Hostname: page-component-8448b6f56d-t5pn6 Total loading time: 0 Render date: 2024-04-19T05:33:32.100Z Has data issue: false hasContentIssue false
  • English
  • Français

Flexible measures in production process: A DEA-based approach

Published online by Cambridge University Press:  01 June 2011

Alireza Amirteimoori  and
Ali Emrouznejad
Alireza Amirteimoori
Affiliation:
Department of Applied Mathematics, Islamic Azad University, Rasht branch, Rasht, Iran. teimoori@guilan.ac.ir
Ali Emrouznejad
Affiliation:
Operations & Information Management Group, Aston Business School, Aston University, Birmingham B4 7ET, UK. a.emrouznejad@aston.ac.uk
Get access

Abstract

Data envelopment analysis (DEA) has been proven as an excellent data-oriented efficiency analysis method for comparing decision making units (DMUs) with multiple inputs and multiple outputs. In conventional DEA, it is assumed that the status of each measure is clearly known as either input or output. However, in some situations, a performance measure can play input role for some DMUs and output role for others. Cook and Zhu [Eur. J. Oper. Res.180 (2007) 692–699] referred to these variables as flexible measures. The paper proposes an alternative model in which each flexible measure is treated as either input or output variable to maximize the technical efficiency of the DMU under evaluation. The main focus of this paper is on the impact that the flexible measures has on the definition of the PPS and the assessment of technical efficiency. An example in UK higher education intuitions shows applicability of the proposed approach.

Keywords

Data envelopment analysisefficiencyflexible measure
Type
Research Article
Information
RAIRO - Operations Research , Volume 45 , Issue 1 , January 2011 , pp. 63 - 74
Copyright
© EDP Sciences, ROADEF, SMAI, 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Banker, R.D., Charnes, A. and Cooper, W.W., Some Methods for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Manage. Sci. 30 (1984) 1078–1092. CrossRef
Beasley, J., Comparing university departments. Omega 8 (1990) 171–183. CrossRef
Charnes, A. and Cooper, W.W., Programming with Linear Fractional Functions. Naval Research. Logistics Quarterly 9 (1962) 181–186. CrossRef
Charnes, A., Cooper, W.W. and Rhodes, E., Measuring the Efficiency of Decision Making Units. Eur. J. Oper. Res. 2 (1978) 429–444. CrossRef
A. Charnes, W.W. Cooper, A. Lewin and L.M. Seiford, Data Envelopment Analysis: Theory, Methodology and Applications. Kluwer Academic Publishers, Boston (1994).
Cook, W.D. and Performance, K. Bala measurement with classification information: An enhanced additive DEA model. Omega 31 (2003) 439–450.
Cook, W.D. and Zhu, J., Building performance standards into DEA structures. IIE Transactions 37 (2005) 267–275.
Cook, W.D. and Zhu, J., Classifying inputs and outputs in DEA. Eur. J. Oper. Res. 180 (2007) 692–699. CrossRef
Cook, W. D., Hababou, M. and Tuenter, H., Multi-component efficiency measurement and shared inputs in data envelopment analysis: An application to sales and service performance in bank branches. J. Prod. Anal. 14 (2000) 209–224. CrossRef
W.W. Cooper, L.M. Seiford and K. Tone, Introduction to data envelopment analysis and its uses. Springer Publisher (2006).
Emrouznejad, A., Tavares, G. and Parker, B., Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio- Econ. Plan. Sci. 42 (2008) 151–157. CrossRef
Toloo, M., On classifying inputs and outputs in DEA: A revised model. Eur. J. Oper. Res. 198 (2009) 358–360. CrossRef