A Distribution-Free Approach to Stochastic Efficiency Measurement with Inclusion of Expert Knowledge
Table 11
DEA-Chebyshev model efficiency analysis from simulation 4 at .
Upper bounds
Lower bounds
St. dev
DMU1
0.8
1.605
1.207 (7)
1.377 (3)
1.292 (0.68)
0.57
1
DMU2
0.729
1.291
1.951 (6)
0.918 (3)
1.4347 (0.05)
0.398
1
DMU3
0.776
1.204
0 (0)
0.719 (4)
0.359 (0.1)
0.303
0.99
DMU4
0.67
1.126
0
0.92
0.46
0.322
0.898
DMU5
0.464
0.987
0
0
0
0.37
0.726
DMU6
0.43
0.813
0
0
0
0.271
0.622
DMU7
0.716
1.363
6.874 (12)
3.849 (10)
5.361 (0.00)
0.458
1
DMU8
0.572
0.979
0
0
0
0.288
0.775
DMU9
0.603
1.01
0
0.015
0.007
0.288
0.807
DMU10
0.697
0.928
0
0
0
0.163
0.812
DMU11
0.799
1.767
0 (0)
2.327 (9)
1.164 (0.002)
0.685
0.9
DMU12
0.831
1.077
0
0.512
0.256
0.174
0.954
DMU13
0.884
1.097
2.217 (4)
0.514 (3)
1.366 (0.06)
0.15
0.991
DMU14
0.913
3.862
1.316 (5)
2.731 (7)
2.023 (0.03)
2.085
1
DMU15
0.923
2.682
1.435 (3)
1.119 (2)
1.277 (0.29)
1.244
1
Note: In Tables 8–11, the values shown in columns 4 and 5 in brackets represent the frequency with which a DEA-efficient DMU is used as a reference unit in DCF. Those in column 6 represent the values for the upper and lower limits for the lambdas for the DEA-efficient units.
