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A bootstrapped robust data envelopment analysis model for efficiency estimating of telecommunication companies in Iran

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  • Sadjadi, S.J.
  • Omrani, H.

Abstract

One of the primary concerns in measuring the relative efficiency of a telecommunication unit compared with other similar units is the uncertainty on input/output data. In this paper, a bootstrapped robust data envelopment analysis (BRDEA) model is proposed to measure the efficiency of telecommunication companies. The proposed method is capable of handling different issues such as the uncertainty in data or sampling errors. The model is examined using some real data from a telecommunication company. First, the data from 24 telecommunication companies are assumed with uncertainty and the efficiency of telecommunication companies are estimated using a robust DEA model. Then, the results of the efficiencies are corrected by a bootstrapping technique. The results indicate that the BRDEA method considers the perturbation in data and sampling error with an adaptation of bootstrapped robust data envelopment analysis and could be more reliable for efficiency estimating strategies.

Suggested Citation

  • Sadjadi, S.J. & Omrani, H., 2010. "A bootstrapped robust data envelopment analysis model for efficiency estimating of telecommunication companies in Iran," Telecommunications Policy, Elsevier, vol. 34(4), pages 221-232, May.
    • Handle: RePEc:eee:telpol:v:34:y:2010:i:4:p:221-232
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    Citations

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    Cited by:

    1. Wang, Wei-Kang & Lu, Wen-Min & Kweh, Qian Long & Lai, Hsiao-Wen, 2014. "Does corporate social responsibility influence the corporate performance of the U.S. telecommunications industry?," Telecommunications Policy, Elsevier, vol. 38(7), pages 580-591.
    2. Moreno, Plácido & Lozano, Sebastián & Gutiérrez, Ester, 2013. "Dynamic performance analysis of U.S. wireline telecommunication companies," Telecommunications Policy, Elsevier, vol. 37(6), pages 469-482.
    3. Toloo, Mehdi & Mensah, Emmanuel Kwasi & Salahi, Maziar, 2022. "Robust optimization and its duality in data envelopment analysis," Omega, Elsevier, vol. 108(C).
    4. Pejman Peykani & Jafar Gheidar-Kheljani & Reza Farzipoor Saen & Emran Mohammadi, 2022. "Generalized robust window data envelopment analysis approach for dynamic performance measurement under uncertain panel data," Operational Research, Springer, vol. 22(5), pages 5529-5567, November.
    5. Hatami-Marbini, Adel & Arabmaldar, Aliasghar, 2021. "Robustness of Farrell cost efficiency measurement under data perturbations: Evidence from a US manufacturing application," European Journal of Operational Research, Elsevier, vol. 295(2), pages 604-620.
    6. Bruno, Clementina & Manello, Alessandro, 2015. "Benchmarking and effects of reforms in the fixed telecommunications industry: A DDF approach," Telecommunications Policy, Elsevier, vol. 39(2), pages 127-139.
    7. Kang, Chao-Chung & Wu, Chin-Chia, 2013. "Statistical precision of productivity change: A bootstrap application to Taiwan’s telecommunications industry," Telecommunications Policy, Elsevier, vol. 37(11), pages 1015-1032.
    8. Shabani, Amir & Visani, Franco & Barbieri, Paolo & Dullaert, Wout & Vigo, Daniele, 2019. "Reliable estimation of suppliers’ total cost of ownership: An imprecise data envelopment analysis model with common weights," Omega, Elsevier, vol. 87(C), pages 57-70.

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