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Mathematical and Computer Modelling
Article
License: Elsevier Non-Commercial
Data sources: UnpayWall
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Mathematical and Computer Modelling
Article . 2013 . Peer-reviewed
License: Elsevier Non-Commercial
Data sources: Crossref
DBLP
Article . 2013
Data sources: DBLP
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A stochastic DEA model considering undesirable outputs with weak disposability

Authors: Chong Wu 0001; Yongli Li 0002; Qian Liu; Kunsheng Wang;

A stochastic DEA model considering undesirable outputs with weak disposability

Abstract

Abstract This paper proposes a stochastic DEA model considering undesirable outputs with weak disposability which not only can deal with the existence of random errors in the collected data, but also depicts the production rules uncovered by weak disposability of the undesirable outputs. This model introduces the concept of risk to define the efficiency of decision making units (DMUs), and utilizes the correlationship matrix of all the variables to portray the weak disposability. On the basis of probability distribution properties, the probabilistic form of the model is transformed to the equivalent deterministic one which is able to be solved. In the application of the model, the environment efficiency evaluation problem is chosen to validate the model by designing different levels of random errors and comparing the new model with the old one. In conclusion, the model, with broad applicability has a more superior analysis capacity than the existing model.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
43
Top 10%
Top 10%
Top 10%
hybrid