Assignment Decision Theory
Last Updated on 28. April 2023 by Martin Schuster
Suppose we have three cars C1, C2, and C3. They have the same productivity but different parameters. The following table shows the parameter values.
Car | Color | Price EUR | Horsepower | Trunk volume |
C1 | White | 25,000 | 120 | 300 |
C2 | Silver | 22,000 | 110 | 320 |
C3 | Red | 29,000 | 150 | 250 |
You assign 3 points to white, 4 points to silver and 4 points to red.
The budget is 30,000 EUR.
The preferred horsepower would be 180.
Task 1
Calculate the achievement rate for all parameters for all cars.
Solution
Car | Color | Price EUR | Horsepower | Trunk volume |
C1 | 0.75 | 0.167 | 0.667 | 0.938 |
C2 | 1 | 0.267 | 0.611 | 1 |
C3 | 1 | 0.033 | 0.833 | 0.781 |
Task 2
Calculate the weights of each parameter with the direct ranking method. The following scores are given:
KPI | Score |
Horse Power | 10 |
Price | 5 |
Space | 6 |
Color | 2 |
Solution
Horse Power | Price EUR | Space | Color | |
Weight | 0.435 | 0.217 | 0.261 | 0.087 |
Task 3
What car should you select from the calculation above?
Solution
Color | Price | Horse Power | Trunk Volume | Final Score | |
C1 | 0.065 | 0.036 | 0.290 | 0.245 | 0.636 |
C2 | 0.087 | 0.058 | 0.266 | 0.261 | 0.671 |
C3 | 0.087 | 0.007 | 0.362 | 0.204 | 0.660 |
Car C2 has the highest final score and should be selected.