Document Type : Original Article
Authors
1 Faculty of Engineering, Islamic Azad University, Central Tehran Branch, Tehran, Iran
2 Department of Basic Science, Science and Research Branch, Islamic Azad University, Tehran, IRAN
3 Department of Mothematics , Shahr-e-Qods Branch , Islamic Azad University, Tehran, IRAN
Abstract
Assessment of progress and regression of organizations is necessary to determine their performance and determination of the efficacy of managerial decisions, supply usage, and weak and strong points for the senior managers and decision-makers. They can improve the efficiency of the units based on this assessment. In this paper, using data envelopment analysis, the performance of regional electric companies of Iran in 2015 and 2016 is assessed. Because of semi-positive and negative indexes, the Slack-Based Measure (SBM) model of efficiency is developed for the 16 regional electric companies of Iran. To determine progress and regression in 2016 compared with 2015, models are proposed to compute the indexes of productivity. Finally, solving the proposed models, the Malmquist productivity index is computed for regional electric companies of Iran with 18 input, intermediate and output indexes and considering the amount of production of renewable energies as one of the important output indexes because of the irrefutable necessity of this kind of energies in the world. Their progress and regression are obtained using the Gams software showing progress in two companies, and regression in 13 companies while one company had neither progress nor regression. Studies performed show that agility of the organizational structure, financial and human resource limitations, sanctions and imbalance between the actual price of production of one kilowatt-hour of electricity and its sale price are most effective factors on the progress and regression of the companies.
Keywords
- Data envelopment analysis
- Slack Based Measure (SBM) of efficacy
- Malmquist productivity index
- Renewable energy
- Semi-positive and negative indexes
Main Subjects
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