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Small and medium-sized enterprises (SMEs) play a prominent role in the ecological transition process needed to curb climate change. The European commitment to eliminate emissions by 2050 requires significant changes in business structures. This research seeks to provide quantitative information on the level of efficiency of the activities carried out by 13,343 companies of the EU-27. The aim is twofold: (1) to analyse the link between resource efficiency and green markets; and (2) to evaluate the boost that certain public and private measures can give to the green processes undertaken by SMEs, as these economic units are responsible for the bulk of carbon emissions. DEA-Bootstrap is applied, confirming the asymmetry between green markets and resource efficiency in efforts to achieve climate neutrality, with more progress needed on the latter to help tackle environmental challenges. Decision-makers should target subsidies to ensure the circularity of productive systems and thereby make progress on meeting the goals established by the 2030 Agenda. The study focuses on European SMEs, showing that in countries such as Denmark, the level of resource efficiency could improve by more than 72% if SMEs were provided with tools for self-assessing their activity, consultancy services, grants, and financial and technological advice, as well as a better understanding of the advantages offered.
Introduction
Climate change (CC) is the major challenge of this century, and slowing its advance requires a universal commitment involving the collaboration of all social and economic strata. Its impacts are opening up wide gaps in society, as well as causing material damage. The world’s most vulnerable people suffer most intensely from the limited and inefficient mitigation measures adopted (Ngcamu, 2023). The last Conference of the Parties organized by the United Nations (COP28) made it clear just how far we are from meeting the objectives set out in the 2015 Paris Agreement. Halfway along the route from that milestone to 2030 and greenhouse gas emissions still have to be reduced by 43% relative to 2019 levels, an extremely difficult task if sufficiently far-reaching strategies are not established (Burki, 2023).
Governments should work together to prevent environmental degradation, attempting to establish a balance between economic performance and sustainable growth (Ishaq et al., 2024). They should promote the circular economy (CE), understood as a production and consumption system whose focus is on extending the useful life of products as long as possible, minimizing waste generation and seeking socio-economic equality (Kirchherr et al., 2017). The CE is a complex system, and innovation, human behaviour and consumption are the keys to its success (Gonçalves Castro et al., 2022). In short, this paradigm involves replacing a linear economy with a circular one, to improve environmental quality while ensuring the responsible supply of raw materials (Almeida-Neves & Cardoso-Marques, 2022) It also requires a holistic consideration of the complete life cycle of products and services, from their conception to their final disposal. The 10 Rs model of the Ellen MacArthur Foundation (2013) establishes a hierarchy of circular strategies. The initial six Rs are related to the production stage—reuse, repair, refurbish, remanufacture and recycle—to which four additional Rs related to the marketing and consumption stages have been added, focused on reducing, rethinking, refusing and recovering products (Shevchenko et al., 2023).
The “butterfly diagram” of the CE proposed by the Ellen MacArthur Foundation depicts the hierarchy of strategies throughout the life cycle of goods and services, from extraction and production to consumption and final disposal. Resource efficiency (RE) mainly concerns the production or manufacturing stage, where the aim is to minimize the use of materials, energy and other natural resources needed to create a product or service. There is a proven association between RE, cost reduction, zero emissions and competitiveness (Van Ewijk, 2018; OECD, 2019). This stage can be considered the starting point for ensuring that resources are used efficiently from the outset. Ahmad et al. (2023) argue that RE reduces production costs, and that the more actions taken, the greater the savings. Throughout this transformative process, it has been shown that micro-level actions aimed at achieving RE positively influence the adoption of macro instruments focused on achieving climate neutrality (Gomes & Pinho, 2023).
On the other hand, the implementation of green markets (GM) mainly affects the marketing and consumption stages, where consumers choose goods and services with a highly positive environmental impact, and efforts are made to ensure the efficient management of natural resources without compromising the ability of future generations to meet their needs, in line with Brundtland (1987). The “green” label implies key issues relating to CC such as energy saving, the efficient use of ecological resources, as well as the reduction of emissions and polluting waste (Skard et al., 2021; Marcon et al., 2022). As consumers become increasingly ecologically aware, green purchase intention is becoming more prevalent, with people changing their habits to buy more environmentally-friendly goods (Ng et al., 2024). According to Chen and Liu (2020), the development of GM requires joint cooperation between companies and customers, with the latter understood to be facilitators of sustainable entrepreneurship. The success of GM rests on an increasingly deep-seated consumer concern about the environmental effects of excessive resource use (Rajput et al., 2022). According to Soomro et al. (2023), green products influence green entrepreneurship and the development of all sectors.
The European Union (EU) has highlighted the role of small and medium-sized enterprises (SMEs) in this conversion process, given that their output accounts for more than 50% of national GDP and they are responsible for 70% of all industrial pollution (European Commission, 2020). The European Green Deal treats SMEs as drivers of sustainable processes in industrial and commercial systems (European Commission, 2021a, b). This can improve the situation of SMEs, which lack the financial resources needed to offer innovative green products that respond to changing consumer needs (Thomas et al., 2022). Shen et al. (2021) suggest strengthening tax legislation to enhance the use of natural resources and encourage green investment, thereby cutting carbon emissions. Caporale et al. (2023) highlight the positive impact of internal financing on the adoption of energy-saving measures, suggesting that the use of private external resources be promoted in countries characterized by their broad environmental awareness. According to Yoshino et al. (2023), public environmental awareness and government research must be encouraged as they are positive determinants of SMEs’ shift towards the CE. Aristei and Gallo (2021) recommend implementing public policies tailored to firm size and to different types of environmental practices. Greater momentum in green growth could be achieved by reinforcing the subsidies offered to SMEs for making RE investments (Özbuğday et al., 2020).
Despite the progress made in successive studies, there is very little research that seeks to measure the effectiveness of efforts made by companies all along the value chain to achieve the goals set out in the 2030 Agenda. To help address this gap in the literature, the present paper aims to quantify the level of efficiency of European SMEs in their efforts to make responsible use of resources in the production stage and also adapt their marketing stage to meet the demands of GM. The results will indicate the capacity of the business sector to lead the transition, providing answers to the following research questions:
Q1. Is there a direct correlation between RE and the efficiency of GM in the fight against CC?
Q2. Would the implementation of additional public and private measures facilitate the necessary progress towards a new setting in which respect for the environment prevails?
The analysis relies on the information collected by means of 13,343 surveys administered to SMEs from EU-27 countries in 2021 (European Commission, 2022). A variant of data envelopment analysis (DEA)—namely, DEA-Bootstrap—is used, thus avoiding possible issues caused by the sample size. In addition, a two-stage model is used to assess the efficiency of the actions undertaken by SMEs and their contribution to climate neutrality. The study makes novel contributions to the literature that can help decision-makers in the arduous task of implementing the most appropriate policies: specifically, (1) it profiles the patterns of behaviour of those countries whose SMEs are more advanced in RE and more environmentally efficient in their production lines; (2) it provides evidence of the need to adopt unprecedented policies aimed at accelerating the climate revolution; and (3) it analyses the importance of the CE as a first step towards the creation of GM.
The rest of the paper is structured as follows: in Sect. 2, a literature review is carried out to establish the conceptual framework for the study; in Sect. 3, the method and the variables used are presented; in Sect. 4, the results of the empirical analysis are analysed and discussed in relation to the existing paradigm; and finally, the conclusions, contribution of the study and limitations are summarized in Sect. 5.
Literature review: resource efficiency and green markets
CC mitigation requires actions aimed at reducing the carbon footprint. The European Climate Law establishes the obligation not to emit more carbon dioxide than can be absorbed (European Parliament, 2021), and in this scenario SMEs play a fundamental role (Adu et al., 2023). By their nature, companies seek to maximize their profits, but they are now also required to achieve a balance between caring for the environment and profitability (Xiang et al., 2022). According to Puertas et al. (2022), the desired equilibrium could be achieved by being located in environmentally-focused countries, with Orazalin et al. (2024) additionally noting the importance of having a board sustainability committee. SMEs are being asked to implement a CE that ensures RE as well as a greater supply of green products and services, which requires the provision of public subsidies that reduce their costs (Özbuğday et al., 2020). The scientific community has developed an extensive literature around these two concepts—RE and GM—seeking to expand the knowledge base and guide decision-makers in their difficult task of implementing the appropriate regulations to reduce the impact of the business sector on the climate.
SMEs and resource efficiency
RE involves actions related to saving water, energy, and materials, as well as making the shift towards renewable energies, greener suppliers, and even waste minimization, recycling and reuse; all of these are focused on ensuring the CE forms part of people’s everyday activities (Chatzistamoulou & Tyllianakis, 2022a; Ferradás-González et al., 2024). In short, it is about producing goods and services using fewer resources while minimizing the generation of waste (Passetti & Tenucci, 2016). Companies must work to ensure the circularity of their business processes and activities by introducing technological and non-technological innovations, thereby improving their environmental, market and social performance (Castro-Lopez et al., 2025). Economic systems must move towards these sustainable practices to achieve RE, as a key factor for reducing carbon emissions (Sun et al., 2023).
According to Tritto et al. (2024), CE practices in European companies are strongly influenced by their size and by the sector of their main activity, with manufacturing-oriented SMEs being the most willing to introduce ecological practices. Maman et al. (2024) confirm the heterogeneous performance of European SMEs, calling on the EU to implement environmental policies that encourage convergence in the reduction of national pollution levels.
The advances made in the literature have helped shed light on both the barriers preventing businesses from becoming circular and the driving forces behind such a transition. For example, Díaz-López et al. (2019) analyse 143 cases in which RE measures are implemented in companies, finding that technical, institutional, and market limitations are the main obstacles. In the same vein, Khan et al. (2022) demonstrate that the main impediments to this transformation are the lack of government policies and industrial support and the need for greater integration of the CE in the supply chain. European SMEs face major challenges in an environment of regulatory complexity and a lack of public financing (Segarra-Blasco et al., 2024). Other authors such as Schipfer et al. (2022) conclude that poor knowledge and insufficient funding limit companies’ ability to adopt environmentally-friendly practices, suggesting that external support could help to overcome these difficulties. In this context, Chatzistamoulou and Tylianakis (2022b) recommend specialized business advice to encourage RE actions, while Milligan and O’Keeffe (2019) call for a global legislative framework to prevent possible discrepancies between national interests and those of local communities, which ultimately hinder the proper management of resources.
Regarding the elements that enhance RE in SMEs, Moreno-Mondejar and Cuerva (2020) find a positive relationship between investment in RE and the ability to offer green products and services, with excessive regulation and pressure from competitors having a negative effect. However, according to İncekara (2022) and Clemente-Almendros et al. (2025), proper waste management and anticipation of future legislation not only contribute to reducing production costs but also help SMEs to cope with competition. Regulation and the environmental commitment of companies’ top management positively influence environmental innovation (Carchano et al., 2024). In addition, Tang et al. (2023) note the relevance of technology adapted to new requirements, coupled with incentives and stable policies to take on the challenges associated with the industrialization and urbanization of humanity.
There is thus a broad literature showing SMEs’ commitment to implementing RE-oriented measures, with this contribution being key to ensuring that economic development aligns with beneficial environmental conditions (Moursellas et al., 2023). For example, Domenech and Bahn-Walkowiak (2019) and Sofuoğlu and Kirikkaleli (2023) demonstrate the need to strengthen RE as a way to achieve zero emission targets even sooner. Other authors such as Gomes and Pinho (2023) add that requirements such as financing conditions, investment and administrative obligations pose major obstacles that must be overcome. Analysing a sample of 10,618 European SMEs, Garrido-Prada et al. (2021) confirm that public investment in R&D oriented to the environment and energy would alleviate the financial burden companies face when implementing CE activities. It has also been shown that discounts for the purchase of environmentally-friendly products and tax reductions for climate-friendly companies positively impact the environment (Sarvari et al., 2024).
SMEs and green markets
Eco-designed goods and services are sold in GM to minimize environmental risk and pollution (European Commission, 2022). According to Li et al. (2018) their development depends on the existence of competitive environments, and then in turn encourages internal green practices and efficient supplier management. Ngo (2022) demonstrates a direct link with business performance, showing that SMEs may become less competitive by introducing ecological practices. However, there is no consensus regarding its impact on profit: other authors such as Zheng et al. (2022) argue that ecological manufacturing fosters green purchases, reducing the cost of production and therefore boosting efficiency.
In this context of conflicting ideas, it is essential to introduce innovations to supply the growing demand without jeopardizing business productivity (Adu-Yeboah et al., 2022). Amoako et al. (2020) demonstrate the nexus between green attitude and sustainable purchase intention among consumers who are increasingly aware of their obligation to engage and reduce the impact of their actions. Many people are looking for efficient products, wanting to avoid excess packaging and purchase low pollution items (Do Paco et al., 2019). At this point, green advertising has a very positive influence on the volume of purchases and the profits attained by SMEs; accordingly, Martins (2022) recommends that green marketing should be incorporated into business plans to boost sales and profitability.
Humanity is increasingly determined to collaborate in the fight against CC; green products are becoming luxury items, with consumers seeking both quality and respect for the environment (Ahmad & Zhang, 2020). According to Sharma et al. (2020), the citizens who are most concerned about the environment are more inclined to buy these products, taking pride in their behaviour in this regard and striving to influence others. In Europe, brand reputation is strongly influenced by companies’ adherence to emission restrictions (Gálvez-Sánchez et al., 2024). Companies must adapt to deal with these new patterns of behaviour, where consumers’ loyalty to the green brand and altruistic feeling can sometimes compensate for higher production costs (Panda et al., 2020). Young people are well represented in this profile, as social networks encourage them to develop a pro-environmental attitude (Zhang et al., 2024). New information channels, environmental concern, subjective norms, and attitude all influence people’s propensity to make green purchases (Yanyan et al., 2023). As for the SMEs, their participation in GM is again conditioned by budgetary allocations, investments and excessive regulation (Sarvari et al., 2024). García-Alonso et al. (2023) argue that government leaders must promote measures aimed at fostering the development of GM, as these markets constitute a powerful driver of sustainable growth and the fight against CC.
These studies underline the major interest in RE, CE and GM, all of which have been conceived as means to achieve the goals of the 2030 Agenda. Nevertheless, there is a need for quantitative measurement to assess the effort made by companies in this transition towards greening the planet against climate change, and thus determine the most appropriate policies to further encourage those efforts.
Method and data
Method: DEA-Bootstrap
The empirical analysis has been carried out using the DEA method to measure the efficiency levels of European SMEs and thus be able to answer the research questions raised. DEA is a linear programming technique that, based on a set of decision-making units (DMUs), constructs an efficient frontier made up of DMUs defined by the optimal combination of inputs/outputs (that is, they cannot increase their outputs without decreasing their inputs, or vice versa). Each DMU is evaluated in terms of its distance from the frontier. This concept of efficiency was originally proposed by Farrell (1957), who assumed a known production function. However, when applied to real-world situations, the production function needs to be estimated, which gives the model its non-parametric nature as defined by Charnes et al. (1978) in a setting of constant returns to scale (CRS). Banker et al. (1984) relaxed the latter assumption, introducing the possibility that the inputs/outputs of the DMUs present variable returns to scale (VRS), thus allowing for a lack of proportionality between the changes made to each. There are two possible orientations for the model: an output orientation (oo), if the objective is to maximize the outputs with the available inputs, or input orientation (io) otherwise. This method has been successfully applied in various areas relating to RE (Calafat-Marzal et al., 2023), the production of green goods and services (Li & Xu, 2023), and to the green innovation (Zhiyong et al., 2024).
One advantage of DEA is that it is not necessary to assume a functional form or weight the factors of the DMUs; it allows for multiple inputs and outputs of very different measurements. However, it is very sensitive to sampling variability, the quality of the information used, and the presence of outliers (Herrera & Pang, 2005). There are different ways to overcome these drawbacks. According to Boyd et al. (2016) super-efficiency outlier detection is only feasible when there are few outliers, so they propose an alternative method based on a stochastic DEA model. Yang et al. (2014) formulate Bi-super DEA as an outlier detection method. Clermont and Schaefer (2019) combine super-efficiency analysis with influence analysis, incorporating statistical methods to examine the position of DMUs in multidimensional space.
In this research, we use the DEA-Bootstrap proposed by Simar and Wilson (2000) to overcome these limitations and account for the possible existence of random errors. It involves constructing an empirical distribution of variables by resampling the original sample, facilitating the calculation of means and standard deviations. This variant provides bias-corrected efficiency scores along with confidence intervals at the selected α-level, by implementing the following steps (Tziogkidis, 2012):
Use DEA to calculate the efficiency levels.
Extract the empirical distribution of (1) by replacement.
Obtain a bootstrap set of pseudo-inputs calculated by dividing the efficient inputs by the pseudo-efficiency levels drawn from the empirical distribution.
Apply DEA to the new set of pseudo-inputs and the original outputs and calculate the bootstrapped efficiency scores.
Repeat steps 2–4 2000 times to get the set of estimates.
Given the nature of this research, we have opted for VRS and oo, meaning that the efficiency scores will take values equal to or greater than 1, where the excess over the value of 1 indicates the level of inefficiency of the evaluated DMU; that is, how much the outputs should increase using the available inputs to achieve maximum efficiency. Furthermore, in the estimation of RE, two-step DEA-Bootstrap is used, where the outputs of the first stage constitute the inputs of the second, in order to gain a more detailed explanation of the process (Seiford & Zhu, 1999).
Data: flash eurobarometer 498
The statistical information has been sourced from the Flash Eurobarometer 498 survey published in 2022, referring to information on the green practices of European and US SMEs in 2021 (European Commission, 2022). Given the EU’s firm commitment to tackling CC, and in order to ensure the homogeneity of the sample, the analysis focuses on the SMEs from the EU-27. The Eurobarometer 498 provides information on 13,343 SMEs grouped by country of residence, such that the sample is made up of 27 DMUs corresponding to the EU Member States. The DEA-Bootstrap method incorporates two models: one referring to RE actions and the other referring to GM, whose inputs/outputs are described in Table 1. The variables, some of which are categorical, represent the total volume of companies’ responses to the questions asked. The DEA method allows for any magnitude of inputs and outputs; hence, survey information and even synthetic indices can sometimes be used (Calafat-Marzal et al., 2023; Puertas et al., 2023).
Table 1. RE and GM: inputs/outputs
RE model | ||
Input i1 | Over the past two years, how much have you invested on average per year to be more resource efficient? | 0 (nothing); 1 (less than 1% of annual turnover); 2 (1–5%); 3 (6–10%); 4 (11–30%); 5 (more than 30%) |
Input i2 | What type of support does your company rely on in its efforts to be more resource efficient? | Proportion of support measures per SMEs in each country |
Undesirable input i3 | Did your company encounter any of the following difficulties when trying to set up resource efficiency actions? | Proportion of difficulties per SMEs in each country |
Conditional input ic | Which of the following would help your company the most to be more resource efficient? | Proportion of measures which would help SMEs in each country |
Output/Input o/i | What actions is your company undertaking to be more resource efficient? | 3 (many actions); 2 (some); 1 (few); 0 (none) |
Output o1 | Does your company have a concrete strategy in place to reduce your carbon footprint and become climate neutral or negative? | 2 (yes); 0.5 (no, but it is in planning) |
Output o2 | What impact have the resource efficiency actions undertaken had on production costs over the past two years? | 2 (significantly decreased); 1 (slightly decreased) |
Output o3 | What actions is your company undertaking to be become climate neutral? | Proportion of actions taken by European SMEs. |
GM model | ||
Input i1 | In terms of turnover over the past 2 years, what were the main markets (countries/ geographical regions) for your green products or services? | Ratio of domestic to international markets for its green products or services |
Input i2 | For how long your company has been selling green products or services? | 1 (less than one year); 2 (between 1 and 3); 3 (more than 3) |
Input i3 | What type of support does your company rely on for the production of its green products or services? | Proportion of support measures given to SMEs in each country |
Input i4 | In your company, how many of your full-time employees, including yourself, work on green tasks some or all of the time? | Mean |
Conditional input ic | What type of support would help you the most to expand your range of green products or services? | Proportion of measures which would help to SMEs in each country |
Output o1 | What actions is your company undertaking to be become climate neutral? | Proportion of actions taken by European SMEs. |
Output o2 | Does your company have a concrete strategy in place to reduce your carbon footprint and become climate neutral or negative? | 2 (yes); 0.5 (no, but it is in planning) |
Output o3 | How much did these green products or services represent in your annual turnover of the latest available fiscal year? | 1 (up to 5%); 2 (6–10%); 3 (11–30%); 4 (31–50%); 5 (51–75%); 6 (more than 75%) |
Both models respect the rule of thumb established by Cooper on the ratio between the number of DMUs and inputs/outputs used (Cooper et al., 2011). Tables 5A and 6A in the Appendix show the level of correlation between the selected variables in both models. In addition, a conditional input has been introduced in each model to assess the suitability of such measures and their possible effect on efficiency levels (Q2). Figure 1 shows the structure of the DEA models estimated.
[See PDF for image]
Fig. 1
Structure of the DEA-Bootstrap models
Results and discussion
The application of the DEA-Bootstrap to a sample containing the green actions of European SMEs provides answers to the two research questions raised. Regarding Q1, the analysis first addresses the companies’ performance when they implement RE-oriented actions in the production stage and how these actions help to improve the environmental situation while preserving profits (two-step). It then addresses the possible impact in the marketing stage caused by the supply of green goods and services. This makes it possible to determine whether there is a parallel between the two dimensions, RE and GM. Regarding Q2, the aim is to provide a quantitative assessment of the possible advantages of providing additional support that could accelerate the achievement of environmentally beneficial results without undermining profits.
Q1. Is there a direct correlation between RE and the efficiency of GM in the fight against CC?
The answer to Q1 has been obtained by calculating the efficiency levels of the models presented in Fig. 1. There are two different stages in the RE model: the first determines which SMEs have made the best use of their inputs to implement RE actions (Stage 1 EFF_Boots), and the second identifies the extent to which these performances have translated into environmental and economic improvements (Stage 2 EFF_Boots), while also providing a global assessment of the RE actions (Total EFF-Boots RE). These two stages enrich the available information, allowing us to detect where the strongest policy efforts should be directed. In the GM model, since we do not have information on internal features, the DEA-Bootstrap has focused on determining whether the inputs used to produce green products have helped to improve environmental benefits and to introduce ecological strategies focused on meeting environmental goals (Total EFF-Boots GM).
The efficiency levels calculated using DEA-bootstrap enable a detailed assessment of the situation of SMEs in each country compared to the rest of the European companies belonging to the EU-27 (Table 2). Overall, it can be seen that SMEs more efficiently pursue climate neutrality in the production stage by introducing green products and services (GM model): compared to an average level of inefficiency of 8.2% in GM, (Total EFF-Boots GM), a level of 52.1% is registered in RE (Total EFF-Boots RE); and there is no correlation between the two according to Spearman’s rho (Q1). For example, Danish SMEs achieve very good results in the GM; they would only have to increase their output by 2.1% to be fully efficient. However, in RE they would have to improve it by 87.2% (Total EFF-Boots GM), as the resources used need to yield more RE actions (Stage 1 EFF-Boots).
Table 2. DEA-bootstrap in RE and GM models
RE model | GM model | |||||
|---|---|---|---|---|---|---|
NºSMEs | Stage 1 EFF-Boots | Stage 2 EFF-Boots | Total EFF-Boots RE | Total EFF_Boots GM | ||
Sweden | 555 | 1.052 | 1.083 | 1.140 | Denmark | 1.021 |
Ireland | 484 | 1.134 | 1.064 | 1.206 | Estonia | 1.026 |
Poland | 590 | 1.162 | 1.107 | 1.287 | Belgium | 1.027 |
Austria | 477 | 1.216 | 1.059 | 1.288 | Slovakia | 1.028 |
Netherlands | 549 | 1.101 | 1.179 | 1.298 | Czechia | 1.030 |
Portugal | 555 | 1.199 | 1.093 | 1.310 | Ireland | 1.032 |
Italy | 538 | 1.039 | 1.265 | 1.314 | Luxembourg | 1.033 |
Luxembourg | 243 | 1.158 | 1.152 | 1.334 | Latvia | 1.038 |
Malta | 243 | 1.277 | 1.060 | 1.353 | Greece | 1.038 |
France | 553 | 1.164 | 1.188 | 1.383 | Germany | 1.043 |
Czechia | 568 | 1.274 | 1.092 | 1.391 | Malta | 1.045 |
Romania | 584 | 1.322 | 1.072 | 1.417 | Netherlands | 1.046 |
Spain | 560 | 1.154 | 1.231 | 1.421 | Romania | 1.046 |
Belgium | 539 | 1.115 | 1.280 | 1.427 | Sweden | 1.047 |
Slovakia | 485 | 1.112 | 1.321 | 1.469 | Portugal | 1.048 |
Germany | 568 | 1.277 | 1.156 | 1.476 | Cyprus | 1.049 |
Croatia | 511 | 1.450 | 1.042 | 1.510 | Hungary | 1.050 |
Hungary | 499 | 1.240 | 1.275 | 1.581 | France | 1.051 |
Greece | 585 | 1.484 | 1.077 | 1.598 | Austria | 1.062 |
Latvia | 498 | 1.154 | 1.404 | 1.621 | Lithuania | 1.067 |
Lithuania | 477 | 1.343 | 1.229 | 1.650 | Finland | 1.090 |
Finland | 482 | 1.330 | 1.286 | 1.710 | Poland | 1.110 |
Cyprus | 247 | 1.156 | 1.509 | 1.745 | Slovenia | 1.116 |
Slovenia | 534 | 1.552 | 1.202 | 1.866 | Spain | 1.129 |
Denmark | 447 | 1.757 | 1.065 | 1.872 | Italy | 1.211 |
Estonia | 495 | 1.788 | 1.092 | 1.952 | Croatia | 1.297 |
Bulgaria | 477 | 2.224 | 1.102 | 2.451 | Bulgaria | 1.424 |
Mean | 1.305 | 1.174 | 1.521 | 1.082 | ||
Spearman´s rho (EFF-Boots RE, EFF-boots GM): 0.0031 | ||||||
To sum up, in the RE model, the poorest performance is found in the first stage, with an inefficiency of 30.5% compared to 17.4% in the second (Stage 1 EFF-Boots and Stage 2 EFF-Boots, respectively). In other words, the inputs used to introduce RE actions are not being used correctly; 30.5% more actions could be implemented to save water, energy, natural resources, etc. Gomes and Pinho (2023) point to financial constraints, investment restrictions and regulatory requirements as the elements that hinder the adoption of measures to improve efficiency in the use of resources at the microeconomic level, compromising the prospects for a successful climate transition. There are exceptions, such as Luxembourg or Finland, where the results of both stages are very similar (15.8% versus 15.2%, and 33.0% versus 28.6%, respectively). On the other hand, in the GM model all countries except Poland, Slovenia, Spain, Italy, Croatia, and Bulgaria, register levels of inefficiency below 10%, and as low as 2% in the case of Denmark. These results confirm that SMEs with strategies oriented towards the supply of green goods and services contribute more efficiently to curbing CC. These are companies with a track record of greater commitment to caring for the environment, with these efforts not being mirrored in the circularity of resources. Kalar et al. (2021) attribute this behaviour to the fact that companies in the innovation stage focus less on RE activities, which are more complex and require more capital, while companies in the conservative stage are involved in more RE actions.
These results support the research of Bassi and Días (2019), which showed that a high percentage of SMEs from Bulgaria, Estonia, Denmark, Slovenia and Cyprus lack plans to minimize the use of water, energy or waste generation, and to maximize the reuse of water, and/or waste. That said, as noted by Wang et al. (2023) the fact that RE actions are more widely implemented does not mean higher levels of efficiency: a case in point is Finland, where the use of renewable energies accounts for 44.6% of total energy, but its level of inefficiency in the RE model is 71% (Total EFF-Boots RE). The RE actions used have not been appropriately targeted at the implementation of strategies conducive to achieving the desired environmental care, while still paying attention to matters of profitability. SMEs must intensify their efforts to jointly integrate efficient resource management with environmental management, which requires external support and employee participation to replace specific frameworks with generic ones that facilitate the achievement of environmental, social and economic benefits (Siegel et al., 2019).
According to Moreno-Móndejar and Cuerva (2020), in order to make progress towards sustainability, SMEs need RE to ensure the implementation of the CE, and this process necessarily involves fostering technological capacities aimed at the production of green goods and services. Those countries whose companies have been less efficient should make an effort to promote green innovation and ensure the economic and environmental performance of their actions.
Lastly, to identify in more detail SMEs’ efficiency performance profile, Table 3 presents the characteristics of those that have registered the best and worst results in each of the stages. The low levels of efficiency of Bulgaria and Cyprus stand out. Their SMEs have focused mainly on retail trade, with low revenues in 2020, dropping further still in recent years. They are mostly service retailers concentrated on meeting consumer needs. In the case of Bulgaria, they express a high degree of dissatisfaction with the public subsidies received.
Table 3. Characteristics of SMEs with the best and worst level of efficiency in each stage
Stage 1 EFF_Boots | Stage 2 EFF_Boots | Total EFF_Boots RE | Total EFF_Boots GM | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
Highest efficiency | Lowest efficiency | Highest efficiency | Lowest efficiency | Highest efficiency | Lowest efficiency | Highest efficiency | Lowest efficiency | |||
Countries | Italy | Bulgaria | Croatia | Cyprus | Sweden | Bulgaria | Denmark | Bulgaria | ||
Mean EFF-Boots | 1.039 | 2.223 | 1.041 | 1.509 | 1.139 | 2.451 | 1.021 | 2.451 | ||
How satisfied are you with the level of public support for your green products or services? | 98% | 1% | 49% | 75% | 80% | 1% | 21% | 1% | ||
Which of the following categories best describes your company? | 20% Construction | 38% Retail | 24% Construction | 35% Retail | 16% Construction | 38% Retail | 25% Retail | 38% Retail | ||
What was your company’s total turnover in 2020? | 35%more than €2–10 million | 33%less than €25,000 | 22% more than €100-250k | 20% more than €100-250k | 21% more than €500k-€2 million | 33%Less than €25,000 | 21% more than €500k-€2 million | 33%Less than €25,000 | ||
Has your company’s annual turnover increased, decreased or remained unchanged? | 36% no change | 44% decrease | 36% no changed | 44% decrease | 41% increase | 44% decrease | 56% increase | 44% decrease | ||
Is your company selling its products, services or both? | 44% Services | 49% Services | 45% Both | 43% Services | 41% Services | 49% Services | 35% Products | 49% Services | ||
How many employees (full-time equivalents) does your company currently have? | 94% 1–9 emp. | 90% 1–9 emp. | 92% 1–9 emp. | 92% 1–9 emp. | 94% 1–9 emp. | 90% 1–9 emp. | 85% 1–9 emp. | 90% 1–9 emp. | ||
Is your company selling its products or services to…? | 67% other companies | 69% directly to consumers | 69% other companies | 75% other companies | 77% other companies | 69% directly consumers | 74% other companies | 69% directly to consumers | ||
Chen and Liu (2020) recommend getting customers involved in the development of green products, as their suggestions are very helpful for directing the battle towards the areas of greatest interest. Preferences for green products evolve over time; as such, it is essential to know the customer to ensure the success of these products in a situation of major environmental pressures. According to authors such as Tchapchet-Tchouto et al. (2023), work will have to be done to break the association between higher incomes and demand for green products—and vice versa, to boost their consumption while avoiding issues of equality that jeopardize the conservation of the environment.
The results reflect a clear weakness of European SMEs in increasing the rate of circularity and the productivity of their resources in the early stages of the value chain. The EU has taken a very rigid stance towards the goal of net cero by 2050; however, the business community, which is the main emitter, shows evident shortcomings in the implementation of the CE. On the other hand, growing public awareness is facilitating the development of GM as a way to achieve the proposals of the European Green Deal. The SMEs of Italy, Croatia, Sweden and Denmark present patterns of behaviour for other European companies to follow. The fundamental difference lies in the degree of satisfaction with the public support received to implement the necessary changes in their production chains.
Q2. Would the implementation of additional public and private measures facilitate the necessary progress towards a new setting in which respect for the environment prevails?
To answer this question, a conditional variable was introduced into each of the analysed models. This variable captures complementary actions to help companies adapt to this new paradigm (advisory services, subsidies, advice on financing and identification of potential markets, new processes and technologies, access to databases, specific legislation, etc.). The aim is to enable a quantitative assessment of the improvements that they would enable for SMEs, both in the RE stage and in the supply of green products and services. Table 4 shows the new results assuming the successful implementation of these measures. This conditional variable allows us to calculate the following scores: Stage 1 EFF-Boots conditional, Total EFF-Boots RE conditional, Improvement Stage 1, Improvement RE model, Total EFF-Boots GM conditional and Improvement GM. The improvements have been determined by calculating the difference between the level of efficiency without including the conditional variable and the level of efficiency achieved when introducing it. For example, Improvement Stage 1 = Stage 1 EFF-Boots – Stage 1 EFF-Boots Conditional.
Table 4. DEA-bootstrap conditional in RE and GM models
Stage 1 EFF-Boots conditional | Improvement stage 1 | Stage 2 EFF_Boots | Total EFF_Boots RE conditional | Improvement RE model | Total EFF_Boots GM conditional | Improvement GM model | ||
|---|---|---|---|---|---|---|---|---|
Sweden | 1.037 | 1.49% | 1.083 | 1.123 | 1.61% | Sweden | 1.043 | 0.31% |
Austria | 1.085 | 13.05% | 1.058 | 1.149 | 13.82% | Austria | 1.059 | 0.18% |
Denmark | 1.079 | 67.79% | 1.065 | 1.149 | 72.22% | Denmark | 1.043 | −2.22% |
Ireland | 1.093 | 4.01% | 1.063 | 1.163 | 4.26% | Ireland | 1.029 | 0.25% |
Poland | 1.079 | 8.30% | 1.107 | 1.194 | 9.20% | Poland | 1.068 | 4.23% |
Germany | 1.061 | 21.57% | 1.155 | 1.227 | 24.93% | Germany | 1.035 | 0.72% |
Czechia | 1.134 | 13.99% | 1.092 | 1.238 | 15.27% | Czechia | 1.032 | −0.23% |
Luxembourg | 1.083 | 7.49% | 1.151 | 1.247 | 8.63% | Luxembourg | 1.027 | 0.50% |
Estonia | 1.153 | 63.47% | 1.091 | 1.259 | 69.29% | Estonia | 1.029 | −0.35% |
Netherlands | 1.068 | 3.24% | 1.179 | 1.259 | 3.83% | Netherlands | 1.039 | 0.59% |
Portugal | 1.169 | 2.89% | 1.093 | 1.278 | 3.16% | Portugal | 1.043 | 0.43% |
France | 1.083 | 8.09% | 1.187 | 1.286 | 9.61% | France | 1.043 | 0.74% |
Italy | 1.044 | −0.49% | 1.264 | 1.320 | −0.62% | Italy | 1.160 | 5.14% |
Malta | 1.252 | 2.42% | 1.059 | 1.327 | 2.56% | Malta | 1.038 | 0.64% |
Croatia | 1.275 | 17.47% | 1.041 | 1.328 | 18.20% | Croatia | 1.244 | 5.29% |
Spain | 1.079 | 7.42% | 1.231 | 1.329 | 9.14% | Spain | 1.128 | 0.05% |
Romania | 1.256 | 6.51% | 1.072 | 1.347 | 6.98% | Romania | 1.040 | 0.60% |
Finland | 1.057 | 27.18% | 1.286 | 1.360 | 34.95% | Finland | 1.051 | 3.85% |
Belgium | 1.068 | 4.62% | 1.280 | 1.368 | 5.92% | Belgium | 1.025 | 0.12% |
Slovakia | 1.036 | 7.54% | 1.321 | 1.369 | 9.97% | Slovakia | 1.027 | 0.05% |
Hungary | 1.078 | 16.18% | 1.275 | 1.374 | 20.64% | Hungary | 1.041 | 0.86% |
Slovenia | 1.1902 | 36.19% | 1.202 | 1.430 | 43.51% | Slovenia | 1.101 | 1.46% |
Latvia | 1.080 | 7.43% | 1404 | 1,516 | 10.43% | Latvia | 1.042 | −0.42% |
Bulgaria | 1.394 | 82.92% | 1.102 | 1.537 | 91.41% | Bulgaria | 1.417 | 0.68% |
Greece | 1.445 | 3.89% | 1.076 | 1.556 | 4.18% | Greece | 1.033 | 0.51% |
Lithuania | 1.279 | 6.34% | 1.228 | 1.572 | 7.79% | Lithuania | 1.065 | 0.13% |
Cyprus | 1.081 | 7.46% | 1.509 | 1.632 | 11.25% | Cyprus | 1.041 | 0.74% |
Mean | 1.138 | 16.61% | 1.173 | 1.331 | 18.97% | 1.072 | 0.92% |
The results show a very significant improvement in the RE model, registering an average of 16.6% in the first stage and 19% in total efficiency (Improvement RE Model). The introduction of these policies would allow SMEs in countries such as Denmark to reduce the inefficiency level of 75.7% for Stage 1 EFF-Boots to only 7.9% (Stage 1 EFF-Boots conditional). In Bulgaria, the improvement would be as high as 91.4%, driven by a greater use of resources to undertake RE actions. However, the good results of RE are not reflected in the advances in the GM, mainly because the initial efficiency levels were high in this case, leaving less room for improvement (8.2% compared to 7.2% with the conditional variable).
In this regard, Cecere et al. (2020) confirm that access to public funds and tax incentives for companies, as well as regulatory support, encourage the introduction of eco-innovations aimed at the green growth of countries. Environmental regulation is fundamental to promote the ecological development of SMEs seeking to bring green goods and services to market (Doran et al., 2023; Unger & Nippa, 2024). In this regard, Ben Amara and Chen (2021) emphasize the connection between ecological efficiency and eco-innovation, endorsing the importance of fostering competitive, technological and regulatory pressure as a way to strengthen sustainable business growth.
The greater flexibility of SMEs compared to large companies makes it easier for them to adapt to new environmental conditions, with financial incentives required for the implementation of these practices. According to Garrido-Prada et al. (2021), the financial burden SMEs face when addressing environmental matters can be alleviated through more governmental research and development, which in turn is beneficial for business growth. Committed SMEs should participate in the innovation of environmentally sustainable products, finding drivers in industrial regulations, economic incentives, ease of access to new markets, competition, technological development, as well as other drivers internal to the company (Melander, 2020). The results obtained confirm the importance of encouraging and incentivizing the granting of all kinds of subsidies to promote the development of a sustainable economy and society. The study has provided answers to the research questions raised; however, when interpreting the results, it should be borne in mind that the sample is limited to statistical information for 2021 and refers to the EU Member States.
Conclusions
The pursuit of long-term sustainability requires adjustments to current strategies in all stages of the value chain, from production to consumption, and SMEs bear great responsibility in this transition given the major contribution they make to growth. A linear use of resources has become obsolete; the goals set in the 2030 Agenda require a judicious use of resources oriented towards the CE, which guarantees to get the most out of all resources. In addition, companies must be prepared to meet the growing demand for GM, serving consumers who are keenly focused on the environment.
There is a need for an in-depth understanding of the current situation, and of where efforts should be directed to ensure that the actions undertaken by SMEs achieve the ultimate objective of reducing emissions and thus safeguarding the health of the climate. Against this backdrop, the present research seeks to make a novel contribution by conducting a detailed and quantitative study of measures in both the production stage of the value chain, through RE, and in the marketing stage, through initiatives such as GM, additionally analysing how the results could be improved by the introduction of complementary measures. The study has focused exclusively on European SMEs, given the major regulatory changes introduced by the European Commission in an effort to achieve a climate-neutral European economy and society by 2050 (European Green Deal or NextGenerationEU). Results provide quantitative evidence of the level of efficiency achieved in RE and in the activities carried out to modify production chains to meet the growing demand for green products and services.
They reveal an asymmetry between RE and the efficiency of GM. SMEs are not properly channelling their RE actions towards improving the health of the climate, indicating the need for more assistance. External and internal decision-making agents should increase incentives, subsidies, and advisory services during the phase in which SMEs’ own resources can give rise to actions such as water and energy saving, recycling, design of environmentally-friendly products, etc.
Limitations and futures lines of research
Despite the valuable contributions it makes, this research is not without its limitations, which should be taken into account for future analyses. First, it focuses solely on 2021, and does not examine previous periods due to the lack of homogeneous information. Second, it would be worth analysing whether specific features of each country are responsible for the situation of its SMEs. Third, it has not been possible to account for the economic sectors of the analysed companies due to a lack of related statistical information. Finally, future studies should conduct a comparison with the situation in another economic association such as NAFTA, BRICs or ASEAN, or with certain sectors of economic activity, in order to expand the study and ensure its universality.
Funding
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.
Data availability
Data are available upon request to the authors.
Declarations
Competing Interests
The authors declare that they have no personal, financial, professional, or organizational relationships that could influence the content of this article. Furthermore, there are no competing interests related to the work submitted for publication.
Abbreviations
Climate change
Circular economy
European Union
Small and medium-sized enterprises
Data envelopment analysis
Resource efficiency
Decision-making units
Constant returns to scale
Variable returns to scale
Output/Input orientation
Green markets
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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