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A new network data envelopment analysis models to measure the efficiency of natural gas supply chain

Author

Listed:
  • Sarah J.-Sharahi

    (Islamic Azad University)

  • Kaveh Khalili-Damghani

    (Islamic Azad University)

  • Amir-Reza Abtahi

    (Kharazmi University)

  • Alireza Rashidi Komijan

    (Islamic Azad University)

Abstract

Natural-gas supply chain network (NGSCN) includes production, transmission, and distribution stages, numerous types of exogenous and undesirable inputs, intermediate products, and outputs. These lead to a complicated structure for NGSCN. Measurement of efficiency of NGSCN is essential and important. In this paper, network data envelopment analysis model is developed to measure the efficiency of the natural-gas supply chain in Iran. The main properties of the proposed model, i.e., feasibility and bound of the objective function, are discussed through several theorems. The proposed model is used to measure the efficiency of a gas supply chain and the associated efficiency of all elements in the chain during a 5-year planning horizon incorporating real monthly operational data. The results illustrate the total efficiency score of the NGSCN and the efficiency and inefficiency of the production, transmission, and distribution stages. The proposed model of this study can be customized and applied in other energy supply chains such as water, oil, electricity, and wind.

Suggested Citation

  • Sarah J.-Sharahi & Kaveh Khalili-Damghani & Amir-Reza Abtahi & Alireza Rashidi Komijan, 2021. "A new network data envelopment analysis models to measure the efficiency of natural gas supply chain," Operational Research, Springer, vol. 21(3), pages 1461-1486, September.
  • Handle: RePEc:spr:operea:v:21:y:2021:i:3:d:10.1007_s12351-019-00474-4
    DOI: 10.1007/s12351-019-00474-4
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    References listed on IDEAS

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    1. Iftikhar, Yaser & Wang, Zhaohua & Zhang, Bin & Wang, Bo, 2018. "Energy and CO2 emissions efficiency of major economies: A network DEA approach," Energy, Elsevier, vol. 147(C), pages 197-207.
    2. 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.
    3. Kao, Chiang & Lin, Pei-Huang, 2011. "Qualitative factors in data envelopment analysis: A fuzzy number approach," European Journal of Operational Research, Elsevier, vol. 211(3), pages 586-593, June.
    4. 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.
    5. Kaveh Khalili-Damghani & Mohammad Taghavifard, 2012. "A three-stage fuzzy DEA approach to measure performance of a serial process including JIT practices, agility indices, and goals in supply chains," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 13(2), pages 147-188.
    6. Boaz Golany & Steven Hackman & Ury Passy, 2006. "An efficiency measurement framework for multi-stage production systems," Annals of Operations Research, Springer, vol. 145(1), pages 51-68, July.
    7. Kaveh Khalili-Damghani & Behnam Taghavifard, 2013. "Sensitivity and stability analysis in two-stage DEA models with fuzzy data," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 17(1), pages 1-37.
    8. Liang Liang & Zhao-Qiong Li & Wade Cook & Joe Zhu, 2011. "Data envelopment analysis efficiency in two-stage networks with feedback," IISE Transactions, Taylor & Francis Journals, vol. 43(5), pages 309-322.
    9. Cook, Wade D. & Zhu, Joe & Bi, Gongbing & Yang, Feng, 2010. "Network DEA: Additive efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1122-1129, December.
    10. Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
    11. Chiu, Yung-ho & Huang, Chin-wei & Ma, Chun-Mei, 2011. "Assessment of China transit and economic efficiencies in a modified value-chains DEA model," European Journal of Operational Research, Elsevier, vol. 209(2), pages 95-103, March.
    12. 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.
    13. Liu, Shiang-Tai, 2011. "A note on efficiency decomposition in two-stage data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 212(3), pages 606-608, August.
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