Measuring Efficiency of Water and Wastewater Company: A DEA Approach

The aim of this study is to measuring the efficiency of Water and Wastewater Company (WWC). Data Envelopment Analysis (DEA) is a body of research methodologies to evaluate overall efficiencies and identify the sources and estimate the amounts of inefficiencies in inputs and outputs. In DEA, the best performers are called DEA efficient and the efficiency score of a DEA efficient unit is denoted by a unity. It is possible to prevent wasting resources and unreasonable increase of costs by measuring efficiency of various sections of the economy, especially servicing and nonprofit units. This research attempts to measure and compare technical efficiency value of 17 municipalities of Markazi province (Iran) in urban Water and Wastewater Company (WWC) by using DEA. Data for 2006 were used to estimate efficiency scores. The results indicated less than 30% of municipalities were fully technically efficient that could be referred as inefficient units. Capital input and water losses were the major source of the inefficiency. Thus, the policy makers should focus on rebuilding the infrastructure of the water networks, beginning with the most DEA inefficient municipalities in order to minimize water losses and maximize efficiency of capital input.

[1]  B. W. Ang,et al.  Decomposition analysis for policymaking in energy:: which is the preferred method? , 2004 .

[2]  B. W. Ang,et al.  Linear programming models for measuring economy-wide energy efficiency performance , 2008 .

[3]  Greg N. Gregoriou,et al.  An input-oriented super-efficiency measure in stochastic data envelopment analysis: Evaluating chief executive officers of US public banks and thrifts , 2010, Expert Syst. Appl..

[4]  Kaoru Tone,et al.  Data Envelopment Analysis , 1996 .

[5]  M. Khodabakhshi,et al.  CHANCE CONSTRAINED ADDITIVE INPUT RELAXATION MODEL IN STOCHASTIC DATA ENVELOPMENT ANALYSIS , 2010 .

[6]  Francisco J. Delgado.  Measuring efficiency with neural networks. An application to the public sector , 2005 .

[7]  C. Kirkpatrick,et al.  An Empirical Analysis of State and Private-Sector Provision of Water Services in Africa. , 2006 .

[8]  K. Witte.  How to stimulate natural monopolies? The drinking water experience , 2008 .

[9]  B. W. Ang,et al.  Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index , 2006 .

[10]  M. Abbott,et al.  The productivity and efficiency of the Australian electricity supply industry , 2006 .

[11]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[12]  Lei Tong,et al.  Efficiency assessment of coal mine safety input by data envelopment analysis , 2008 .

[13]  Surender Kumar,et al.  Measuring the performance of water service providers in urban India: implications for managing water utilities , 2012 .

[14]  Brian Dollery,et al.  The relative economic efficiency of urban water utilities in regional New South Wales and Victoria , 2010 .

[15]  A. U.S.,et al.  Measuring the efficiency of decision making units , 2003 .

[16]  Toshiyuki Sueyoshi,et al.  DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation , 2011 .

[17]  Thomas C. Kinnaman,et al.  The Economics of Residential Solid Waste Management , 1999 .

[18]  M. Farrell.  The Measurement of Productive Efficiency , 1957 .

[19]  David K. Lambert,et al.  Ownership and sources of inefficiency in the provision of water services , 1993 .