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Nonlinear Efficiency in DEA Relative to “Ideal Reference”

Nonlinear Efficiency in DEA Relative to “Ideal Reference”

P. Sunil Dharmapala
Copyright: © 2014 |Pages: 11
ISBN13: 9781466652026|ISBN10: 1466652020|EISBN13: 9781466652033
DOI: 10.4018/978-1-4666-5202-6.ch146
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MLA

Dharmapala, P. Sunil. "Nonlinear Efficiency in DEA Relative to “Ideal Reference”." Encyclopedia of Business Analytics and Optimization, edited by John Wang, IGI Global, 2014, pp. 1637-1647. https://doi.org/10.4018/978-1-4666-5202-6.ch146

APA

Dharmapala, P. S. (2014). Nonlinear Efficiency in DEA Relative to “Ideal Reference”. In J. Wang (Ed.), Encyclopedia of Business Analytics and Optimization (pp. 1637-1647). IGI Global. https://doi.org/10.4018/978-1-4666-5202-6.ch146

Chicago

Dharmapala, P. Sunil. "Nonlinear Efficiency in DEA Relative to “Ideal Reference”." In Encyclopedia of Business Analytics and Optimization, edited by John Wang, 1637-1647. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-5202-6.ch146

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Abstract

Several researchers in the past have emphasized the importance of computing efficiency measures in Data Envelopment Analysis (DEA) relative to a best-practice benchmark. Thompson et al. (1995) introduced a nonlinear efficiency measure with linked-cone (LC) assurance-regions (AR) in DEA. In this paper, we compute Thompson-Thrall's measure vis-à-vis linear efficiency measures of CCR (Charnes et al., 1978), BCC (Banker et al., 1984), CCR/AR and BCC/AR (Thompson et al., 1992), relative to “ideal reference”- an industry average. We demonstrate the computations in an application to a set of banks and show that the nonlinear measure is stricter than the linear measures.

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