies take to make their resources more efficient and thus avoid negative externalities in the environment. The actions are classified according to the following list: saving water (AA); designing products that are easier to maintain, repair, or reuse (DP); recycling, reusing materials or waste within their company (R); selling their waste and residues to another company (VR); minimizing waste (MR); switching to greener material suppliers (PROV); saving energy (AE); saving materials (AM); using predominantly renewable energy (including own production with solar panels, etc.) (ER); other; or none.
Table 7 shows the number of actions developed by companies according to country. Thus, we can see which type of activity each country focuses more on. It can be seen that, in general, waste minimization (MR) and/or energy saving (AE) actions predominate in all countries. In general, countries show homogeneous behavior. There are some exceptions, such as Ireland and Portugal, where recycling is prioritized and Malta, where material and water savings are prioritized. If we look at Spain, its focus is to minimize waste and save materials, but what is most striking is that it is the country where water conservation has the highest priority. 72.19 Of the Spanish companies, 72.19% saved water, a higher percentage than in other countries for this action.
Table 7. Percentage of a given action across all companies in a country.
| AA | DP | R | VR | MR | PROV | AE | AM | ER | Others | None |
|---|
| Austria | 44.99% | 23.18% | 47.94% | 29.67% | 65.62% | 29.86% | 66.21% | 54.81% | 31.43% | 0.39% | |
| Belgium | 55.03% | 32.71% | 46.51% | 46.00% | 83.48% | 45.49% | 76.32% | 65.93% | 45.66% | 3.07% | |
| Bulgaria | 25.10% | 9.92% | 24.51% | 28.60% | 39.88% | 13.81% | 42.02% | 30.93% | 9.14% | 5.06% | |
| Croatia | 44.87% | 22.71% | 35.90% | 38.28% | 68.13% | 26.37% | 56.59% | 52.38% | 10.07% | 0.18% | |
| Czechia | 47.99% | 35.91% | 47.48% | 39.43% | 74.50% | 33.56% | 64.60% | 57.21% | 13.59% | 0.67% | |
| Denmark | 29.88% | 23.98% | 31.10% | 25.41% | 43.29% | 28.66% | 54.67% | 38.01% | 22.97% | 5.08% | |
| Estonia | 32.28% | 20.99% | 34.26% | 30.30% | 51.49% | 24.55% | 51.68% | 51.88% | 12.67% | 0.40% | |
| Finland | 36.14% | 31.33% | 47.19% | 31.73% | 69.08% | 35.74% | 65.86% | 65.26% | 26.91% | 2.41% | |
| France | 40.07% | 27.38% | 47.75% | 30.88% | 55.43% | 28.05% | 47.25% | 41.24% | 10.18% | 1.50% | |
| Germany | 41.25% | 27.50% | 48.75% | 33.04% | 58.21% | 38.04% | 71.07% | 53.39% | 37.86% | 1.07% | |
| Greece | 39.77% | 28.79% | 45.26% | 33.78% | 52.58% | 42.10% | 56.41% | 55.91% | 15.97% | 0.50% | |
| Hungary | 55.77% | 29.68% | 36.11% | 35.16% | 66.16% | 31.00% | 73.91% | 64.27% | 23.25% | 0.95% | |
| Ireland | 28.18% | 15.25% | 53.60% | 11.44% | 50.85% | 30.93% | 40.47% | 25.64% | 12.71% | 1.91% | |
| Italy | 42.40% | 23.21% | 45.08% | 25.21% | 82.97% | 32.89% | 61.94% | 59.43% | 26.21% | 1.17% | |
| Latvia | 38.17% | 23.66% | 24.25% | 28.63% | 46.52% | 27.63% | 57.65% | 55.27% | 5.77% | 2.39% | |
| Lithuania | 53.51% | 25.45% | 25.25% | 37.47% | 59.32% | 37.68% | 65.33% | 64.93% | 12.42% | 2.00% | |
| Luxembourg | 41.53% | 35.48% | 46.37% | 29.03% | 67.34% | 43.95% | 55.65% | 50.00% | 14.52% | 4.84% | |
| Malta | 49.02% | 21.18% | 43.53% | 23.92% | 49.80% | 38.43% | 41.57% | 49.41% | 27.84% | 3.92% | |
| Netherlands | 38.70% | 33.72% | 56.64% | 40.86% | 76.08% | 40.70% | 75.75% | 63.46% | 50.33% | 0.66% | |
| Poland | 50.25% | 17.63% | 31.30% | 30.97% | 57.50% | 27.35% | 64.25% | 60.63% | 14.66% | 1.15% | |
| Portugal | 37.20% | 15.87% | 53.92% | 25.43% | 32.76% | 19.97% | 50.68% | 41.64% | 11.09% | 4.44% | |
| R. of Cyprus | 35.71% | 13.10% | 43.65% | 19.84% | 37.70% | 25.40% | 58.33% | 46.43% | 21.03% | 0.00% | |
| Romania | 63.88% | 35.80% | 44.17% | 45.32% | 76.03% | 45.98% | 70.61% | 73.07% | 11.00% | 0.82% | |
| Slovakia | 70.77% | 31.45% | 52.82% | 30.04% | 79.03% | 40.52% | 74.80% | 73.79% | 9.07% | 0.40% | |
| Slovenia | 36.28% | 23.29% | 39.89% | 38.27% | 63.72% | 38.81% | 54.87% | 47.83% | 17.51% | 2.35% | |
| Spain | 72.19% | 39.20% | 76.72% | 45.06% | 85.43% | 52.60% | 83.75% | 84.09% | 24.46% | 1.01% | |
| Sweden | 46.21% | 47.89% | 70.99% | 40.47% | 85.67% | 60.03% | 77.91% | 82.80% | 48.57% | 1.35% | |
Next, we focused on the overall set of shares.
Table 8 shows the average number of actions taken by companies in each country. Spanish companies report the highest number of actions on average (an average of 5.64 actions per company out of nine possible 9 actions), closely followed by Swedish companies (an average of 5.62 actions per company). At the other end of the scale, Bulgaria is the country where companies report the lowest average number of actions (2.29 actions per company).
Table 8. Average number of actions by companies in each country.
| Country | Firms per Country | Number of total actions | Number of total actions in average | Country | Firms per Country | Number of total actions | Number of total actions in average |
|---|
| Austria | 509 | 2006 | 3.94 | Latvia | 503 | 1559 | 3.10 |
| Belgium | 587 | 2936 | 5.00 | Lithuania | 499 | 1913 | 3.83 |
| Bulgaria | 514 | 1177 | 2.29 | Luxembourg | 248 | 964 | 3.89 |
| Croatia | 546 | 1941 | 3.55 | Malta | 255 | 889 | 3.49 |
| Czechia | 596 | 2473 | 4.15 | Netherlands | 602 | 2871 | 4.77 |
| Denmark | 492 | 1491 | 3.03 | Poland | 607 | 2159 | 3.56 |
| Estonia | 505 | 1568 | 3.10 | Portugal | 586 | 1717 | 2.93 |
| Finland | 498 | 2050 | 4.12 | R. of Cyprus | 252 | 759 | 3.01 |
| France | 599 | 1975 | 3.30 | Romania | 609 | 2842 | 4.67 |
| Germany | 560 | 2297 | 4.10 | Slovakia | 496 | 2295 | 4.63 |
| Greece | 601 | 2230 | 3.71 | Slovenia | 554 | 2010 | 3.63 |
| Hungary | 529 | 2202 | 4.16 | Spain | 597 | 3370 | 5.64 |
| Ireland | 472 | 1279 | 2.71 | Sweden | 593 | 3332 | 5.62 |
| Italy | 599 | 2399 | 4.01 | | | | |
We now group the nine actions into three figures (
Figures 3, 4, and 5) to analyze the performance of each country against each of the environmental actions studied.
Figure 3. Actions: 1. ‘Saving water’; 2. ‘Designing products that are easier to maintain, repair or reuse’; 3. ‘Recycling, by reusing materials or waste within their company’.
Source: Own elaboration.
Figure 4. Actions: 4. ‘Selling their waste and residues to another company’; 5. ‘Minimizing waste’; 6. ‘Switching to greener material suppliers’.
Source: Own elaboration.
Figure 5. Actions: 7. ‘Saving materials’, 8. ‘Saving energy’ y 9. ‘Using predominantly renewable energy (including own production with solar panels, etc.)’
Source: Own elaboration.
Regarding Action 1 (water saving), the results show that Spanish companies are the best performers, with 72.2%, closely followed by Slovakian companies. Bulgarian and Irish companies have the least importance for this action.
The objective of Action 2 ‘Design products that are easier to maintain, repair, or reuse is to move away from the attitude of the linear economy to avoid excessive waste that degrades the environment. However, this action is least directly related to economic savings. As can be seen, Swedish companies, with 47.9%, give most importance to this action.
Action 3 ‘Recycle, by using materials or waste within your company,’ also sees Spanish companies stand out. A total of 76.72% stated that they carried out this action, followed by Swedish companies in second place.
Figure 4 shows that Belgian companies stand out for Action 4 ‘Sell your waste and residues to other companies,’ with 46% of companies reporting that they sell their waste; Romanian companies occupy second place. Regarding Action 5 (minimize waste), Swedish companies again stood out at 85.7%. For Action 6 (switch suppliers of more environmentally friendly materials), Swedish companies again stand out at 60%.
For Action 7 (‘Save energy’) and Action 8 (‘Save materials’), Spanish companies were once again leading the way, showing 83.8% and 84.1%, respectively. For Action 9 ‘Use predominantly renewable energy (including own production with solar panels, etc.), Dutch companies stand out from the rest at 50.3%.
Taking into account the three types of actions for which Swedish companies stand out (designing products that are easier to maintain, reduce waste, and look for greener suppliers), we can deduce that companies in this country are more aware of environmental sustainability, as these actions do not in the first instance lead to savings in terms of cost, but can even reduce economic profitability.
On the other hand, Spanish companies give more importance to saving water, energy, materials, and to recycling. This suggests that they are more concerned with cost savings in order to increase their competitiveness.
3.2. Clustering analysis
Using the K-mode clustering method, we could differentiate the three clusters. Cluster 1 consists of 6,195 companies, Cluster 2 consists of 4,002 companies, and Cluster 3 consists of 3,811 companies. Before examining the relationship between the environmental actions carried out by the companies and the clusters, we performed a significance analysis before drawing up the contingency tables.
Table 9 summarizes the main characteristics of the three clusters. These are the number of enterprises contained in each cluster, the Circular Economy activities they carry out, whether they sell products and/or services, and the type of customers they target.
Table 9. Number of enterprises and characteristics per cluster.
| Cluster | Firms | Characteristics |
|---|
| Cluster 1 | 6195 | Saving energy (71.65%),
Minimizing waste (72.90%)
Selling services (43,04%).
Sell to other firms |
| Cluster 2 | 4002 | Saving energy (22.31%),
Recycling (29,51%)
None (21,14%)
Selling products (45,18%).
Selling directly to consumers |
| Cluster 3 | 3811 | Saving energy (89.50%),
Minimizing waste (91,13%)
Selling services and products (51,01%).
Selling to other companies, directly to consumers or to the public administration |
As shown in
Table 9, Cluster 1, consisting of 6,195 companies, is the largest cluster. The activities carried out by these companies in terms of sustainability were mainly energy saving (71.65% of the companies stated that they saved energy) and waste minimization (72.90% of the companies). They focus on selling the services to other companies.
The second group comprises 4,002 companies and is characterized by the fact that it is the group that performs the fewest actions. If we look at this group, the most common action is recycling, which is only carried out by 29.51% of the companies, followed by energy-saving (22.31% of the companies). In addition, 21.14% of the companies declared that they did not carry out any of the activities related to energy and/or resource saving. This cluster is also characterized by the fact that companies sell products to end consumers.
The third group, Cluster 3, was the smallest, consisting of 3,811 companies. It places the greatest emphasis on minimizing waste (91.13% of the companies) and/or saving energy (89.50% of the companies). It is more heterogeneous in terms of what they sell and to whom, as more than half of the companies sell services and products and their clients can be other companies, end consumers, or public administrations. This is the cluster in which companies declare more environmental actions, in contrast to Cluster 2.
According to Masi et al. (2018), CE initiatives can be carried out at three levels: the micro-, meso-, and macro-levels. They find evidence that most CE actions are at the micro level, and our findings concur with this. Micro-level initiatives refer to the 3R Principles: Reduce, Reuse, and Recycle. Meso-level initiatives refer to an inter-firm level, which in this study corresponds to actions 4 and 6: ‘Sell your waste and residues to other companies’ and ‘Switch to suppliers of more environmentally friendly materials.’ Macro-level initiatives cannot be checked directly in this survey, as they correspond to the government level.
Table 10 is a contingency table showing the relationship between the environmental variables and clusters, and the significance of these variables.
Table 10. Contingency table and significance.
| Actions | Cluster 1 | Cluster 2 | Cluster 3 | EST- Chi^2 | Cramer’s V |
|---|
| Minimizing waste | 72.90% | 21.94% | 91.13% | 4463.31 | 0.564 |
| Saving materials | 66.49% | 14.52% | 85.46% | 4428.93 | 0.562 |
| Saving energy | 71.65% | 22.31% | 89.50% | 4160.93 | 0.545 |
| Saving water | 40.02% | 16.44% | 82.29% | 3524.78 | 0.502 |
| Switching to greener suppliers of materials | 25.31% | 15.24% | 71.69% | 3194.86 | 0.478 |
| Selling your residues and waste to another company | 22.11% | 18.44% | 66.83% | 2678.89 | 0.437 |
| Recycling, by reusing material or waste within the company | 35.50% | 29.51% | 76.36% | 2128.94 | 0.390 |
| None | 2.57% | 21.14% | 0.00% | 1663.98 | 0.345 |
| Designing products that are easier to maintain, repair or reuse | 24.39% | 12.69% | 46.29% | 1156.07 | 0.287 |
| Using renewable energy | 20.48% | 10.79% | 33.61% | 610.88 | 0.209 |
Table 10 shows the relative weights, that is, the percentage of companies in each cluster that perform each of the different actions. For example, in Cluster 1, 72.9% of companies carried out the action of minimizing waste. In general, we can see that the companies in Cluster 3 are the most environmentally active because the percentage of companies participating in each of the actions is higher than that of the companies in the other two clusters. Extended data- Annex-1 presents the remaining contingency tables.
Table 10 also shows the significance of the environmental actions carried out by the companies used for our analysis. To collate this, we used the chi-square statistical test and Cramer’s V.
All Cramer’s V variables show a significant relationship with the cluster, except for the last two actions: designing products that are easier to maintain, repair, or reuse; and using renewable energy.
Table 11 shows our analysis of the significance of the relationship between the variables that characterize companies and their distribution by cluster.
Table 11. Significance table of the variables characterizing the enterprises.
| Other variables considered | EST- Chi^2 | Cramer’s V |
|---|
| COUNTRY | 2020.70 | 0.269 |
| OUTPUT | 1954.70 | 0.264 |
| TO WHOM DO YOU SELL | 1415.13 | 0.225 |
| PRODUCTIVE SECTOR | 1340.89 | 0.219 |
| SIZE | 1200.10 | 0.207 |
| REVENUES FROM LAST YEAR | 484.43 | 0.131 |
Here, the relationship between firm characteristics and cluster distribution is weaker. The two most significant characteristics are the country and the type of output they sell. The correlation tables for these variables are included in the extended data- Annex-1.
Finally, the previously analyzed clustering results can be mapped, showing which cluster predominates in each EU country.
The map in
Figure 6 shows the importance of each cluster for each country. Thus, Area A is composed of countries whose companies belong mainly to Cluster 1. In area B, we find the countries whose companies belong mainly to Cluster 2, and in C, we find those in Cluster 3. In areas X, Y, and Z, no single predominant cluster was observed. In area X, Clusters 1 and 2 were predominant. In area Y, Clusters 1 and 3 were predominant. In area Z, Clusters 2 and 3 show similar representations. To summarize, we represent countries by area in
Table 12.
Figure 6. Predominant clusters in each country.
Table 12. Distribution of countries by area.
| Area A | Area B | Area C | Area X | Area Y | Area Z |
|---|
| Austria | Bulgaria | Romania | Belgium | Czechia | Germany |
| Hungary | Croatia | Spain | Latvia | Finland | Slovenia |
| Italy | Denmark | Sweden | Luxembourg | Lithuania | |
| Poland | Estonia | | | Netherlands | |
| France | | | Slovakia | |
| Greece | | | | |
| Ireland | | | | |
| Malta | | | | |
| Portugal | | | | |
| R. of Cyprus | | | | |
As can be seen, area C shows the countries that carry out the most actions, that is, where the companies that make up Cluster 3 predominate. However, this does not mean that they perform the same type of action. For example, as we have seen in
Table 6 and as Vasilescu et al. (2023) have also found, Swedish companies focus more on the design of environmentally sustainable products, whereas Spanish companies focus more on cost savings such as saving water or recycling materials.
3.3. Difficulties encountered by companies and type of support they request
In this section, we examine the companies’ perceptions of the difficulties they face when implementing environmental policy measures. Additionally, we present the types of aid requested by these companies. Both variables are shown by the type of cluster to which companies belong.
Figure 7 shows how companies are most affected by the cost of environmental actions and administrative procedures. As might be expected, the companies that carried out the most actions, those in Cluster 3, reported the most difficulties.
Figure 7. Distribution of clusters according to the difficulties faced by companies.
Source: Own elaboration.
Table 13 presents a contingency analysis of these difficulties. This table confirms that administrative and legal procedures are perceived as the principal difficulties faced by enterprises in any cluster. This difficulty had the highest percentage of all clusters. That is, it does not depend on whether firms take more or fewer actions or on the type of action they take.
Table 13. Difficulties contingency analysis.
| DIFFICULTIES | Cluster 1 | Cluster 2 | Cluster 3 | EST-
Chi^2 | Cramer’s V |
|---|
| Complexity of administrative or legal procedures | 30.64% | 16.39% | 46.71% | 2826.97 | 0.449 |
| The technical requirements of the legislation not being up to date | 16.58% | 8.80% | 28.26% | 2519.14 | 0.440 |
| Difficulty in choosing the right resource efficiency actions for your company | 18.60% | 10.17% | 29.57% | 2510.67 | 0.440 |
| Difficulty adapting environmental legislation to your company | 18.64% | 10.52% | 29.70% | 2494.65 | 0.435 |
| Lack of specific environmental expertise | 24.08% | 13.54% | 41.33% | 2715.98 | 0.424 |
| Lack of supply of required materials, parts, products or services | 21.82% | 13.79% | 35.08% | 2504.39 | 0.423 |
| Lack of demand for resource efficient products or services | 17.27% | 8.72% | 26.48% | 2496.42 | 0.422 |
| Complexity associated with environmental labelling and certification | 17.27% | 8.72% | 26.48% | 2496.42 | 0.422 |
| Cost of environmental actions | 24.08% | 13.54% | 41.33% | 2715.98 | 0.422 |
When analyzing the help sought by the companies, we can see in
Figure 8 that they mainly request subsidies; however, in addition to this economic incentive to meet the cost of environmental actions, they also want greater cooperation with other companies. In terms of the significance of these variables, we can see that all are relevant.
Figure 8. Distribution of clusters according to the support received by companies.
Source: Own elaboration.
We can observe that the percentage of companies in Cluster 3, which are the most sustainable companies, are those that request more support. That is the reason we can see in
Figure 8 “None” support is close to 0. There is also a relevant percentage of companies in the less environmentally active cluster that do not claim any aid.
A contingency analysis of these demands is presented in
Table 14. All responses regarding the requested aid were significant. As shown in
Figure 8, companies seek financial aid or subsidies as expected. However, it is striking that for companies in Clusters 1 and 3, the second most requested aid was cooperation between companies. However, for Cluster 2 (the least active in this area), the main request is for help in the form of consultancy on how to improve the efficiency of their use of resources.
Table 14. Requests contingency analysis.
| Support requested | Cluster 1 | Cluster 2 | Cluster 3 | EST-
Chi^2 | Cramer’s V |
|---|
| Better cooperation between companies across sectors so that new processes to reuse waste and byproducts can be … | 25.83% | 18.67% | 35.16% | 2388.75 | 0.415 |
| A tool to self-assess how resource efficient your company is with respect to other companies | 16.48% | 10.97% | 19.18% | 2276.02 | 0.413 |
| Clearer rules on the use of secondary raw materials | 17.92% | 12.19% | 23.85% | 2301.02 | 0.412 |
| Advice on funding possibilities and financial planning for resource efficiency investments | 23.42% | 18.89% | 29.76% | 2270.74 | 0.405 |
| Database with case studies that show the benefits of resource efficiency for companies | 17.00% | 11.37% | 21.07% | 2284.88 | 0.404 |
| Demonstration of new technologies or processes to improve resource efficiency | 25.71% | 18.34% | 29.18% | 2373.70 | 0.403 |
| Grants or subsidies | 40.98% | 34.91% | 49.38% | 2410.99 | 0.402 |
| Consultancy on how to improve resource efficiency in your company | 25.29% | 21.39% | 30.46% | 2260.33 | 0.385 |
4. Discussion
This study contributes to a better understanding of SMEs in the context of a Circular Economy in the EU. This is essential for policymakers, both for ecological reasons and given the uncertain geopolitical situation. We detected three clusters based on the company characteristics. Cluster 3 was the most proactive in terms of environmental issues and Cluster 2 was the least proactive. The following observations can be made. On the one hand, the EU’s Circular Economy Action Plan was implemented to help firms become more sustainable. In this sense, Govindan and Hasanagic (2018) demonstrated in an empirical study of the supply chain that the government is the actor that has the most impact on the implementation of the Circular Economy. In this context, it is surprising that the principal difficulty that firms identify is the complexity of administrative or legal requirements, except for Cluster 1, which focuses on the costs of these actions. Additionally, more environmentally proactive firms face the most difficulties. Further, after subsidies, firms’ second strongest call is for better cooperation between companies in Cluster 3 and for consultancy in Cluster 2. It seems that less proactive companies need technical assistance in implementing environmental actions.
In sum, first, most firms seem to find the implementation of environmentally sustainable practices to be expensive and entail administrative difficulties. As such, it is noteworthy that macro-level initiatives such as the Circular Economy Action Plan are considered a problem for firms rather than a source of help. Second, companies are seeking a more dynamic connection with their commercial counterparts and are requesting support to encourage meso-level initiatives. In this regard, the problem of asymmetric information could be best addressed by active engagement on the part of public administrations or bodies designed for this purpose. Finally, the least proactive cluster does not see a way forward to implement green practices.
All of these are considerations for policymakers to consider for the improvement of the sustainable economy process across the European Union.
5. Conclusions
This study grouped the European companies according to their environmental actions. We found three types of clusters, each with different characteristics and identified the countries in which each group was principally located.
The first cluster comprises the largest number of companies, mainly those that provide services to other companies. They are characterized by a strong focus on energy savings and waste minimization.
The second group, Cluster 2, stands out because it constitutes the companies that carry out the fewest actions.
At the other extreme, we have Cluster 3, whose main characteristic is that it carries out the most actions. It is also the most diverse cluster in terms of the type of targeted customer. Companies ask for financial support to become more environmentally sustainable, as they state that the actions carried out are costly and for more information, as they see a benefit in collaboration with other firms in this area. Difficulties in administrative processes are the second problem faced by companies, and companies also ask for help in implementing new technologies or processes to become more efficient.
In short, they request financial support, on the one hand, and, on the other hand, greater simplicity in terms of administrative procedures, along with information regarding possible cooperation between companies regarding new technologies or processes.
Ethics and consent
Ethical approval and consent were not required for this study.
Data availability.
All the data underlying the results presented in this article are publicly available under open licences permitting reuse.
Garcia-Alcober, M. P., Mateos Ansótegui, A. I., Pastor Gosálbez, M. T., & Navarro, J. (2026). Extended data “How are European Small Enterprises dealing with the Circular Economy?” [Data set]. Zenodo. https://doi.org/10.5281/zenodo.19691797 García-Alcober (2026).
Data are available under the terms of the Creative Commons Attribution 4.0 International.
All datasets are freely available and distributed under open licenses permitting reuse (CC-BY or equivalent), depending on.
the source). These datasets can be used to replicate the analyses and findings presented in this study.
Acknowledgements
The authors acknowledge the comments of attendants at the XLVIII International Conference on Regional Science.
References
- Baldassarre B:
Circular economy for resource security in the European Union (EU): Case study, research framework, and future directions.
Ecol. Econ.
2025; 227: 108345. Publisher Full Text
- Cao F, Liang J, Bai L:
A New Initialization Method for Categorical Data Clustering.
Expert Syst. Appl.
2009; 36(7): 10223–10228. Publisher Full Text
- Chatzistamoulou N, Tyllianakis E:
Commitment of European SMEs to resource efficiency actions to achieve sustainability transition. A feasible reality or an elusive goal?.
J. Environ. Manag.
2022; 321: 115937. Publisher Full Text
- Christis M, Athanassiadis A, Vercalsteren A:
Implementation at a city level of circular economy strategies and climate change mitigation–the case of Brussels.
Journal of Cleaner Production.
2019; 218: 511–520. Publisher Full Text
- European Commission:
Closing the loop—An EU action plan for the circular economy.
Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions;
2015.
- European Commission:
A new Circular Economy Action Plan for a cleaner and more competitive Europe.2020.
Reference Source
- European Commission:
Flash Eurobarometer 498. SMEs, Resource Efficiency and Green Markets, wave 5.
GESIS;
Cologne:
2022a. ZA7806 Data file Version 1.0, Brussels 2022. Publisher Full Text
- European Commission:
Annual Report on European SMEs 2021/22. SMEs and environmental sustainability.
Brussels:
2022b; vol. 2022.
- European Parliament and Council:
Regulation (EU) 2024/1252 of the European Parliament and of the Council of 11 April 2024 Establishing a Framework for Ensuring a Secure and Sustainable Supply of Critical Raw Materials and Amending Regulations (EU) no 168/2013, (EU) 2018/858, (EU) 2018/17.
Off. J. Eur. Union.
2024; 2024: 1–67.
- García-Alcober M:
Online Appendix to "How are European Small Enterprises dealing with the Circular Economy?".
Zenodo.
2026. Publisher Full Text
- Ghisellini P, Cialani C, Ulgiati S:
A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems.
Journal of Cleaner Production.
2016; 114: 11–32. Publisher Full Text
- Gomonov K, Ratner S, Lazanyuk I, et al.:
Clustering of EU countries by the level of circular economy: An objective-oriented approach.
Sustainability.
2021; 13: 7158. Publisher Full Text
- Govindan K, Hasanagic M:
A systematic review on drivers, barriers, and practices towards circular economy: a supply chain perspective.
Int. J. Prod. Res.
2018; 56(1–2): 278–311. Publisher Full Text
- Masi D, Kumar V, Garza-Reyes JA, et al.:
Towards a more circular economy: exploring the awareness, practices, and barriers from a focal firm perspective.
Prod. Plan. Control.
2018; 29(6): 539–550. Publisher Full Text
- Turcu C, Gillie H:
Governing the circular economy in the city: Local planning practice in London.
Plan. Pract. Res.
2020; 35(1): 62–85. Publisher Full Text
- Vasilescu MD, Dimian GC, Gradinaru GI:
Green entrepreneurship in challenging times: a quantitative approach for European countries.
Economic research-Ekonomska istraživanja.
2023; 36(1): 1828–1847. Publisher Full Text
