Efficiency-based rank assessment for electric power industry: A combined use of Data Envelopment Analysis (DEA) and DEA-Discriminant Analysis (DA)

被引:117
作者
Sueyoshi, Toshiyuki [1 ]
Goto, Mika [2 ]
机构
[1] New Mexico Inst Min & Technol, Dept Management, Socorro, NM 87801 USA
[2] Cent Res Inst Elect Power Ind, Komae, Tokyo 2018511, Japan
关键词
Electric power industry; DEA; DEA-DA; WILLIAM W. COOPER; TECHNICAL EFFICIENCY; PERFORMANCE; GENERATION; RETURNS; PLANTS; SCALE;
D O I
10.1016/j.eneco.2011.04.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study discusses a combined use of DEA (Data Environment Analysis) and DEA-DA (Discriminant Analysis) to determine the efficiency-based rank of energy firms. This type of performance evaluation is important because we often have a difficulty in accessing a large sample on energy firms to derive reliable empirical results. The proposed approach is useful in dealing with such a limited number of energy firms, often found in previous DEA studies on energy industries in the world. The proposed approach uses DEA to classify energy firms into efficient and inefficient groups based upon their efficiency scores. Then, it utilizes DEA-DA to assess their efficiency scores and ranks. In this stage, we can find an adjusted efficiency score for each energy firm. The proposed approach provides us with the following analytical capabilities, all of which cannot be found in a conventional use of DEA in assessing energy firms. First, the proposed DEA approach can avoid zero in all multipliers on efficient energy firms by incorporating SCSC (Strong Complementary Slackness Condition) so that it can handle an occurrence of multiple reference sets and multiple projections. The DEA result classifies all energy firms into efficient and inefficient groups. Second, DEA-DA, applied to the two groups, evaluates all energy firms by an industry-wide evaluation, not depending upon a limited number of efficient energy firms in a reference set, as found in a conventional use of DEA. The analytical capability can reduce the number of efficient energy firms. Third, the proposed approach can provide their efficiency-based ranking scores. Finally, we can conduct a rank sum test based upon their ranking scores to obtain a statistical inference. As an application, this study uses the proposed approach to examine the performance of Japanese electric power industry. We find two economic implications. One of the two implications is that no major change has occurred in the operational performance of Japanese electric power industry because of Japanese sluggish economy from 2005 to 2009. The other implication indicates that there are strategic differences in the operation of Japanese electric power firms after the liberalization. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:634 / 644
页数:11
相关论文
共 36 条
[1]   The productivity and efficiency of the Australian electricity supply industry [J].
Abbott, Malcolm .
ENERGY ECONOMICS, 2006, 28 (04) :444-454
[2]   Economic and environmental efficiency of district heating plants [J].
Agrell, PJ ;
Bogetoft, P .
ENERGY POLICY, 2005, 33 (10) :1351-1362
[3]  
[Anonymous], 2001, UTIL POLICY
[4]  
AVERCH H, 1962, AM ECON REV, V52, P1052
[5]   An integrated, DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors [J].
Azadeh, A. ;
Amalnick, M. S. ;
Ghaderi, S. F. ;
Asadzadeh, S. M. .
ENERGY POLICY, 2007, 35 (07) :3792-3806
[6]   Technical efficiency of thermoelectric power plants [J].
Barros, Carlos Pestana ;
Peypoch, Nicolas .
ENERGY ECONOMICS, 2008, 30 (06) :3118-3127
[7]   Efficiency analysis of hydroelectric generating plants: A case study for Portugal [J].
Barros, Carlos Pestana .
ENERGY ECONOMICS, 2008, 30 (01) :59-75
[8]   CONE RATIO DATA ENVELOPMENT ANALYSIS AND MULTI-OBJECTIVE PROGRAMMING [J].
CHARNES, A ;
COOPER, WW ;
WEI, QL ;
HUANG, ZM .
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1989, 20 (07) :1099-1118
[9]   New concepts, methodologies and algorithms for business education and research in the 21st century [J].
Dyson, Robert ;
Glover, Fred ;
Ijiri, Yuji ;
Whinston, Andrew ;
Sueyoshi, Toshiyuki .
DECISION SUPPORT SYSTEMS, 2010, 48 (03) :427-429
[10]  
Emrouznejad A., 2008, Journal of Socio-Economics Planning Science, V42, P151, DOI DOI 10.1016/J.SEPS.2007.07.002