Multiobjective Decision Making Policies and Coordination Mechanisms in Hierarchical Organizations: Results of an Agent-Based Simulation
Table 1
Equal weighting.
Interdependencies
Final performances
Average performances
obj 1/obj 2
Panel A: coordination mode: central
Low/low
0.8984
0.8994
0.8989
0.8941
0.8949
0.8945
Low/medium
0.8777
0.8737
0.8757
0.8734
0.8694
0.8714
Medium/medium
0.8515
0.8475
0.8495
0.8479
0.8437
0.8458
Low/high
0.8515
0.8508
0.8512
0.8478
0.8474
0.8476
Medium/high
0.8215
0.8334
0.8274
0.8186
0.8303
0.8245
High/high
0.8089
0.8084
0.8087
0.8070
0.8063
0.8066
Panel B: coordination mode: decentral
Low/low
0.8987
0.8975
0.8981
0.8957
0.8945
0.8951
Low/medium
0.9004
0.8705
0.8855
0.8967
0.8638
0.8803
Medium/medium
0.8599
0.8596
0.8598
0.8530
0.8525
0.8527
Low/high
0.8961
0.8415
0.8688
0.8909
0.8310
0.8609
Medium/high
0.8457
0.8323
0.8390
0.8369
0.8198
0.8284
High/high
0.8121
0.8153
0.8137
0.7989
0.8023
0.8006
Incentivisation: and . Results are based on 450 landscapes, each with 20 adaptive walks. obj = objective, confidence intervals vary from 0.002 to 0.005 on the 99.9% level.
