TY - JOUR
T1 - General and multiplicative non-parametric corporate performance models with interval ratio data
AU - Emrouznejad, Ali
AU - Rostamy-Malkhalifeh, Mohsen
AU - Hatami-Marbini, Adel
AU - Tavana, Madjid
PY - 2012/11/1
Y1 - 2012/11/1
N2 - The increasing intensity of global competition has led organizations to utilize various types of performance measurement tools for improving the quality of their products and services. Data envelopment analysis (DEA) is a methodology for evaluating and measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. All the data in the conventional DEA with input and/or output ratios assumes the form of crisp numbers. However, the observed values of data in real-world problems are sometimes expressed as interval ratios. In this paper, we propose two new models: general and multiplicative non-parametric ratio models for DEA problems with interval data. The contributions of this paper are fourfold: (1) we consider input and output data expressed as interval ratios in DEA; (2) we address the gap in DEA literature for problems not suitable or difficult to model with crisp values; (3) we propose two new DEA models for evaluating the relative efficiencies of DMUs with interval ratios, and (4) we present a case study involving 20 banks with three interval ratios to demonstrate the applicability and efficacy of the proposed models where the traditional indicators are mostly financial ratios.
AB - The increasing intensity of global competition has led organizations to utilize various types of performance measurement tools for improving the quality of their products and services. Data envelopment analysis (DEA) is a methodology for evaluating and measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. All the data in the conventional DEA with input and/or output ratios assumes the form of crisp numbers. However, the observed values of data in real-world problems are sometimes expressed as interval ratios. In this paper, we propose two new models: general and multiplicative non-parametric ratio models for DEA problems with interval data. The contributions of this paper are fourfold: (1) we consider input and output data expressed as interval ratios in DEA; (2) we address the gap in DEA literature for problems not suitable or difficult to model with crisp values; (3) we propose two new DEA models for evaluating the relative efficiencies of DMUs with interval ratios, and (4) we present a case study involving 20 banks with three interval ratios to demonstrate the applicability and efficacy of the proposed models where the traditional indicators are mostly financial ratios.
KW - Corporate performance
KW - Data envelopment analysis
KW - Interval data
KW - Multiplicative non-parametric
KW - Ratio analysis
UR - http://www.scopus.com/inward/record.url?scp=84864038797&partnerID=8YFLogxK
U2 - 10.1016/j.apm.2011.12.040
DO - 10.1016/j.apm.2011.12.040
M3 - Article
AN - SCOPUS:84864038797
VL - 36
SP - 5506
EP - 5514
JO - Applied Mathematical Modelling
JF - Applied Mathematical Modelling
SN - 0307-904X
IS - 11
ER -