Measuring the eco-efficiency of the provision of drinking water by two-stage network data envelopment analysis

被引:10
作者
Mocholi-Arce, Manuel [1 ]
Sala-Garrido, Ramon [1 ]
Molinos-Senante, Maria [2 ]
Maziotis, Alexandros [2 ]
机构
[1] Univ Valencia, Dept Math Econ, Avd Tarongers S-N 5, Valencia, Spain
[2] Pontificia Univ Catolica Chile, Dept Ingn Hidraul & Ambiental, Avda Vicuna Mackenna, Santiago 4860, Chile
关键词
Eco-efficiency; England and Wales; Environmental variables; Greenhouse gas emissions; Network DEA (NDEA); Water utilities; ENVIRONMENTAL PERFORMANCE; UNDESIRABLE OUTPUTS; PRODUCTIVITY GROWTH; SHADOW PRICE; DEA; QUALITY; ENERGY; SERVICE; BENCHMARKING; EMISSIONS;
D O I
10.1007/s10668-021-01972-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The water production system is a complex network and policy makers can get a better insight into how the system operates if they know how efficient each sub-process is. In this study, and for the first time, we employ a two-stage network Data Envelopment Analysis model to evaluate the eco-efficiency of water services in England and Wales, integrating greenhouse gas (GHG) emissions as an undesirable output. We then use regression techniques to determine the impact of environmental variables on a water company's efficiency. The results indicate that from an economic perspective (first stage), companies need to reduce the costs of running their business by 22.3% on average to produce the same level of services. From an operations and environmental point of view (second stage), companies need to curtail down the levels of inputs and GHG emissions by 32.6% on average to generate the same level of output. Thus, the mean overall eco-efficiency was 0.514, which means that the potential for input and GHG emissions savings among companies was approximately 48.6%. Moreover, the complexity of water treatment and average pumping head could lead to lower eco-efficiency. Several policy implications are finally discussed.
引用
收藏
页码:12883 / 12899
页数:17
相关论文
共 63 条
[21]   Second stage DEA: Comparison of approaches for modelling the DEA score [J].
Hoff, Ayoe .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 181 (01) :425-435
[22]   A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China [J].
Huang, Jianhuan ;
Chen, Juanjuan ;
Yin, Zhujia .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
[23]   Network DEA: efficiency analysis of organizations with complex internal structure [J].
Lewis, HF ;
Sexton, TR .
COMPUTERS & OPERATIONS RESEARCH, 2004, 31 (09) :1365-1410
[24]   Comparing water footprint and water scarcity footprint of energy demand in China's six megacities [J].
Liao, Xiawei ;
Zhao, Xu ;
Liu, Wenfeng ;
Li, Ruoshui ;
Wang, Xiaoxi ;
Wang, Wenpeng ;
Tillotson, Martin R. .
APPLIED ENERGY, 2020, 269
[28]   Performance assessment of water companies: A metafrontier approach accounting for quality of service and group heterogeneities [J].
Mocholi-Arce, Manuel ;
Sala-Garrido, Ramon ;
Molinos-Senante, Maria ;
Maziotis, Alexandros .
SOCIO-ECONOMIC PLANNING SCIENCES, 2021, 74
[29]   Assessing the influence of exogenous and quality of service variables on water companies′ performance using a true-fixed stochastic frontier approach [J].
Molinos-Senante, Maria ;
Maziotis, Alexandros .
URBAN WATER JOURNAL, 2018, 15 (07) :682-691
[30]   Reducing CO2 emissions from drinking water treatment plants: A shadow price approach [J].
Molinos-Senante, Maria ;
Guzman, Catalina .
APPLIED ENERGY, 2018, 210 :623-631