IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v34y2012i3p634-644.html
   My bibliography  Save this article

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

Author

Listed:
  • Sueyoshi, Toshiyuki
  • Goto, Mika

Abstract

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.

Suggested Citation

  • Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Efficiency-based rank assessment for electric power industry: A combined use of Data Envelopment Analysis (DEA) and DEA-Discriminant Analysis (DA)," Energy Economics, Elsevier, vol. 34(3), pages 634-644.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:3:p:634-644
    DOI: 10.1016/j.eneco.2011.04.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988311000843
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2011.04.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sueyoshi, Toshiyuki & Goto, Mika, 2009. "Methodological comparison between DEA (data envelopment analysis) and DEA-DA (discriminant analysis) from the perspective of bankruptcy assessment," European Journal of Operational Research, Elsevier, vol. 199(2), pages 561-575, December.
    2. Barros, Carlos Pestana, 2008. "Efficiency analysis of hydroelectric generating plants: A case study for Portugal," Energy Economics, Elsevier, vol. 30(1), pages 59-75, January.
    3. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis," Energy Policy, Elsevier, vol. 38(10), pages 5902-5911, October.
    4. Abbott, Malcolm, 2006. "The productivity and efficiency of the Australian electricity supply industry," Energy Economics, Elsevier, vol. 28(4), pages 444-454, July.
    5. Sueyoshi, Toshiyuki, 2006. "DEA-Discriminant Analysis: Methodological comparison among eight discriminant analysis approaches," European Journal of Operational Research, Elsevier, vol. 169(1), pages 247-272, February.
    6. Mukherjee, Kankana, 2008. "Energy use efficiency in U.S. manufacturing: A nonparametric analysis," Energy Economics, Elsevier, vol. 30(1), pages 76-96, January.
    7. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    8. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2007. "The measurement of returns to scale under a simultaneous occurrence of multiple solutions in a reference set and a supporting hyperplane," European Journal of Operational Research, Elsevier, vol. 181(2), pages 549-570, September.
    9. Sueyoshi, Toshiyuki & Goto, Mika & Shang, Jennifer, 2009. "Core business concentration vs. corporate diversification in the US electric utility industry: Synergy and deregulation effects," Energy Policy, Elsevier, vol. 37(11), pages 4583-4594, November.
    10. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2007. "Measurement of returns to scale using a non-radial DEA model: A range-adjusted measure approach," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1918-1946, February.
    11. Agrell, Per J. & Bogetoft, Peter, 2005. "Economic and environmental efficiency of district heating plants," Energy Policy, Elsevier, vol. 33(10), pages 1351-1362, July.
    12. Olatubi, Williams O. & Dismukes, David E., 2000. "A data envelopment analysis of the levels and determinants of coal-fired electric power generation performance," Utilities Policy, Elsevier, vol. 9(2), pages 47-59, June.
    13. Azadeh, A. & Amalnick, M.S. & Ghaderi, S.F. & Asadzadeh, S.M., 2007. "An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors," Energy Policy, Elsevier, vol. 35(7), pages 3792-3806, July.
    14. Pombo, Carlos & Taborda, Rodrigo, 2006. "Performance and efficiency in Colombia's power distribution system: Effects of the 1994 reform," Energy Economics, Elsevier, vol. 28(3), pages 339-369, May.
    15. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    16. Lam, Pun-Lee & Shiu, Alice, 2001. "A data envelopment analysis of the efficiency of China's thermal power generation," Utilities Policy, Elsevier, vol. 10(2), pages 75-83, June.
    17. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    18. Sarıca, Kemal & Or, Ilhan, 2007. "Efficiency assessment of Turkish power plants using data envelopment analysis," Energy, Elsevier, vol. 32(8), pages 1484-1499.
    19. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    20. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Measurement of a linkage among environmental, operational, and financial performance in Japanese manufacturing firms: A use of Data Envelopment Analysis with strong complementary slackness condition," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1742-1753, December.
    21. Vaninsky, Alexander, 2006. "Efficiency of electric power generation in the United States: Analysis and forecast based on data envelopment analysis," Energy Economics, Elsevier, vol. 28(3), pages 326-338, May.
    22. Nag, Barnali, 2006. "Estimation of carbon baselines for power generation in India: the supply side approach," Energy Policy, Elsevier, vol. 34(12), pages 1399-1410, August.
    23. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2009. "An occurrence of multiple projections in DEA-based measurement of technical efficiency: Theoretical comparison among DEA models from desirable properties," European Journal of Operational Research, Elsevier, vol. 196(2), pages 764-794, July.
    24. Barros, Carlos Pestana & Peypoch, Nicolas, 2008. "Technical efficiency of thermoelectric power plants," Energy Economics, Elsevier, vol. 30(6), pages 3118-3127, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    2. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "Operational synergy in the US electric utility industry under an influence of deregulation policy: A linkage to financial performance and corporate value," Energy Policy, Elsevier, vol. 39(2), pages 699-713, February.
    3. Sueyoshi, Toshiyuki & Goto, Mika, 2010. "Should the US clean air act include CO2 emission control?: Examination by data envelopment analysis," Energy Policy, Elsevier, vol. 38(10), pages 5902-5911, October.
    4. Sueyoshi, Toshiyuki & Goto, Mika & Ueno, Takahiro, 2010. "Performance analysis of US coal-fired power plants by measuring three DEA efficiencies," Energy Policy, Elsevier, vol. 38(4), pages 1675-1688, April.
    5. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Returns to scale and damages to scale on U.S. fossil fuel power plants: Radial and non-radial approaches for DEA environmental assessment," Energy Economics, Elsevier, vol. 34(6), pages 2240-2259.
    6. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "Environmental assessment on coal-fired power plants in U.S. north-east region by DEA non-radial measurement," Energy Economics, Elsevier, vol. 50(C), pages 125-139.
    7. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Returns to Scale and Damages to Scale with Strong Complementary Slackness Conditions in DEA Assessment: Japanese Corporate Effort on Environment Protection," Energy Economics, Elsevier, vol. 34(5), pages 1422-1434.
    8. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA radial and non-radial models for unified efficiency under natural and managerial disposability: Theoretical extension by strong complementary slackness conditions," Energy Economics, Elsevier, vol. 34(3), pages 700-713.
    9. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "DEA environmental assessment in time horizon: Radial approach for Malmquist index measurement on petroleum companies," Energy Economics, Elsevier, vol. 51(C), pages 329-345.
    10. Sueyoshi, Toshiyuki & Goto, Mika, 2015. "Japanese fuel mix strategy after disaster of Fukushima Daiichi nuclear power plant: Lessons from international comparison among industrial nations measured by DEA environmental assessment in time hori," Energy Economics, Elsevier, vol. 52(PA), pages 87-103.
    11. Chiu, Ching-Ren & Liou, Je-Liang & Wu, Pei-Ing & Fang, Chen-Ling, 2012. "Decomposition of the environmental inefficiency of the meta-frontier with undesirable output," Energy Economics, Elsevier, vol. 34(5), pages 1392-1399.
    12. Sueyoshi, Toshiyuki & Goto, Mika & Sugiyama, Manabu, 2013. "DEA window analysis for environmental assessment in a dynamic time shift: Performance assessment of U.S. coal-fired power plants," Energy Economics, Elsevier, vol. 40(C), pages 845-857.
    13. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "Methodological comparison between two unified (operational and environmental) efficiency measurements for environmental assessment," European Journal of Operational Research, Elsevier, vol. 210(3), pages 684-693, May.
    14. Wang, Derek & Li, Shanling & Sueyoshi, Toshiyuki, 2014. "DEA environmental assessment on U.S. Industrial sectors: Investment for improvement in operational and environmental performance to attain corporate sustainability," Energy Economics, Elsevier, vol. 45(C), pages 254-267.
    15. Sueyoshi, Toshiyuki & Goto, Mika, 2016. "Undesirable congestion under natural disposability and desirable congestion under managerial disposability in U.S. electric power industry measured by DEA environmental assessment," Energy Economics, Elsevier, vol. 55(C), pages 173-188.
    16. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Environmental assessment for corporate sustainability by resource utilization and technology innovation: DEA radial measurement on Japanese industrial sectors," Energy Economics, Elsevier, vol. 46(C), pages 295-307.
    17. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: Comparison between Japanese electric power industry and manufacturing industries," Energy Economics, Elsevier, vol. 34(3), pages 686-699.
    18. Gharneh, Naser Shams & Nabavieh, Alireza & Gholamiangonabadi, Davoud & Alimoradi, Mohammad, 2014. "Productivity change and its determinants: Application of the Malmquist index with bootstrapping in Iranian steam power plants," Utilities Policy, Elsevier, vol. 31(C), pages 114-120.
    19. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Returns to Scale, Damages to Scale, Marginal Rate of Transformation and Rate of Substitution in DEA Environmental Assessment," Energy Economics, Elsevier, vol. 34(4), pages 905-917.
    20. Sueyoshi, Toshiyuki & Goto, Mika, 2013. "DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations," Energy Economics, Elsevier, vol. 40(C), pages 370-382.

    More about this item

    Keywords

    Electric power industry; DEA; DEA–DA;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:34:y:2012:i:3:p:634-644. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.