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Semi-disposability of undesirable outputs in data envelopment analysis for environmental assessments

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  • Chen, Lei
  • Wang, Ying-Ming
  • Lai, Fujun

Abstract

The assumptions of strong and weak disposability for undesirable outputs have long dominated studies of data envelopment analysis for environmental assessments. Unfortunately, these assumptions cannot describe the diverse technical features of different undesirable outputs during the actual production process. Thus, we introduce a non-disposal degree to develop a new semi-disposability assumption, which can replace the assumptions of strong and weak disposability in environmental assessments. This assumption ensures that decision makers can address undesirable outputs freely within the scope of current production technology; otherwise, they have to reduce desirable outputs in the same proportion to decrease undesirable outputs. A reference point comparison method is proposed for determining the non-disposal degree from an objective perspective. The assumption of semi-disposability is extended to uncertain circumstances by using the interval non-disposal degree. Finally, two empirical examples are provided to illustrate the effectiveness of the semi-disposability assumption.

Suggested Citation

  • Chen, Lei & Wang, Ying-Ming & Lai, Fujun, 2017. "Semi-disposability of undesirable outputs in data envelopment analysis for environmental assessments," European Journal of Operational Research, Elsevier, vol. 260(2), pages 655-664.
  • Handle: RePEc:eee:ejores:v:260:y:2017:i:2:p:655-664
    DOI: 10.1016/j.ejor.2016.12.042
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    as
    1. Woo, Chungwon & Chung, Yanghon & Chun, Dongphil & Seo, Hangyeol & Hong, Sungjun, 2015. "The static and dynamic environmental efficiency of renewable energy: A Malmquist index analysis of OECD countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 367-376.
    2. Vlontzos, George & Niavis, Spyros & Manos, Basil, 2014. "A DEA approach for estimating the agricultural energy and environmental efficiency of EU countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 91-96.
    3. Chang, Young-Tae & Zhang, Ning & Danao, Denise & Zhang, Nan, 2013. "Environmental efficiency analysis of transportation system in China: A non-radial DEA approach," Energy Policy, Elsevier, vol. 58(C), pages 277-283.
    4. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    5. Chen, Po-Chi & Yu, Ming-Miin & Chang, Ching-Cheng & Hsu, Shih-Hsun & Managi, Shunsuke, 2015. "The enhanced Russell-based directional distance measure with undesirable outputs: Numerical example considering CO2 emissions," Omega, Elsevier, vol. 53(C), pages 30-40.
    6. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: Comparison between Japanese electric power industry and manufacturing industries," Energy Economics, Elsevier, vol. 34(3), pages 686-699.
    7. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    8. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    9. Korhonen, Pekka J. & Luptacik, Mikulas, 2004. "Eco-efficiency analysis of power plants: An extension of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 437-446, April.
    10. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "DEA radial measurement for environmental assessment and planning: Desirable procedures to evaluate fossil fuel power plants," Energy Policy, Elsevier, vol. 41(C), pages 422-432.
    11. Yang, Hongliang & Pollitt, Michael, 2010. "The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants," Energy Policy, Elsevier, vol. 38(8), pages 4440-4444, August.
    12. Boussemart, Jean Philippe & Leleu, Hervé & Shen, Zhiyang, 2015. "Environmental growth convergence among Chinese regions," China Economic Review, Elsevier, vol. 34(C), pages 1-18.
    13. Adler, Nicole & Volta, Nicola, 2016. "Accounting for externalities and disposability: A directional economic environmental distance function," European Journal of Operational Research, Elsevier, vol. 250(1), pages 314-327.
    14. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    15. Hang, Ye & Sun, Jiasen & Wang, Qunwei & Zhao, Zengyao & Wang, Yizhong, 2015. "Measuring energy inefficiency with undesirable outputs and technology heterogeneity in Chinese cities," Economic Modelling, Elsevier, vol. 49(C), pages 46-52.
    16. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.
    17. Rolf Färe & Shawna Grosskopf, 2003. "Nonparametric Productivity Analysis with Undesirable Outputs: Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1070-1074.
    18. Leleu, Hervé, 2013. "Shadow pricing of undesirable outputs in nonparametric analysis," European Journal of Operational Research, Elsevier, vol. 231(2), pages 474-480.
    19. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Environmental assessment for corporate sustainability by resource utilization and technology innovation: DEA radial measurement on Japanese industrial sectors," Energy Economics, Elsevier, vol. 46(C), pages 295-307.
    20. Barros, C.P. & Emrouznejad, Ali, 2016. "Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping: A case of Mozambican banksAuthor-Name: Wanke, Peter," European Journal of Operational Research, Elsevier, vol. 249(1), pages 378-389.
    21. Kuosmanen, Timo & Kazemi Matin, Reza, 2011. "Duality of weakly disposable technology," Omega, Elsevier, vol. 39(5), pages 504-512, October.
    22. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    23. Liu, Wenbin & Zhou, Zhongbao & Ma, Chaoqun & Liu, Debin & Shen, Wanfang, 2015. "Two-stage DEA models with undesirable input-intermediate-outputs," Omega, Elsevier, vol. 56(C), pages 74-87.
    24. Mariano, Enzo Barberio & Sobreiro, Vinicius Amorim & Rebelatto, Daisy Aparecida do Nascimento, 2015. "Human development and data envelopment analysis: A structured literature review," Omega, Elsevier, vol. 54(C), pages 33-49.
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