Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination
This paper reexamines the unintended consequences of the two widely cited models for measuring environmental efficiency—the hyperbolic efficiency model (HEM) and directional distance function (DDF). I prove the existence of three main problems: (1) these two models are not monotonic in undesirable o...
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sg-ntu-dr.10356-1041262023-05-19T06:44:41Z Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination Chen, Chien-Ming Nanyang Business School DRNTU::Business::Operations management This paper reexamines the unintended consequences of the two widely cited models for measuring environmental efficiency—the hyperbolic efficiency model (HEM) and directional distance function (DDF). I prove the existence of three main problems: (1) these two models are not monotonic in undesirable outputs (i.e., a firm’s efficiency may increase when polluting more, and vice versa), (2) strongly dominated firms may appear efficient, and (3) some firms’ environmental efficiency scores may be computed against strongly dominated points. Using the supply-chain carbon emissions data from the 50 major U.S. manufacturing companies, I empirically compare these two models with a weighted additive DEA model. The empirical results corroborate the analytical findings that the DDF and HEM models can generate spurious efficiency estimates and must be used with extreme caution. Accepted version 2014-05-26T01:51:09Z 2019-12-06T21:27:02Z 2014-05-26T01:51:09Z 2019-12-06T21:27:02Z 2013 2013 Journal Article Chen, C. M. (2014). Evaluating eco-efficiency with data envelopment analysis: an analytical reexamination. Annals of Operations Research, 214(1), 49-71. 0254-5330 https://hdl.handle.net/10356/104126 http://hdl.handle.net/10220/19441 10.1007/s10479-013-1488-z en Annals of operations research © 2013 Springer Science+Business Media New York. This is the author created version of a work that has been peer reviewed and accepted for publication by Annals of Operations Research, Springer Science+Business Media New York. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1007/s10479-013-1488-z]. application/pdf |
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DRNTU::Business::Operations management Chen, Chien-Ming Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination |
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This paper reexamines the unintended consequences of the two widely cited models for measuring environmental efficiency—the hyperbolic efficiency model (HEM) and directional distance function (DDF). I prove the existence of three main problems: (1) these two models are not monotonic in undesirable outputs (i.e., a firm’s efficiency may increase when polluting more, and vice versa), (2) strongly dominated firms may appear efficient, and (3) some firms’ environmental efficiency scores may be computed against strongly dominated points. Using the supply-chain carbon emissions data from the 50 major U.S. manufacturing companies, I empirically compare these two models with a weighted additive DEA model. The empirical results corroborate the analytical findings that the DDF and HEM models can generate spurious efficiency estimates and must be used with extreme caution. |
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Nanyang Business School |
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Nanyang Business School Chen, Chien-Ming |
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Chen, Chien-Ming |
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Chen, Chien-Ming |
title |
Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination |
title_short |
Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination |
title_full |
Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination |
title_fullStr |
Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination |
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Evaluating eco-efficiency with data envelopment analysis : an analytical reexamination |
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evaluating eco-efficiency with data envelopment analysis : an analytical reexamination |
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2014 |
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https://hdl.handle.net/10356/104126 http://hdl.handle.net/10220/19441 |
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1770565216582500352 |