Governmental effectiveness in the transition to a circular economy: Dynamic DEA model
This study applies Data Envelopment Analysis (DEA) model to the problem of assessing the results of government support of transition to a circular economy development in 27 EU countries in 2014–2021. The performance of governments is evaluated in terms of creating conditions for the development of cost-effective business models and technologies that can operate without permanent incentives and benefits from the state. This approach differs from the models popular in the current literature, which assess the efficiency of the circular economy primarily in terms of improved environmental performance. Calculations show that the most efficient models of circular economy are created by Austria, France, Germany, Italy, Luxembourg, Malta, and Sweden. • The performance of governments is evaluated in terms of creating conditions for the development of cost-effective business models and technologies. • The most efficient circular economy models have been developed by Austria, France, Germany, Italy, Luxembourg, Malta, and Sweden. • Cyprus, Greece, the Netherlands and Spain showed the best growth dynamics in circular economy efficiency. • The circular economy systems in most EU countries display decreasing returns to scale.
Authors
- Светлана Ратнер (ORCID: https://orcid.org/0000-0003-3485-5595)
- Andrey V. Lychev (ORCID: https://orcid.org/0000-0003-1532-1141)
- Светлана Балашова (ORCID: https://orcid.org/0000-0003-1797-8825)
- V. E. Krivonozhko (ORCID: https://orcid.org/0000-0003-0583-2829)
Institutions
- National University of Science and Technology (RU)
- Peoples' Friendship University of Russia (RU)
- Lomonosov Moscow State University (RU)
- V. A. Trapeznikov Institute of Control Sciences (RU)
Publication Details
- Journal
- Unconventional Resources
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1016/j.uncres.2025.100161
- Citations
- 3
- Primary Topic
- Sustainable Supply Chain Management
- Type
- article
- Field-Weighted Citation Impact
- 6.68
Funders
- Russian Science Foundation