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Application of a robust data envelopment analysis model for performance evaluation of electricity distribution companies

机译:强大的数据包络分析模型在电力分配公司绩效评估中的应用

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Purpose - This study evaluates the efficiency and productivity change of 39 electricity distribution companies in Iran over the period 2005-2014. For purposes of electricity management and utilization of scarce resources, Iran's 33 provinces have been classified into five regions by the Ministry of the Interior. Analyzing the efficiency of distribution companies across these regions yields significant understanding of these resources and helps policymakers to generate more informed decisions. Design/methodology/approach - The proposed method of this study develops nonparametric data envelopment analysis (DEA) with the consideration of geographic classification, size and type of company. At the first stage, a DEA model is used to estimate the relative technical efficiency and productivity change of these companies. At the second stage, distributions of efficiency improvements are examined based on geographic classification, size and type of the company type. A stability test is also conducted to verify the proposed model's robustness. Findings - The results demonstrate that the average technical efficiency of the companies increased during the years 2006-2009, but decreased during 2010-2014. The productivity measurement reveals that low efficiency change was the largest contributor to the small increase in productivity change rather than technology change. In addition, testing the hypothesis that the large and small companies have statistically the same efficiency scores revealed no statistical difference among them. Moreover, another test did not detect a difference among companies at the urban and provincial levels. Practical implications - By applying this approach, policymakers and practitioners in the power industry at the country and corporate level can effectively compare the efficiency and productivity changes among electricity distribution companies, and therefore generate more informed decisions. Originality/value - The paper's novel concept applies DEA to Iran's electricity distribution companies and analyzes them by examining geographic classification, size and the type of the companies. In addition, a stability test is conducted and productivity changes are estimated.
机译:目的 - 本研究在2005 - 2014年期间评估了伊朗39次配电公司的效率和生产率变化。出于电力管理和利用稀缺资源的用途,伊朗的33个省份被内政部分为五个地区。分析这些地区的分销公司的效率会产生重大了解这些资源,并帮助政策制定者产生更明智的决策。设计/方法/方法 - 本研究的建议方法通过考虑到地理分类,规模和类型的公司来发展非参数数据包络分析(DEA)。在第一阶段,DEA模型用于估计这些公司的相对技术效率和生产率变化。在第二阶段,基于公司类型的地理分类,大小和类型来检查效率改进的分布。还进行了稳定性测试以验证所提出的模型的鲁棒性。调查结果 - 结果表明,公司的平均技术效率在2006 - 2009年期间增加,但2010-2014期间减少。生产率测量表明,低效率变化是生产力变化的小幅增加而不是技术变化的最大贡献者。此外,测试大型和小型公司在统计上具有统计上相同的效率评分的假设显示出它们之间没有统计学差异。此外,另一项测试并未检测到城市和省级公司之间的差异。实际意义 - 通过将这种方法应用于国家和企业水平的电力行业的政策制定者和从业者可以有效地比较电力分销公司的效率和生产力变化,从而产生更明智的决策。原创性/价值 - 本文的小说概念将DEA适用于伊朗的电力分销公司,并通过检查公司的地理分类,规模和类型来分析它们。另外,进行稳定性测试,估计生产率变化。

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