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A novel multilevel network slacks-based measure with an application in electric utility companies

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  • Mahmoudabadi, Mohammad Zarei
  • Azar, Adel
  • Emrouznejad, Ali

Abstract

In this paper, we developed an alternative Network Slacks-Based Data Envelopment Analysis Measure (NSBM) wherein the overall efficiency is expressed as a weighted average of the efficiencies of the individual processes. The advantage of this new model is that both overall efficiency and multi-divisional efficiencies have been calculated with a unified framework. The major merits of the proposed model are its ability to provide appropriate measure of efficiency, obtaining weight of processes from model, simultaneous assessment of intermediate variables considering them as both input and output. Finally, an application in electric power companies shows the practicality of the proposed model.

Suggested Citation

  • Mahmoudabadi, Mohammad Zarei & Azar, Adel & Emrouznejad, Ali, 2018. "A novel multilevel network slacks-based measure with an application in electric utility companies," Energy, Elsevier, vol. 158(C), pages 1120-1129.
    • Handle: RePEc:eee:energy:v:158:y:2018:i:c:p:1120-1129
    DOI: 10.1016/j.energy.2018.05.161
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    1. Amado, Carla A.F. & Santos, Sérgio P. & Marques, Pedro M., 2012. "Integrating the Data Envelopment Analysis and the Balanced Scorecard approaches for enhanced performance assessment," Omega, Elsevier, vol. 40(3), pages 390-403.
    2. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    3. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    4. 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.
    5. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    6. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    7. Bai, Xue-Jie & Yan, Wen-Kai & Chiu, Yung-Ho, 2015. "Performance evaluation of China's Hi-tech zones in the post financial crisis era — Analysis based on the dynamic network SBM model," China Economic Review, Elsevier, vol. 34(C), pages 122-134.
    8. Özkara, Yücel & Atak, Mehmet, 2015. "Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey," Energy, Elsevier, vol. 93(P1), pages 495-510.
    9. Wang, Ke & Huang, Wei & Wu, Jie & Liu, Ying-Nan, 2014. "Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA," Omega, Elsevier, vol. 44(C), pages 5-20.
    10. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Toloo, Mehdi & Ghazizadeh, Mohammad Sadegh, 2016. "Eco-efficiency considering the issue of heterogeneity among power plants," Energy, Elsevier, vol. 111(C), pages 722-735.
    11. Li, Ye & Wang, Yan-zhang & Cui, Qiang, 2015. "Evaluating airline efficiency: An application of Virtual Frontier Network SBM," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 1-17.
    12. Chen, Yao & Cook, Wade D. & Zhu, Joe, 2010. "Deriving the DEA frontier for two-stage processes," European Journal of Operational Research, Elsevier, vol. 202(1), pages 138-142, April.
    13. Chen, Yao & Cook, Wade D. & Li, Ning & Zhu, Joe, 2009. "Additive efficiency decomposition in two-stage DEA," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1170-1176, August.
    14. Lin, Boqiang & Wu, Ya & Zhang, Li, 2012. "Electricity saving potential of the power generation industry in China," Energy, Elsevier, vol. 40(1), pages 307-316.
    15. Despotis, Dimitris K. & Koronakos, Gregory & Sotiros, Dimitris, 2016. "The “weak-link” approach to network DEA for two-stage processes," European Journal of Operational Research, Elsevier, vol. 254(2), pages 481-492.
    16. Shermeh, H. Ebrahimzadeh & Najafi, S.E. & Alavidoost, M.H., 2016. "A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies," Energy, Elsevier, vol. 112(C), pages 686-697.
    17. Lin, Tzu-Yu & Chiu, Sheng-Hsiung, 2013. "Using independent component analysis and network DEA to improve bank performance evaluation," Economic Modelling, Elsevier, vol. 32(C), pages 608-616.
    18. Paradi, Joseph C. & Rouatt, Stephen & Zhu, Haiyan, 2011. "Two-stage evaluation of bank branch efficiency using data envelopment analysis," Omega, Elsevier, vol. 39(1), pages 99-109, January.
    19. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    20. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
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    Cited by:

    1. She, Zhen-Yu & Meng, Gang & Xie, Bai-Chen & O'Neill, Eoghan, 2020. "The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective," Applied Energy, Elsevier, vol. 264(C).
    2. Mahmoudabadi, Mohammad Zarei & Emrouznejad, Ali, 2019. "Comprehensive performance evaluation of banking branches: A three-stage slacks-based measure (SBM) data envelopment analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 359-376.
    3. 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).
    4. Yanhong Tang & Yingwen Chen & Rui Yang & Xin Miao, 2020. "The Unified Efficiency Evaluation of China’s Industrial Waste Gas Considering Pollution Prevention and End-Of-Pipe Treatment," IJERPH, MDPI, vol. 17(16), pages 1-27, August.
    5. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    6. Joohwan Kim & Hwayoung Kim, 2021. "Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    7. Xiao Shi & Ali Emrouznejad & Minyue Jin & Feng Yang, 2020. "A new parallel fuzzy data envelopment analysis model for parallel systems with two components based on Stackelberg game theory," Fuzzy Optimization and Decision Making, Springer, vol. 19(3), pages 311-332, September.

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