Benchmarking the efficiency of the Chilean water and sewerage companies: a double-bootstrap approach

Benchmarking the efficiency of water companies is essential to set water tariffs and to promote their sustainability. In doing so, most of the previous studies have applied conventional data envelopment analysis (DEA) models. However, it is a deterministic method that does not allow to identify envi...

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Bibliographic Details
Published in:Environmental science and pollution research international 2018-03, Vol.25 (9), p.8432-8440
Main Authors: Molinos-Senante, María, Donoso, Guillermo, Sala-Garrido, Ramon, Villegas, Andrés
Format: Article
Language:English
Subjects:
Aquatic Pollution
Atmospheric Protection/Air Quality Control/Air Pollution
Benchmarking - statistics & numerical data
Benchmarks
Chile
Computing time
Data envelopment analysis
Data processing
Earth and Environmental Science
Ecotoxicology
Efficiency
Efficiency, Organizational
Environment
Environmental Chemistry
Environmental factors
Environmental Health
Environmental science
Operations research
Research Article
Sewer systems
Sewerage
Sustainability
Waste Water Technology
Water
Water Management
Water Pollution Control
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Summary:Benchmarking the efficiency of water companies is essential to set water tariffs and to promote their sustainability. In doing so, most of the previous studies have applied conventional data envelopment analysis (DEA) models. However, it is a deterministic method that does not allow to identify environmental factors influencing efficiency scores. To overcome this limitation, this paper evaluates the efficiency of a sample of Chilean water and sewerage companies applying a double-bootstrap DEA model. Results evidenced that the ranking of water and sewerage companies changes notably whether efficiency scores are computed applying conventional or double-bootstrap DEA models. Moreover, it was found that the percentage of non-revenue water and customer density are factors influencing the efficiency of Chilean water and sewerage companies. This paper illustrates the importance of using a robust and reliable method to increase the relevance of benchmarking tools.
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-017-1149-x