Performance Evaluation of Mazandaran Water and Wastewater by Data Envelopment Analysis and Artificial Neural Network

Document Type: Research Paper

Authors

1 Faculty member of Mazandaran University of Science and Technology, I.R. Iran

2 Msc student of Industrial Management Institute, I.R. Iran

Abstract

In this study, Mazandaran Water and Wastewater Company’ performance is evaluated by using an input-oriented data envelopment analysis. As a principle, the performance of each organizational unit or organization should be measured as far as possible and what cannot be evaluated cannot be well governed. One method of evaluating the performance of units is data envelopment analysis method. One of the main problems of using data envelopment analysis is its low-resolution which it is due to the low number of decision making units to compare with the number of inputs and outputs. Given to the calculated efficiency by the DEA model (CCR input-oriented) for 16 decision making unit for years 1389 and 1390 there is the problem of existence of several efficient areas, which in the first step was used from Anderson and Peterson (AP) technique to cover this weaknesses. Since the AP technique involves solving a linear programming model for each of the DMUs. Therefore, by increasing the dimension of issue, efficiency assessment will be time consuming process. So the idea of using a neural network with efficiency data of data envelopment analysis is proposed as an alternative approach. Analytical results of calculated efficiencies of DMUs by the combination method of Neuro-DEA indicate the high power of neural network in resolution of decision-making areas in terms of efficiency.

Keywords


1. Niazi, M. (1384). The designing of performance measurement system of areas in Mazandaran Water and Wastewater Company, Industrial Management Master's thesis, High Education Institute of Planning Management of Mazandaran province.

2. Charnes, A., Cooper, W. W., and Rhodes, E. (1978). “Measuring the efficiency of decision making units.” European Journal of Operational Research, 2, 429-444.

3. Mehregan, M. R. (1387). Quantitative Models in Performance Evaluation agencies (DEA), Department of Management, Tehran University.

4. Ajaly, M. and Safari, H. (1390). “Performance evaluation of decision making units using the hybrid model of neural networks of predicting performance and data envelopment analysis (case study: National Iranian Gas Company).” Special Journal of Industrial Engineering, Vol 45, No. 1.

5. Mehregan, M. R., Frasat, A., and Kamyabmoghadas, A. (1385). “Analyzes the technical efficiency of oil refineries of company using a hybrid model of neural network and data envelopment analysis (Neuro-DEA).” Journal of Humanities and Social Sciences, sixth Year, N 23.

6. William Cooper., Lawrence Siford., Koraten., translation by Dr Mir-Hosseini, Ali (1389). Data envelopment analysis models and applications.

7. Ghafourian, M. (1383). Performance Evaluation of citizen offices of Telecom Company of Hormozgan province with data envelopment analysis method (DEA), Industrial Management Master's thesis, University of Shiraz.

8. Gholamrezayee, D. and Shah Tahmasebi, A. (1388). The relative performance assessment of country provinces in the achievement of Third Development Plan objectives in agriculture, agricultural and development economics section, seventeenth year, N 67.

9. Shalkoof Robert, J. (1382). Artificial Neural Networks, translation by Jorabiyan, M., Zare, T and Ostvar, O., martyr Chamran University Press of Ahvaz, first edition.

10. Menhaj, M. B. (1384). Foundations of Neural Networks, Vol 1, Amir Kabir Industrial University Press, third edition, Tehran.

11. Troutt, M. D., Rai, A., and Zhang, A. (1995). “The potential use of DEA for credit applicant acceptance system.” Computers and Operation research, 4, 405-408.

12. Farrell, M. (1957). “The Measurement of Productive Efficiency.” Journal of the Royal Statistics Society, Series A, Vol. 120, No. 3, 253-281.