scholarly journals Measuring operational and quality-adjusted efficiency of Chilean water companies

2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Ramon Sala-Garrido ◽  
Manuel Mocholí-Arce ◽  
Maria Molinos-Senante ◽  
Alexandros Maziotis
Keyword(s):  
Water Cycle ◽  
Water Utilities ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Operational Quality ◽  
Average Water ◽  
Water Companies ◽  
Analysis Models ◽  
Mixed Water ◽  
Scale Of Operation

AbstractThe path to a sustainable management of the urban water cycle requires the assessment of both operational and quality-adjusted efficiency in a unified manner. This can be done by the use of non-radial Data Envelopment Analysis models. This study used Range Adjusted Measure models to evaluate the operational, quality-adjusted, and operational & quality-adjusted efficiency (O&QAE) scores of the Chilean water industry including water leakage and unplanned interruptions as undesirable outputs. It was found that on average water utilities presented large O&QAE scores over time. The mean O&QAE score was 0.964 which means that water utilities could further reduce costs and undesirable outputs by 3.6% on average, while trying to expand the scale of operation. This finding suggests that excellent quality-adjusted efficiency at an efficient expenditure could be feasible. It was also evidenced that customer density, mixed water resources, and ownership influenced the O&QAE of Chilean water companies.

scholarly journals A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

2021 ◽  
Vol 9 (4) ◽  
pp. 378-398
Author(s):  
Chunhua Chen ◽  
Haohua Liu ◽  
Lijun Tang ◽  
Jianwei Ren
Keyword(s):  
Data Envelopment Analysis ◽  
Transportation Systems ◽  
Decision Makers ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Super Efficiency ◽  
Dea Model ◽  
Dea Models ◽  
Analysis Models ◽  
Transport Accidents

Abstract DEA (data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure (RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model, especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA model with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs; 2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable; 3) The results can be easily obtained as it is based on linear programming; 4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems (RTSs) considering the number of transport accidents (an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.

scholarly journals Eco-Efficiency of the English and Welsh Water Companies: A Cross Performance Assessment

2021 ◽  
Vol 18 (6) ◽  
pp. 2831
Author(s):  
Ramon Sala-Garrido ◽  
Manuel Mocholi-Arce ◽  
Maria Molinos-Senante ◽  
Michail Smyrnakis ◽  
Alexandros Maziotis
Keyword(s):  
Ghg Emissions ◽  
High Energy ◽  
Policy Implications ◽  
Water Utilities ◽  
Data Envelopment ◽  
Regression Techniques ◽  
Water Companies ◽  
Large Water ◽  
Treatment Complexity ◽  
First Time

Analyzing costs and greenhouse gas (GHG) emissions could be of great importance for the water utilities to supply water services in a healthy and sustainable manner. In this study, we measured the eco-efficiency of several water utilities in England and Wales by incorporating GHG as an undesirable output. For the first time, we evaluated the eco-efficiency of the water production process using robust cross-efficiency data envelopment analysis (DEA) techniques. The further use of clustering and regression techniques allowed us to better understand the drivers of eco-efficiency. The results showed that the mean eco-efficiency of the water sector was 0.748, which indicates that costs and GHG emissions could be reduced by 25.2% to generate the same level of output. Large water companies with high energy costs and levels of GHG emissions belonged to the less eco-efficient group. Environmental factors related to density, topography, and treatment complexity further impacted eco-efficiency. Finally, we linked our results to the regulatory cycle and discuss some policy implications.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

Multidimensional Visualization of Data Envelopment Analysis Models

2021 ◽  
Vol 5 (2) ◽  
pp. 339-361
Author(s):  
Alexander P. Afanasiev ◽  
Vladimir E. Krivonozhko ◽  
Finn R. Førsund ◽  
Andrey V. Lychev
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Multidimensional Visualization ◽  
Visualization Of Data ◽  
Analysis Models

Fuzzy Data Envelopment Analysis Models with R Codes

2019 ◽  
pp. 163-236
Author(s):  
Farhad Hosseinzadeh Lotfi ◽  
Ali Ebrahimnejad ◽  
Mohsen Vaez-Ghasemi ◽  
Zohreh Moghaddas
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Fuzzy Data Envelopment Analysis ◽  
Analysis Models
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