Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation
Table 2
Satisficing approach, aspiration level for objective 1: .
Interdependencies
Final performances
Average performances
obj 1/obj 2
Panel A: coordination mode: central
Low/low
0.9090
0.8818
0.8954
0.9030
0.8700
0.8865
Low/medium
0.9065
0.8503
0.8784
0.9005
0.8393
0.8699
Medium/medium
0.8857
0.7849
0.8353
0.8794
0.7762
0.8278
Low/high
0.8996
0.8293
0.8645
0.8938
0.8201
0.8570
Medium/high
0.8784
0.7850
0.8317
0.8729
0.7768
0.8248
High/high
0.8568
0.7117
0.7842
0.8526
0.7073
0.7799
Panel B: coordination mode: decentral
Low/low
0.9122
0.8783
0.8952
0.9104
0.8715
0.8910
Low/medium
0.9166
0.8505
0.8836
0.9146
0.8422
0.8784
Medium/medium
0.8907
0.7983
0.8445
0.8851
0.7889
0.8370
Low/high
0.9130
0.8259
0.8695
0.9110
0.8166
0.8638
Medium/high
0.8871
0.7888
0.8379
0.8817
0.7795
0.8306
High/high
0.8573
0.7134
0.7853
0.8482
0.7074
0.7778
Incentivisation: and . Results are based on 450 landscapes, each with 20 adaptive walks. obj = objective, confidence intervals vary from 0.002 to 0.003 on the 99.9% level.
