GMAA: A DSS Based on the Decision Analysis Methodology - Application Survey and Further Developments - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 275

Fig. 10 shows the assessed imprecise linear piecewise utility function for the Total annual
expenditure (Spend HCC ) , whereas Fig. 11 shows the attribute weights for the decision.
Fig. 12 shows the ranking of segments derived from the additive multi-attribute utility
model. SG19 , SG11 , SG18 and SG 13 are the best-ranked segments, with average overall
utilities of 0.6963, 0.6835, 0.5877 and 0.5417, respectively; whereas SG9 , SG4 and SG5 are the
worst ranked segments, with average overall utilities of 0.3833, 0.3716 and 0.3213. Although
SG19 appears to be the most highly recommended segment, sensitivity analysis (SA) should
be used to examine the overlapped utility intervals (ranking robustness) in a more detail.
Fig. 11. Attribute weights in the selection of segment to be sourced from low cost countries
Fig. 12. Ranking of segment to be sourced from low cost countries
Only three segments, SG11 , SG18 and SG19 , are non-dominated and potentially optimal.
Note that these were the best-ranked segments. Looking at the box plots output by Monte