IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v174y2019icp985-998.html
   My bibliography  Save this article

A novel network data envelopment analysis model for performance measurement of Turkish electric distribution companies

Author

Listed:
  • Petridis, Konstantinos
  • Ünsal, Mehmet Güray
  • Dey, Prasanta Kumar
  • Örkcü, H. Hasan

Abstract

Electric distribution companies have a significant role for both households and industries. Benchmarking of the electric distribution companies in the energy sector has become a subject that is studied widely nowadays due to the effect of privatization policies for developing countries. Since there are multiple production stages regarding the generation and supply procedures of electric power, Network DEA technique is used. Directional Distance Function is also integrated into Network DEA technique. Electric distribution companies are organizations that are aiming at maximizing profit while minimizing the expenses. The main problem is how the profit idea can be integrated into the evaluation process. The aim of the proposed model is to evaluate profit efficiency of electric distribution companies while taking into account expansion cost for additional energy supply. This two stage approach is applied to Turkish electric distribution companies. Results are presented based on radial and profit efficiency measures. The proposed model is demonstrates realistic results by considering the expenses and incomes of distribution companies.

Suggested Citation

  • Petridis, Konstantinos & Ünsal, Mehmet Güray & Dey, Prasanta Kumar & Örkcü, H. Hasan, 2019. "A novel network data envelopment analysis model for performance measurement of Turkish electric distribution companies," Energy, Elsevier, vol. 174(C), pages 985-998.
    • Handle: RePEc:eee:energy:v:174:y:2019:i:c:p:985-998
    DOI: 10.1016/j.energy.2019.01.051
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219300532
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.01.051?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. Hess, Borge & Cullmann, Astrid, 2007. "Efficiency analysis of East and West German electricity distribution companies - Do the "Ossis" really beat the "Wessis"?," Utilities Policy, Elsevier, vol. 15(3), pages 206-214, September.
    2. Edvardsen, Dag Fjeld & Forsund, Finn R., 2003. "International benchmarking of electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 25(4), pages 353-371, October.
    3. Bagdadioglu, Necmiddin & Waddams Price, Catherine M. & Weyman-Jones, Thomas G., 1996. "Efficiency and ownership in electricity distribution: A non-parametric model of the Turkish experience," Energy Economics, Elsevier, vol. 18(1-2), pages 1-23, April.
    4. Yadav, Vinod Kumar & Padhy, N.P. & Gupta, H.O., 2011. "Performance evaluation and improvement directions for an Indian electric utility," Energy Policy, Elsevier, vol. 39(11), pages 7112-7120.
    5. Abbott, Malcolm, 2006. "The productivity and efficiency of the Australian electricity supply industry," Energy Economics, Elsevier, vol. 28(4), pages 444-454, July.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Filippini, Massimo & Wetzel, Heike, 2014. "The impact of ownership unbundling on cost efficiency: Empirical evidence from the New Zealand electricity distribution sector," Energy Economics, Elsevier, vol. 45(C), pages 412-418.
    8. Astrid Cullmann & Christian Hirschhausen, 2008. "Efficiency analysis of East European electricity distribution in transition: legacy of the past?," Journal of Productivity Analysis, Springer, vol. 29(2), pages 155-167, April.
    9. Yun Zhang & Robert Bartels, 1998. "The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand," Journal of Productivity Analysis, Springer, vol. 9(3), pages 187-204, March.
    10. Sueyoshi, Toshiyuki & Goto, Mika, 2011. "DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation," Energy Economics, Elsevier, vol. 33(2), pages 292-303, March.
    11. Mirza, Faisal Mehmood & Mushtaq, Iqra & Ullah, Kafait, 2017. "Assessing the efficiency dynamics of post reforms electric distribution utilities in Pakistan," Utilities Policy, Elsevier, vol. 47(C), pages 18-28.
    12. Deng, Na-Qian & Liu, Li-Qiu & Deng, Ying-Zhi, 2018. "Estimating the effects of restructuring on the technical and service-quality efficiency of electricity companies in China," Utilities Policy, Elsevier, vol. 50(C), pages 91-100.
    13. Ghasemi, Mostafa & Dashti, Reza, 2017. "A risk-based model for performance-based regulation of electric distribution companies," Utilities Policy, Elsevier, vol. 45(C), pages 36-44.
    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. Necmiddin Bagdadioglu & Alparslan Basaran & Catherine Waddams Price, 2007. "Potential Impact of Electricity Reforms on Turkish Households," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2007-08, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    16. Yunos, Jamaluddin Mohd & Hawdon, David, 1997. "The efficiency of the National Electricity Board in Malaysia: An intercountry comparison using DEA," Energy Economics, Elsevier, vol. 19(2), pages 255-269, May.
    17. Giannakis, Dimitrios & Jamasb, Tooraj & Pollitt, Michael, 2005. "Benchmarking and incentive regulation of quality of service: an application to the UK electricity distribution networks," Energy Policy, Elsevier, vol. 33(17), pages 2256-2271, November.
    18. Goto, Mika & Tsutsui, Miki, 1998. "Comparison of Productive and Cost Efficiencies Among Japanese and US Electric Utilities," Omega, Elsevier, vol. 26(2), pages 177-194, April.
    19. Arcos-Vargas, A. & Núñez-Hernández, F. & Villa-Caro, Gabriel, 2017. "A DEA analysis of electricity distribution in Spain: An industrial policy recommendation," Energy Policy, Elsevier, vol. 102(C), pages 583-592.
    20. 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.
    21. H. Örkcü & Mehmet Ünsal & Hasan Bal, 2015. "A modification of a mixed integer linear programming (MILP) model to avoid the computational complexity," Annals of Operations Research, Springer, vol. 235(1), pages 599-623, December.
    22. Gouveia, M.C. & Dias, L.C. & Antunes, C.H. & Boucinha, J. & Inácio, C.F., 2015. "Benchmarking of maintenance and outage repair in an electricity distribution company using the value-based DEA method," Omega, Elsevier, vol. 53(C), pages 104-114.
    23. Welch, Eric & Barnum, Darold, 2009. "Joint environmental and cost efficiency analysis of electricity generation," Ecological Economics, Elsevier, vol. 68(8-9), pages 2336-2343, June.
    24. Sartori, Simone & Witjes, Sjors & Campos, Lucila M.S., 2017. "Sustainability performance for Brazilian electricity power industry: An assessment integrating social, economic and environmental issues," Energy Policy, Elsevier, vol. 111(C), pages 41-51.
    25. Førsund, Finn R. & Kittelsen, Sverre A. C., 1998. "Productivity development of Norwegian electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 20(3), pages 207-224, September.
    26. Jamasb, Tooraj & Pollitt, Michael, 2003. "International benchmarking and regulation: an application to European electricity distribution utilities," Energy Policy, Elsevier, vol. 31(15), pages 1609-1622, December.
    27. Pekka Korhonen & Mikko Syrjänen, 2003. "Evaluation of Cost Efficiency in Finnish Electricity Distribution," Annals of Operations Research, Springer, vol. 121(1), pages 105-122, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuan, Peng & Pu, Yuran & Liu, Chang, 2021. "Improving electricity supply reliability in China: Cost and incentive regulation," Energy, Elsevier, vol. 237(C).
    2. Ikram, Majid & Rafique, Muhammad Zahid & Mohammed, Kamel Si & Waheed, Rida & Ferraz, Diogo, 2023. "Efficient resource utilization of the electricity distribution sector using nonparametric data envelopment analysis and influential factors," Utilities Policy, Elsevier, vol. 82(C).
    3. Patyal, Vishal Singh & Kumar, Ravi & Lamba, Kuldeep & Maheshwari, Sunil, 2023. "Performance evaluation of Indian electricity distribution companies: An integrated DEA-IRP-TOPSIS approach," Energy Economics, Elsevier, vol. 124(C).
    4. Vecihi Yiğit & Nazlı Nisa Demir & Hisham Alidrisi & Mehmet Emin Aydin, 2020. "Elicitation of the Factors Affecting Electricity Distribution Efficiency Using the Fuzzy AHP Method," Mathematics, MDPI, vol. 9(1), pages 1-25, December.
    5. Meng, Ming & Pang, Tingting, 2022. "Operational efficiency analysis of China's electric power industry using a dynamic network slack-based measure model," Energy, Elsevier, vol. 251(C).
    6. Gautier, Axel & Nsabimana, René & Walheer, Barnabé, 2023. "Quality performance gaps and minimal electricity losses in East Africa," Utilities Policy, Elsevier, vol. 82(C).
    7. Ogunrinde, Olawale & Shittu, Ekundayo, 2023. "Efficiency and productivity of renewable energy technologies: Evidence from U.S. investor-owned utilities across regional markets," Utilities Policy, Elsevier, vol. 82(C).
    8. Konstantinos Petridis, 2022. "Spatio-temporal efficiency measurement under undesirable outputs using multi-objective programming: a GAMS representation," Annals of Operations Research, Springer, vol. 311(2), pages 1183-1202, April.

    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. H. Örkcü & Mehmet Ünsal & Hasan Bal, 2015. "A modification of a mixed integer linear programming (MILP) model to avoid the computational complexity," Annals of Operations Research, Springer, vol. 235(1), pages 599-623, December.
    2. 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.
    3. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    4. S P Santos & C A F Amado & J R Rosado, 2011. "Formative evaluation of electricity distribution utilities using data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1298-1319, July.
    5. Jinchao Li & Jinying Li & Fengting Zheng, 2014. "Unified Efficiency Measurement of Electric Power Supply Companies in China," Sustainability, MDPI, vol. 6(2), pages 1-15, February.
    6. Patyal, Vishal Singh & Kumar, Ravi & Lamba, Kuldeep & Maheshwari, Sunil, 2023. "Performance evaluation of Indian electricity distribution companies: An integrated DEA-IRP-TOPSIS approach," Energy Economics, Elsevier, vol. 124(C).
    7. San Cristóbal, José Ramón, 2011. "A multi criteria data envelopment analysis model to evaluate the efficiency of the Renewable Energy technologies," Renewable Energy, Elsevier, vol. 36(10), pages 2742-2746.
    8. Lee, Boon L. & Wilson, Clevo & Simshauser, Paul & Majiwa, Eucabeth, 2021. "Deregulation, efficiency and policy determination: An analysis of Australia's electricity distribution sector," Energy Economics, Elsevier, vol. 98(C).
    9. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
    10. Gautier, Axel & Nsabimana, René & Walheer, Barnabé, 2023. "Quality performance gaps and minimal electricity losses in East Africa," Utilities Policy, Elsevier, vol. 82(C).
    11. Sadjadi, S.J. & Omrani, H., 2008. "Data envelopment analysis with uncertain data: An application for Iranian electricity distribution companies," Energy Policy, Elsevier, vol. 36(11), pages 4247-4254, November.
    12. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    13. Jamasb, T. & Pollitt, M., 2000. "Benchmarking and regulation: international electricity experience," Utilities Policy, Elsevier, vol. 9(3), pages 107-130, September.
    14. Núñez, F. & Arcos-Vargas, A. & Villa, G., 2020. "Efficiency benchmarking and remuneration of Spanish electricity distribution companies," Utilities Policy, Elsevier, vol. 67(C).
    15. Mota, R.L., 2004. "‘Comparing Brazil and USA electricity performance; what was the impact of privatisation?’," Cambridge Working Papers in Economics 0423, Faculty of Economics, University of Cambridge.
    16. Walheer, Barnabé, 2019. "Malmquist productivity index for multi-output producers: An application to electricity generation plants," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 76-88.
    17. Azadeh, A. & Ghaderi, S.F. & Omrani, H. & Eivazy, H., 2009. "An integrated DEA-COLS-SFA algorithm for optimization and policy making of electricity distribution units," Energy Policy, Elsevier, vol. 37(7), pages 2605-2618, July.
    18. Zakaria, Muhammad & Noureen, Rabia, 2016. "Benchmarking and regulation of power distribution companies in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1095-1099.
    19. Bai-Chen, Xie & Ying, Fan & Qian-Qian, Qu, 2012. "Does generation form influence environmental efficiency performance? An analysis of China’s power system," Applied Energy, Elsevier, vol. 96(C), pages 261-271.
    20. Nakano, Makiko & Managi, Shunsuke, 2008. "Regulatory reforms and productivity: An empirical analysis of the Japanese electricity industry," Energy Policy, Elsevier, vol. 36(1), pages 201-209, January.

    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:energy:v:174:y:2019:i:c:p:985-998. 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.journals.elsevier.com/energy .

    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.