Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis

Tran, Trung Hieu and Mao, Yong and Nathanail, Paul and Siebers, Peer-Olaf and Robinson, Darren (2018) Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis. Omega . ISSN 0305-0483

[img] PDF - Repository staff only until 15 December 2019. - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution Non-commercial No Derivatives.
Download (313kB)

Abstract

In this paper, we develop an integrated model for slacks-based measure (SBM) simultaneously of both the efficiency and the super-efficiency for decision-making units (DMUs) in data envelopment analysis (DEA). Unlike the traditional solution approaches in which we need to identify the efficient DMUs by the SBM model of Tone (2001) [20] before applying the super SBM model of Tone (2002) [21] for the DMUs to achieve their super-efficiency scores, our integration can obtain the efficiency scores of the inefficient DMUs and the super-efficiency scores of the efficient DMUs by solving simultaneously these two models by an one-stage approach. Therefore, it may save computational time for large-scale practical applications. Due to the non-linearity in the objective function of this integrated model, we develop a linearisation technique to deal with the non-linear model. The numerical experiments, carried out on several examples in the literature and a case study, have demonstrated the accuracy and the computational time effectiveness of our proposed model as compared with the traditional solution approaches.

Item Type: Article
Keywords: Data envelopment analysis (DEA) ; Slacks-based measure ; Efficiency ; Super-efficiency ; One-stage approach ; Linearisation
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
University of Nottingham, UK > Faculty of Social Sciences > School of Geography
University of Nottingham, UK > Faculty of Science > School of Computer Science
University of Nottingham, UK > Faculty of Science > School of Physics and Astronomy
Identification Number: https://doi.org/10.1016/j.omega.2018.06.008
Depositing User: Eprints, Support
Date Deposited: 29 Jun 2018 12:08
Last Modified: 02 Jul 2018 09:30
URI: http://eprints.nottingham.ac.uk/id/eprint/52691

Actions (Archive Staff Only)

Edit View Edit View