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A new approach in modelling undesirable output in DEA model☆

Author

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  • S You

    (The Hong Kong Polytechnic University, Hung Hom, Hong Kong)

  • H Yan

    (The Hong Kong Polytechnic University, Hung Hom, Hong Kong)

Abstract

With an increasing attention on the environment, one of the major research thrusts in Data Envelopment Analysis (DEA) based performance evaluation is the undesirable output in the conventional DEA model. There is considerable research published on the undesirable aspects of production outputs. However, the economic implications and the suitability of the DEA models for incorporating the undesirable outputs are less carefully investigated and discussed. In this paper, a comparative study is conducted of typical eco-DEA models to illustrate this issue. We propose a ratio model to evaluate the undesirable as well as the desirable outputs simultaneously. We apply the specially developed model to investigate the impact of production pollutants while conducting the efficiency evaluation in the textile industry of China. The results reveal that the production output-oriented efficiency evaluation can be significantly altered once the environmental aspects are factored into the model.

Suggested Citation

  • S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model☆," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:12:p:2146-2156
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    Citations

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    Cited by:

    1. Jun Xu & Yuchen Jiang & Xin Guo & Li Jiang, 2021. "Environmental Efficiency Assessment of Heavy Pollution Industry by Data Envelopment Analysis and Malmquist Index Analysis: Empirical Evidence from China," IJERPH, MDPI, vol. 18(11), pages 1-17, May.
    2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    3. Zhao, Jiqiang & Wu, Xianhua & Guo, Ji & Gao, Chao, 2022. "Allocation of SO2 emission rights in city agglomerations considering cross-border transmission of pollutants: A new network DEA model," Applied Energy, Elsevier, vol. 325(C).
    4. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.
    5. Ngobeni, Victor & Breitenbach, Marthinus C, 2021. "Production and Scale Efficiency of South African Water Utilities: The Case of Water Boards," MPRA Paper 106242, University Library of Munich, Germany.
    6. José Manuel Cordero & Carlos Díaz Caro & Francisco Pedraja Chaparro & Cristina Polo Fernández, 2020. "Tributos cedidos y eficiencia en la gestión tributaria de las Comunidades Autónomas," Hacienda Pública Española / Review of Public Economics, IEF, vol. 232(1), pages 75-112, March.
    7. César Salazar & Roberto Cárdenas-Retamal & Marcela Jaime, 2023. "Environmental efficiency in the salmon industry—an exploratory analysis around the 2007 ISA virus outbreak and subsequent regulations in Chile," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8107-8135, August.
    8. Kao, Chiang & Hwang, Shiuh-Nan, 2021. "Measuring the effects of undesirable outputs on the efficiency of production units," European Journal of Operational Research, Elsevier, vol. 292(3), pages 996-1003.
    9. Ma-Lin Song & Ron Fisher & Jian-Lin Wang & Lian-Biao Cui, 2018. "Environmental performance evaluation with big data: theories and methods," Annals of Operations Research, Springer, vol. 270(1), pages 459-472, November.
    10. Natalia Borisovna Lubsanova & Lyudmila Bato-Zhargalovna Maksanova & Zinaida Sergeevna Eremko & Taisiya Borisovna Bardakhanova & Anna Semenovna Mikheeva, 2022. "The Eco-Efficiency of Russian Regions in North Asia: Their Green Direction of Regional Development," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    11. Cordero, José Manuel & Alonso-Morán, Edurne & Nuño-Solinis, Roberto & Orueta, Juan F. & Arce, Regina Sauto, 2015. "Efficiency assessment of primary care providers: A conditional nonparametric approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 235-244.
    12. Song, Malin & Song, Yaqing & An, Qingxian & Yu, Huayin, 2013. "Review of environmental efficiency and its influencing factors in China: 1998–2009," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 8-14.
    13. Sheng, Pengfei & Li, Jun & Zhai, Mengxin & Huang, Shoujun, 2020. "Coupling of economic growth and reduction in carbon emissions at the efficiency level: Evidence from China," Energy, Elsevier, vol. 213(C).
    14. Leonidas Sotirios Kyrgiakos & George Vlontzos & Panos M. Pardalos, 2021. "Ranking EU Agricultural Sectors under the Prism of Alternative Widths on Window DEA," Energies, MDPI, vol. 14(4), pages 1-26, February.
    15. Ma-Lin Song & Yuan-Xiang Zhou & Rong-Rong Zhang & Ron Fisher, 2017. "Environmental efficiency evaluation with left–right fuzzy numbers," Operational Research, Springer, vol. 17(3), pages 697-714, October.
    16. Jomthanachai, Suriyan & Wong, Wai-Peng & Soh, Keng-Lin & Lim, Chee-Peng, 2022. "A global trade supply chain vulnerability in COVID-19 pandemic: An assessment metric of risk and resilience-based efficiency of CoDEA method," Research in Transportation Economics, Elsevier, vol. 93(C).
    17. Khoshroo, Alireza & Izadikhah, Mohammad & Emrouznejad, Ali, 2022. "Total factor energy productivity considering undesirable pollutant outputs: A new double frontier based malmquist productivity index," Energy, Elsevier, vol. 258(C).
    18. Afzalinejad, Mohammad, 2020. "Reverse efficiency measures for environmental assessment in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    19. Breitenbach, Marthinus C & Ngobeni, Victor & Aye, Goodness C, 2020. "Global Healthcare Resource Efficiency in the Management of COVID-19 Death and Infection Prevalence Rates," MPRA Paper 104814, University Library of Munich, Germany.

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