Random effects logistic regression model for ranking efficiency in data envelopment analysis

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11 Citations (Scopus)


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 languageEnglish
Pages (from-to)1289-1299
Number of pages11
JournalJournal of the Operational Research Society
Issue number11
Publication statusPublished - 2006 Nov 30

Bibliographical note

Funding Information:
Acknowledgements—This work was supported by the Korea Research Foundation Grant (KRF-2003-041-D00612).

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing


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