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ELearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Case: Family selecting a car eLearning resources / MCDA team Director prof.

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Presentation on theme: "ELearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Case: Family selecting a car eLearning resources / MCDA team Director prof."— Presentation transcript:

1 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Case: Family selecting a car eLearning resources / MCDA team Director prof. Raimo P. Hämäläinen Helsinki University of Technology Systems Analysis Laboratory

2 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Group decision-making with value trees About the case Problem description Group decision making Weighted arithmetic mean method Value trees for car selection Group hierarchy Group preferences Sensitivity analysis

3 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology About the case The purpose is to illustrate group decision- making with value trees. Note, this is only one possible approach to group decision making. The weighted arithmetic mean method is applied to aggregate individual opinions into a group value tree. For basics of the value tree analysis, see the Job selection problem and the related theory parts.

4 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Problem description Family buying a car A family is buying a new car and they have to make a choice between three options. The first option, a sports car, is the absolute favorite of familys son, who have had the licence just for a couple of months. However, his father is concerned with the space requirements and prefers a cross-country vehicle, which would be far more spacious and perfectly suitable for his fishing trips. The last option, a family car, the favorite of familys mother, lags behind in performance fot the sports car and is not as spacious as the cross-country vehicle, but consumes considerably less, and most importantly, is far more cheaper than the others. Properties of the cars are presented in Table 1. Table 1. Properties of the cars.

5 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Group decision making Data projector The family decided to use Web-HIPREs group property to support the decision making. Father Internet Mother Son Group members create their own models... …which are combined in the group model Server

6 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Weighted arithmetic mean method 1) Preferences of individual DMs are modelled with a value tree. 2) The overall value is calculated as a weighted sum of individual values. DM1&2: V 1&2 (a 1 ) = w 1 v 1 (a 1 ) + w 2 v 2 (a 1 ) In the group hierarchy, the overall value of each DM is represented as an objective.

7 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Value trees for car selection Value trees of the mother and the father Mother and father decided to use similar value trees Note: Individual value trees need not be identical, but all models have to have same alternatives The model is available in Web-HIPRE

8 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Value trees for car selection Value tree of the son As the son is not concerned with money he decided to use this value tree For more about Problem structuring Preference elicitation see Job selection case and corresponding sections in the theory part.

9 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology The group hierarchy Group members value trees are set as objectives Each family member has a weight In this model equal weights are used w i =1/3, for i =1,2,3 AlternativesMembersGroup

10 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Group preferences Family car is the most preferred alternative Sports car comes second Cross-country vehicle is the least preferred alternative To see how the individual models are integrated in Web-HIPRE see the. with sound (3.2Mb) with sound no sound (604Kb)no sound animation (544Kb)animation Group decision making with Web-HIPRE

11 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Sensitivity analysis What if the family members weights w i are not equal? How sensitive is the model to changes in individual preference statements?

12 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Sensitivity to DMs weights The cross-country vehicle becomes familys choice if fathers weight increases to 0.76 If mothers weight is close to zero the sports car becomes the most preferred alternative

13 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Sensitivity to DMs weights If sons weight is more than 0.66 sports car becomes the most preferred alternative The results are not sensitive to the changes in group members weights!

14 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Sensitivity to individual preference statements For example, assume that the economy objective becomes more important due to tightened loan terms Modify individual preference statements accordingly Check for changes in the group model Repeat with other objectives

15 eLearning / MCDA Systems Analysis Laboratory Helsinki University of Technology Conclusion Family car is the recommended solution, i.e. the most preferred alternative. The solution is not sensitive to family members weights. However, it may be sensitive to individual preference statements. This issue would still require further analysis.


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