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A second-order cone programming based robust data envelopment analysis model for the new-energy vehicle industry

Author

Listed:
  • Chao Lu

    (Shanghai University)

  • Jie Tao

    (University of Shanghai for Science and Technology)

  • Qiuxian An

    (North China Electric Power University)

  • Xiaodong Lai

    (South China Normal University)

Abstract

The validity of performance evaluation is determined by, and therefore greatly influenced by, the accuracy of data set. To address such imprecise and negative data problems widely spread in the real world, this paper proposes a second-order cone based robust data envelopment analysis (SOCPR-DEA) model, which is more robust to data variety. Further, this new computational tractable model is applied to analyze 13 new-energy vehicle (NEV) manufacturers from China. The findings support that the SOCPR-DEA model could well mitigate the deficiency caused by data variety, and the evidence from Chinese NEV industry shows that a focus strategy is more likely to enhance a firm’s efficiency especially at its emerging stage, and the efficiency is more sensitive with production cost than other factors such as research and development, sales income, earnings per share, and predicted income. In addition, this paper also gives some industrial implications and policy suggestions based on these interesting findings.

Suggested Citation

  • Chao Lu & Jie Tao & Qiuxian An & Xiaodong Lai, 2020. "A second-order cone programming based robust data envelopment analysis model for the new-energy vehicle industry," Annals of Operations Research, Springer, vol. 292(1), pages 321-339, September.
    • Handle: RePEc:spr:annopr:v:292:y:2020:i:1:d:10.1007_s10479-019-03155-9
    DOI: 10.1007/s10479-019-03155-9
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    Cited by:

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    2. Zhang, Tinglong & Li, Sasa & Li, Yifan & Wang, Weizhong, 2023. "Evaluation of technology innovation efficiency for the listed NEV enterprises in China," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1445-1458.
    3. Emmanuel Kwasi Mensah, 2020. "Robust data envelopment analysis via ellipsoidal uncertainty sets with application to the Italian banking industry," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(2), pages 491-518, December.
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    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. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2022. "Innovation efficiency and technology heterogeneity within China's new energy vehicle industry: A two-stage NSBM approach embedded in a three-hierarchy meta-frontier framework," Energy Policy, Elsevier, vol. 161(C).

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