TY - GEN
T1 - Statistical analysis in the DEA context
AU - Sinuany-Stern, Zilla
AU - Friedman, Lea
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/3/11
Y1 - 2016/3/11
N2 - This paper deals with Data Envelopment Analysis (DEA), where we have several organizational units or Decision Making Units - DMUs. Each DMU has multiple inputs and multiple outputs. DEA calculates the relative efficiencies of DMUs via linear programming. Various versions of DEA were developed. Although DEA is a deterministic model, during the last two decades statistical methods are used in three main dimensions: 1. In preparing the input and output data and DMUs, 2. As a stochastic alternative to derive DMUs efficiencies, 3. As a second stage after the efficiencies are derived to test the relationship between the efficiency and various environmental parameters. Our paper explores the use of the various statistical methods in the DEA context covering these three main dimensions. The major statistical methods we present are: comparisons including parametric and non-parametric tests, correlation and regression, analyses of variance, multivariate analyses, and bootstrapping. Examples from the literature, using various statistical methods in the DEA context, will be presented along the above three dimensions.
AB - This paper deals with Data Envelopment Analysis (DEA), where we have several organizational units or Decision Making Units - DMUs. Each DMU has multiple inputs and multiple outputs. DEA calculates the relative efficiencies of DMUs via linear programming. Various versions of DEA were developed. Although DEA is a deterministic model, during the last two decades statistical methods are used in three main dimensions: 1. In preparing the input and output data and DMUs, 2. As a stochastic alternative to derive DMUs efficiencies, 3. As a second stage after the efficiencies are derived to test the relationship between the efficiency and various environmental parameters. Our paper explores the use of the various statistical methods in the DEA context covering these three main dimensions. The major statistical methods we present are: comparisons including parametric and non-parametric tests, correlation and regression, analyses of variance, multivariate analyses, and bootstrapping. Examples from the literature, using various statistical methods in the DEA context, will be presented along the above three dimensions.
KW - DEA
KW - Data envelopment analysis
KW - Efficiency
UR - http://www.scopus.com/inward/record.url?scp=84964847117&partnerID=8YFLogxK
U2 - 10.1109/SMRLO.2016.82
DO - 10.1109/SMRLO.2016.82
M3 - Conference contribution
AN - SCOPUS:84964847117
T3 - Proceedings - 2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016
SP - 469
EP - 474
BT - Proceedings - 2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016
A2 - Lisnianski, Anatoly
A2 - Frenkel, Ilia
PB - Institute of Electrical and Electronics Engineers
T2 - 2nd International Symposium on Stochastic Models in Reliability Engineering, Life Science, and Operations Management, SMRLO 2016
Y2 - 15 February 2016 through 18 February 2016
ER -