An Interval Efficiency Measurement in DEA When considering Undesirable Outputs
Joint Authors
Mo, Renbian
Huang, Hongyun
Yang, Liyang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-16
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Data envelopment analysis (DEA) is a popular mathematical tool for analyzing the relative efficiency of homogenous decision-making units (DMUs).
However, the existing DEA models cannot tackle the newly confronted applications with imprecise and negative data as well as undesirable outputs simultaneously.
Thus, we introduce undesirable outputs into modified slack-based measure (MSBM) model and propose an interval-modified slack-based measure (IMSBM) model, which extends the application of interval DEA (IDEA) in fields that concern with less undesirable outputs.
The novelties of the model are that it considers the undesirable outputs while dealing with imprecise and negative data, and it is slack-based.
Furthermore, the model with undesirable outputs is proven translation-invariant and unit-invariant.
Moreover, a numerical example is provided to illustrate the changes of the lower and upper bounds of the efficiency score after considering the undesirable outputs.
The empirical results show that, without considering undesirable outputs, most of the lower bounds of the efficiency scores will be overestimated when the DMUs are weakly efficient and inefficient.
The upper bound will also change after considering undesirable outputs when the DMU is inefficient.
Finally, an improved degree of preference approach is introduced to rank the DMUs.
American Psychological Association (APA)
Mo, Renbian& Huang, Hongyun& Yang, Liyang. 2020. An Interval Efficiency Measurement in DEA When considering Undesirable Outputs. Complexity،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1143609
Modern Language Association (MLA)
Mo, Renbian…[et al.]. An Interval Efficiency Measurement in DEA When considering Undesirable Outputs. Complexity No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1143609
American Medical Association (AMA)
Mo, Renbian& Huang, Hongyun& Yang, Liyang. An Interval Efficiency Measurement in DEA When considering Undesirable Outputs. Complexity. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1143609
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143609