Ranking European countries on the basis of their environmental and circular economy performance: A DEA application in MSW
Introduction
Municipal Solid Waste (MSW) is not only an unavoidable product of our daily life, but also a complex and serious problem for our societies, due to the environmental impacts associated with its management. Ιndustry’s heavy dependence on the extraction and utilization of new materials and resources further exacerbates these environmental problems. Moreover, competition for scarce resources and high prices of raw materials put pressure on the competitiveness of European economies.
In view of these problems, the European Union (EU) faces two key challenges in the waste management sector. Firstly, to diminish the level of waste generation, “approaching production and consumption in a more thoughtful, effective, and responsible manner” (Corvellec et al., 2018), since the environmental benefits of avoiding waste clearly far exceed the environmental impacts of managing it. Secondly, to move waste management up the EU waste hierarchy (WH), by diverting waste towards treatments that allow re-using, recycling, composting and recovering energy from it (European Parliament and Council, 2008).
The transformation of the waste management sector will also be crucial in the transition towards a circular economy (CE), where products and materials are maintained and used for as long as possible, minimizing waste and resource use (European Commission, 2015a, European Commission, 2015b, European Commission, 2015c, European Commission, 2015d, European Commission, 2015e). Towards this end, the EC (2015b) introduced the Circular Economy package “Closing the loop – An EU action plan for the circular economy”, with ambitious targets for waste management, based on the EU WH. The package aims to promote a sustainable economy and alleviate the environmental pressures from waste, while providing European industries with high-quality secondary raw materials to be fed back into the production process.
Indeed, the concept of CE has gained significant prominence in today’s politics, with its supporters emphasizing the economic opportunities it can create (World Economic Forum, 2014, European Commission, 2015c), as well as the expected environmental and societal benefits (MacArthur, 2015, Wijkman and Skånberg, 2015, Reike et al., 2018).
However, CE is also strongly criticized as being merely a concept in early stage (Kirchherr et al., 2017), that lacks sufficient conceptualization (Blomsma and Brennan, 2017) and a proper constructed framework (Lazarevic and Valve, 2017) and for failing to place enough weight on the social dimensions (Murray et al., 2017). Similarly, the EU WH has been criticized, as a concept, for many reasons, such as being inefficient to promote reduction of waste (Kijak and Moy, 2004, Barti, 2014, Ferrari et al., 2016), for not distinguishing different forms of recycling (Pires and Martinho, 2019) and even for its priority options with regards to their environmental impacts (Finnveden et al., 2005, Van Ewijk and Stegemann, 2016).
Despite these concerns, the examination of which is beyond the scope of this article, we believe that promoting efficient and environmentally friendly waste management and some form of circularity in today’s resource strained global economy is important. Therefore, it is vital for policymakers and scientists to be able to measure waste management (hereafter environmental) performance and also to assess if EU countries are on the right track towards a more efficient exploitation of recycled materials (hereafter circular economy performance).
Nevertheless, assessing this progress is not a simple task. Although there are several intergovernmental, national and private initiatives aiming at measuring the progress in the implementation of the WH, in conjunction or not with the transitioning to a circular economy (European Commission, 2018a, European Commission, 2018b, Mayer et al., 2019; Blomsma and Brennan, 2017; Pires and Martinho, 2019, Sassanelli et al., 2019), no commonly accepted framework exists (Bocken et al., 2016, Smol et al., 2017).
Making a step towards this direction, the European Commission (2018b) adopted a monitoring framework for circular economy that comprises ten indicators and serves as a tool for monitoring key trends in the transition and the success of taken measures, with respect to the related targets imposed by the EU legislation (European Commission, 2018a, European Commission, 2018b). However, this set of indicators does not encompass the economic, social, and technical issues of CE in order to provide a holistic evaluation of waste management and economic circularity (see Iacovidou et al., 2017). In other words, although these indicators are useful for measuring the absolute performance of countries with respect to specific targets, they ignore the differences in the managerial abilities of these countries, which are driven by their economic and social status and thus, can lead to an underestimation or overestimation of their performance.
However, it is possible to combine some of these indices and construct a composite indicator (see e.g. Cylus et al., 2017), which can account for these economic and social differences. This is the approach we take in our study by implementing Data Envelopment Analysis (DEA) to measure the relative environmental performance (EP) and the CE performance (CEP) of EU countries. We do so by utilizing three out of the ten indicators adopted by the European Commission for the CE monitoring framework, namely the generation of MSW per capita, the MSW recycling rate (hereafter recycling rate) and CMUr, along with the Social Progress Index (SPI). We only use those three CE indicators, since the others are inappropriate for our analysis, either because they are related to other aspects of the CE like competitiveness and innovation or to a specific waste stream, while the indicator “Trade in recyclable raw materials” is already taken into evaluation in the computation of CMUr.
Summing up, two are the main contributions of our work. Firstly, to the best of our knowledge, this is one of the first attempts in the literature to measure relative EP and CEP, by incorporating in a DEA model, variables capturing social factors. Secondly, the performances calculated by the DEA models can be viewed as composite indicators that better reflect EP and CEP, compared to single indices. Therefore, the proposed framework can be used as a more objective tool for identifying best and worst performing countries and thus, can facilitate the development of relevant policies both at the EU and at a Member State level.
The remainder of the paper is organized as follows. Firstly, we provide a brief overview of MSW management in the EU and the transnational waste trade. In Section 3 we review the state of the existing DEA-literature on MSW. The methodology and the data used in the present study are incorporated in Section 4. Section 5 presents the results, along with some necessary discussion. Finally, Section 6 concludes.
Section snippets
MSW management and trade in EU
Naturally, the economic and social differences between the EU countries manifest themselves into differences in MSW generation and management, as evidenced by the Eurostat data used throughout this chapter (unless otherwise specified). In 2017, the average per capita MSW generation in the EU was 486 kg/year; a figure which is far higher for more developed countries and lower for poorer countries. Also, MSW generation is still increasing in around one-third of the Member States, despite
Literature review of MSW studies using DEA
DEA, developed by Charnes, Cooper and Rhodes (1978), has gained a prominent role in studies measuring the efficiency, productivity, or performance of a set of peer units. Its flexibility and adaptability to a variety of problems have permitted its application in a wide range of diversified fields, mainly in energy, agriculture, banking, industry, as well as, in public policy (Emrouznejad and Yang, 2017). However, its use is still limited in scientific publications on solid waste, although it is
Methodology
The aim of this research is to measure the relative performance of the EU countries in managing and exploiting MSW, using DEA; a linear programming technique used for measuring the production efficiency or operational performance of similar activity units, commonly referred to as “decision making units” (or DMUs).
The key advantage of DEA and the main reason for its utilization is its non-parametric approach. Each DMU is treated as a “black box”, in the sense that there is no exact knowledge of
Results
The DEA model was implemented within the AIMMS modelling environment with CPLEX used as the standard solver. The results of the EP and the CEP models were obtained by solving the basic and the weight restricted linear programming problems with the respective inputs and outputs. The optimal value of the objective function for each DMU (country) is the EP and the CEP performance indicator respectively.
Starting with the results of the EP model (Table 4) for 2014, our calculations show that the
Conclusions
Summing up, the results of our study show that there are large disparities among EU countries, with respect to their environmental and circular economy performance. Interestingly though, the borders between Western and Eastern Europe, but not between the north and the south, have fallen: old EU members, such as Spain or France, perform significantly worse, both from an environmental and a circular economy perspective, than newer member states such as Slovenia or Poland, while southern countries
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We should like to thank Editor-in-Chief Morton Barlaz for his constructive guidance. We are also grateful to all the anonymous reviewers, for their time and their invaluable comments and suggestions.
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
References (109)
- et al.
Determinants of efficiency in the provision of municipal street-cleaning and refuse collection services
Waste Manage.
(2011) - et al.
Incorporating the learning effect into data envelopment analysis to measure MSW recycling performance
Eur. J. Oper. Res.
(2013) - et al.
Measuring the efficiency of decision making units
Eur. J. Oper. Res.
(1978) A performance evaluation of MSW management practice in Taiwan
Resour. Conserv. Recycl.
(2010)- et al.
Cost-efficiency in packaging waste management: The case of Belgium
Resour. Conserv. Recycl.
(2014) Pitfalls and protocols in DEA
Eur. J. Oper. Res.
(2001)Life cycle assessment of energy from solid waste-part 1: general methodology and results
J. Cleaner Prod.
(2005)- et al.
An application procedure for data envelopment analysis
Omega
(1989) - et al.
Performance assessment for municipal solid waste collection in Taiwan
J. Environ. Manage.
(2011) Metrics for optimising the multi-dimensional value of resources recovered from waste in a circular economy: A critical review
J. Cleaner Prod.
(2017)
Productive efficiency of public and private solid waste logistics and its implications for waste management policy
IATSS Res.
Narrating expectations for the circular economy: towards a common and contested European transition
Energy Res. Social Sci.
Hybrid dynamic network data envelopment analysis
Discrete Dyn. Nat. Soc.
Centralised target setting for regional recycling operations using DEA
Omega
Exploring social dimensions of municipal solid waste management around the globe – A systematic literature review
Waste Manage.
Waste hierarchy index for circular economy in waste management
Waste Manage.
Optimal weights in DEA models with weight restrictions
Eur. J. Oper. Res.
The circular economy: New or refurbished as CE 3.0? — exploring controversies in the conceptualization of the circular economy through a focus on history and resource value retention options
Resour. Conserv. Recycl.
Evaluating the efficiency of municipalities in collecting and processing municipal solid waste: A shared input DEA-model
Waste Manage.
Measuring and explaining the cost efficiency of municipal solid waste collection and processing services
Omega
Circular economy performance assessment methods: A systematic literature review
J. Cleaner Prod.
Performance assessment of refuse collection services using robust efficiency measures
Resour. Conserv. Recycl.
Moving from recycling to waste prevention: A review of barriers and enables
Waste Manage. Res.
The emergence of circular economy: a new framing around prolonging resource productivity’
J. Indus. Ecol.
Product design and business model strategies for a circular economy
J. Ind. Prod. Eng.
Introduction to Data Envelopment Analysis and its Uses: With DEA-solver Software and References
Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software
An evaluation of technical efficiency and managerial correlates of solid waste management by Welsh SMEs using parametric and non-parametric techniques
J. Oper. Res. Soc.
Output-orientated Data Envelopment Analysis for measuring recycling efficiency: an application at Italian regional level
Environ. Educ. Res.
Using data envelopment analysis to address the challenges of comparing health system efficiency
Glob Policy
The greening of the globe? Cross-national levels of environmental group membership
Environ. Politics
A robust indicator for promoting Circular Economy through recycling
J. Environ. Protection
A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016
Socio-Econ. Planning Sci.
Waste Prevention Programme, Belgium Fact Sheet
Cited by (79)
Coupling and coordinated evolution characteristics of regional economy-energy-carbon emission multiple systems: A case study of main China's Basin
2024, Journal of Environmental Sciences (China)Assessing the progress of the mining industry towards green growth in China: A three-stage dynamic network slacks-based measure approach
2024, Journal of Cleaner ProductionThe impact of circular economy indicators in the optimal planning of energy systems
2024, Sustainable Production and ConsumptionA global and comparative assessment of the level of economic circularity in the EU
2023, Journal of Cleaner ProductionA multi-criteria approach to assess interconnections among the environmental, economic, and social dimensions of circular economy
2023, Journal of Environmental Management