Calculate an overall preference score for each


1. Your first step is to work with Alan to convert the consequences table shown on p. 91 to a preferences table. Clearly, on commuting time, Baranov is his "best" (100 points), Parkway his worst (0 points). He rates the others as shown on line 1 in the table below. Once completed, the preference table looks like this:


Parkway

Lombard

Baranov

Montana

Pierpoint

Commute

0

80

100

80

50

Access

0

80

60

100

70

Services

100

60

0

100

0

Size

90

80

0

100

80

Cost

10

50

100

0

40

2. Is it still clear that Lombard dominates Pierpoint, and that Montana practically dominates Parkway? You could drop Pierpoint and Parkway now, but keep them in while you finish the exercise.

3. Using the method described earlier, you elicit the following swing weights from Alan:

Commute

1.0

Access

1.5

Services

1.2

Size

3.0

Cost

1.0

4. Using these weights, calculate an overall preference score for each location. What do these scores imply for Alan's decision?

5. Alan wonders about the weights, especially the cost. He considers cost very important, but his swing weight for cost is relatively small. How do you explain this?

6. Alan notices that the two alternatives you saw were dominated (Pierpoint and Parkway) score poorly, but that Baranov, the worst-scoring option, was not dominated. How do you explain this?

7. The even swaps and swing weights methods took about the same amount of time and effort on this problem. Do you find one easier to explain to the client than the other? Which would you choose if Alan had 40 sites to evaluate, rather than four?

8. Write a short (one or two pages, single-spaced) report to Alan summarizing the two site selection procedures, what you recommend, and why. Include enough detail that Alan can defend his decision to his Board.

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Advanced Statistics: Calculate an overall preference score for each
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