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Technical and environmental efficiency of a two-stage production and abatement system

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  • Sebastián Lozano

    (University of Seville)

Abstract

In this paper, a network data envelopment analysis system that considers a production stage followed by an abatement stage is studied. Two DEA models are proposed for assessing, respectively, the technical and the environmental efficiency of the system. The technical efficiency model computes a network slacks-based inefficiency measure. In the case of the environmental efficiency model the reduction in the pollutants emissions can be weighted according to their environmental impact or to their allowance costs, thus allowing inputs as well as pollutants substitution. An allocative efficiency score can also be computed comparing the technical efficient projection with that of the environmental efficiency model. A key feature of the proposed approach is that it assumes that any inputs, outputs or intermediate products that contain the pollutants of interest are not freely disposable. Assuming otherwise would violate the materials balance principle. The proposed approach has been applied to a dataset involving 23 coal-fired power plants and a single pollutant. The results show that the technical efficiency model estimates maximum input reductions and output increases, which brings about significant emissions reductions. Those reductions are, however, smaller than those than can be achieved when environmental efficiency is the goal.

Suggested Citation

  • Sebastián Lozano, 2017. "Technical and environmental efficiency of a two-stage production and abatement system," Annals of Operations Research, Springer, vol. 255(1), pages 199-219, August.
    • Handle: RePEc:spr:annopr:v:255:y:2017:i:1:d:10.1007_s10479-015-1933-2
    DOI: 10.1007/s10479-015-1933-2
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    2. Amirteimoori, Alireza & Kazemi Matin, Reza & Yadollahi, Amir Hossein, 2024. "Stochastic resource reallocation in two-stage production processes with undesirable outputs: An empirical study on the power industry," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    3. Fan, Qiufang & Liu, Jintao & Zhang, Tao & Liu, Haomin, 2022. "An Evaluation of the Efficiency of China’s green investment in the “Belt and Road” countries," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 496-511.
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    5. Ming-Miin Yu & Li-Hsueh Chen, 2020. "A meta-frontier network data envelopment analysis approach for the measurement of technological bias with network production structure," Annals of Operations Research, Springer, vol. 287(1), pages 495-514, April.
    6. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    7. Alireza Moradi & Saber Saati & Mehrzad Navabakhsh, 2023. "Genetic algorithms for optimizing two-stage DEA by considering unequal intermediate weights," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1202-1217, September.
    8. Lívia Torres & Francisco S. Ramos, 2024. "Allocating Benefits Due to Shared Resources Using Shapley Value and Nucleolus in Dynamic Network Data Envelopment Analysis," Mathematics, MDPI, vol. 12(5), pages 1-23, February.
    9. Bei Gao & Zuoren Sun, 2023. "Marginal CO 2 and SO 2 Abatement Costs and Determinants of Coal-Fired Power Plants in China: Considering a Two-Stage Production System with Different Emission Reduction Approaches," Energies, MDPI, vol. 16(8), pages 1-26, April.
    10. Xiang Ji & Jie Wu & Qingyuan Zhu & Jiasen Sun, 2019. "Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study," Annals of Operations Research, Springer, vol. 278(1), pages 281-335, July.
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