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

S. Y. Sohn

doi:10.1057/palgrave.jors.2602117

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

S. Y. Sohn

Department of Industrial Engineering

Research output: Contribution to journal › Article

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 language	English
Pages (from-to)	1289-1299
Number of pages	11
Journal	Journal of the Operational Research Society
Volume	57
Issue number	11
DOIs	https://doi.org/10.1057/palgrave.jors.2602117
Publication status	Published - 2006 Nov 30

All Science Journal Classification (ASJC) codes

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

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Sohn, S. Y. (2006). Random effects logistic regression model for ranking efficiency in data envelopment analysis. Journal of the Operational Research Society, 57(11), 1289-1299. https://doi.org/10.1057/palgrave.jors.2602117

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