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Equivalent solutions to additive two-stage network data envelopment analysis

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  • Zhang, Linyan
  • Chen, Yao

Abstract

In the additive approach of two-stage network data envelopment analysis (DEA), the non-linear DEA model is transformed into a parametric linear model and then solved by computing a series of linear programs. Lim and Zhu (2013; Integrated data envelopment analysis: Global vs. local optimum.European Journal of Operational Research, 229(1), 276–278) and Ang and Chen (2016; Pitfalls of decomposition weights in the additive multi-stage DEA model. Omega, 58, 139–153) propose two parametric linear approaches to solve additive two-stage network DEA model. The current study shows that the two approaches are equivalent and use the same parameter in searching for the global optimal solution.

Suggested Citation

  • Zhang, Linyan & Chen, Yao, 2018. "Equivalent solutions to additive two-stage network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1189-1191.
    • Handle: RePEc:eee:ejores:v:264:y:2018:i:3:p:1189-1191
    DOI: 10.1016/j.ejor.2017.07.042
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    References listed on IDEAS

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    1. Guo, Chuanyin & Abbasi Shureshjani, Roohollah & Foroughi, Ali Asghar & Zhu, Joe, 2017. "Decomposition weights and overall efficiency in two-stage additive network DEA," European Journal of Operational Research, Elsevier, vol. 257(3), pages 896-906.
    2. 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.
    3. 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.
    4. Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
    5. Li, Yongjun & Chen, Yao & Liang, Liang & Xie, Jianhui, 2012. "DEA models for extended two-stage network structures," Omega, Elsevier, vol. 40(5), pages 611-618.
    6. Ang, Sheng & Chen, Chien-Ming, 2016. "Pitfalls of decomposition weights in the additive multi-stage DEA model," Omega, Elsevier, vol. 58(C), pages 139-153.
    7. Lim, Sungmook & Zhu, Joe, 2013. "Integrated data envelopment analysis: Global vs. local optimum," European Journal of Operational Research, Elsevier, vol. 229(1), pages 276-278.
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    Cited by:

    1. Jianhui Xie & Qiwei Xie & Yongjun Li & Liang Liang, 2021. "Solving data envelopment analysis models with sum-of-fractional objectives: a global optimal approach based on the multiparametric disaggregation technique," Annals of Operations Research, Springer, vol. 304(1), pages 453-480, September.
    2. Qingxian An & Fanyong Meng & Beibei Xiong & Zongrun Wang & Xiaohong Chen, 2020. "Assessing the relative efficiency of Chinese high-tech industries: a dynamic network data envelopment analysis approach," Annals of Operations Research, Springer, vol. 290(1), pages 707-729, July.
    3. Khoveyni, Mohammad & Fukuyama, Hirofumi & Eslami, Robabeh & Yang, Guo-liang, 2019. "Variations effect of intermediate products on the second stage in two-stage processes," Omega, Elsevier, vol. 85(C), pages 35-48.
    4. Mohammad Izadikhah & Reza Farzipoor Saen, 2023. "Developing a linear stochastic two-stage data envelopment analysis model for evaluating sustainability of supply chains: a case study in welding industry," Annals of Operations Research, Springer, vol. 322(1), pages 195-215, March.

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