Author
Listed:
- María Molinos‐Senante
- Alexandros Maziotis
- Ramón Sala‐Garrido
Abstract
Assessing the eco‐efficiency of municipalities regarding the provision of solid waste services is a useful tool for improving its sustainability. However, robust, and reliable methods are needed to benchmark the performance of municipalities. Data envelopment analysis (DEA) methods typically used to assess the eco‐efficiency of municipal solid waste (MSW) service providers. However, the variables used in the eco‐efficiency assessment bear distinct weights for each individual unit, limiting thus interpretation. Therefore, benchmarking the performance of MSW service providers becomes challenging because different conditions are applied. Thus, this study uses a common set weights DEA (DEA‐CSW) model assess the eco‐efficiency of different municipalities in providing MSW services. Eco‐efficiency scores were estimated by integrating total costs, recycled waste and unsorted waste as input, desirable outputs and undesirable outputs, respectively. The empirical application of the model demonstrated that when using DEA‐CSW, only one municipality (out of 36) was eco‐efficient in managing MSW. The weightings for inputs and outputs were allocated based on the degree of satisfaction estimated for each municipality. Satisfaction ranged from 0.829 to 1.000 indicating that none of the municipalities were heavily penalized based on the eco‐efficiency scores estimation when allocating common weights. In conclusion, this study demonstrates that compared to traditional DEA models, the DEA‐CSW approach is more adequate at benchmarking the performance of municipalities regarding the provision of MSW services.
Suggested Citation
María Molinos‐Senante & Alexandros Maziotis & Ramón Sala‐Garrido, 2024.
"Estimating the eco‐efficiency of urban waste services towards sustainable waste management,"
Sustainable Development, John Wiley & Sons, Ltd., vol. 32(5), pages 5677-5691, October.
Handle:
RePEc:wly:sustdv:v:32:y:2024:i:5:p:5677-5691
DOI: 10.1002/sd.2983
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