Application of a robust data envelopment analysis model for performance evaluation of electricity distribution companies. Issue 4 (14th October 2019)

• Record Type: Journal Article
• Authors: Fallahi, Alireza; Fallahi, Fatemeh; Sarhadi, Hassan; Ghaderi, S.F.; Ebrahimi, Reza
• Is Part Of: International journal of energy sector management. Volume 15:Issue 4(2021)
• Page Start: 724
• Page End: 742
• Publication Date: 2019-10-14
• Subjects: Efficiency -- Productivity -- Energy sector -- Linear programming -- Resource management -- Optimization -- DEA -- Electricity distribution -- Input-output tables -- Correlation analysis -- Energy balance; Energy industries -- Management -- Periodicals; 333.79068
• DOI: 10.1108/IJESM-08-2018-0008
• Languages: English
• ISSNs: 1750-6220

Abstract

Abstract : 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.