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

Research output: Contribution to journalArticle

10 Citations (Scopus)

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 languageEnglish
Pages (from-to)1289-1299
Number of pages11
JournalJournal of the Operational Research Society
Volume57
Issue number11
DOIs
Publication statusPublished - 2006 Nov 30

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Data envelopment analysis
Logistics
Decision making
Information technology
Decision making units
Ranking
Random effects
Logistic regression model

All Science Journal Classification (ASJC) codes

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

Cite this

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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 journalArticle

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