Abstract
Ranking efficiency based on data envelopment analysis (DEA) results can be used for grouping decision-making units (DMUs). The resulting group membership can be partly related to the environmental characteristics of DMU, which are not used either as input or output. Utilizing the expert knowledge on super efficiency DEA results, we propose a multinomial Dirichlet regression model, which can be used for the purpose of selection of new projects. A case study is presented in the context of ranking analysis of new information technology commercialization projects. It is expected that our proposed approach can complement the DEA ranking results with environmental factors and at the same time it facilitates the prediction of efficiency of new DMUs with only given environmental characteristics.
| Original language | English |
|---|---|
| Pages (from-to) | 1289-1299 |
| Number of pages | 11 |
| Journal | Journal of the Operational Research Society |
| Volume | 57 |
| Issue number | 11 |
| DOIs | |
| Publication status | Published - 2006 Nov 30 |
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All Science Journal Classification (ASJC) codes
- Management Information Systems
- Strategy and Management
- Management Science and Operations Research
- Marketing
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Random effects logistic regression model for ranking efficiency in data envelopment analysis. / Sohn, S. Y.
In: Journal of the Operational Research Society, Vol. 57, No. 11, 30.11.2006, p. 1289-1299.Research output: Contribution to journal › Article
TY - JOUR
T1 - Random effects logistic regression model for ranking efficiency in data envelopment analysis
AU - Sohn, S. Y.
PY - 2006/11/30
Y1 - 2006/11/30
N2 - Ranking efficiency based on data envelopment analysis (DEA) results can be used for grouping decision-making units (DMUs). The resulting group membership can be partly related to the environmental characteristics of DMU, which are not used either as input or output. Utilizing the expert knowledge on super efficiency DEA results, we propose a multinomial Dirichlet regression model, which can be used for the purpose of selection of new projects. A case study is presented in the context of ranking analysis of new information technology commercialization projects. It is expected that our proposed approach can complement the DEA ranking results with environmental factors and at the same time it facilitates the prediction of efficiency of new DMUs with only given environmental characteristics.
AB - Ranking efficiency based on data envelopment analysis (DEA) results can be used for grouping decision-making units (DMUs). The resulting group membership can be partly related to the environmental characteristics of DMU, which are not used either as input or output. Utilizing the expert knowledge on super efficiency DEA results, we propose a multinomial Dirichlet regression model, which can be used for the purpose of selection of new projects. A case study is presented in the context of ranking analysis of new information technology commercialization projects. It is expected that our proposed approach can complement the DEA ranking results with environmental factors and at the same time it facilitates the prediction of efficiency of new DMUs with only given environmental characteristics.
UR - http://www.scopus.com/inward/record.url?scp=33750489390&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33750489390&partnerID=8YFLogxK
U2 - 10.1057/palgrave.jors.2602117
DO - 10.1057/palgrave.jors.2602117
M3 - Article
AN - SCOPUS:33750489390
VL - 57
SP - 1289
EP - 1299
JO - Journal of the Operational Research Society
JF - Journal of the Operational Research Society
SN - 0160-5682
IS - 11
ER -