Applying Network Data Envelopment Analysis Model in Evaluating Efficiency of Power Transmission Sector, in Iran Electricity Industry
Among strategic and infrastructure industries in each country, the electricity industry is the most important and critical one, which due to its capital-intensive and costly nature is considered as a unique industry. Hence, increasing efficiency and productivity in this industry is very important. S...
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Veröffentlicht in: | Mudīrīyat-i ṣanʻatī 2014-06, Vol.6 (2), p.263-282 |
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Zusammenfassung: | Among strategic and infrastructure industries in each country, the electricity industry is the most important and critical one, which due to its capital-intensive and costly nature is considered as a unique industry. Hence, increasing efficiency and productivity in this industry is very important. Since process of power transmission in Iran electricity industry carries out by regional electricity companies, this research has been done with purpose of investigating and evaluating mentioned company’s efficiency, by using nonparametric data envelopment analysis (DEA) method. Due to weakness of conventional and classical DEA models, in this research, network models have been used to evaluate efficiency of Iran regional electricity companies, and efficiency of companies’ internal units has been examined too. The present study is an applied research. Necessary information, to analyze the efficiency, have been extracted from the performance of listed companies in statistical yearbook of Iran electricity industry in the year of 2011, and research data have been analyzed by GAMS software. The results indicate that regional electricity companies in Isfahan, Zanjan and Kerman during all stages of their activities have unit efficiency. As well as, the results of this study indicate that there are significant differences between classical approaches and network data envelopment analysis (DEA) in determining efficiency of regional electricity companies, and to more careful analyzing companies, applying network models is necessary. |
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ISSN: | 2008-5885 2423-5369 |
DOI: | 10.22059/imj.2014.50840 |