1. BUSINESS PERFORMANCE MANAGEMENT
Analytical Hierarchy Process (AHP): A Multi-Objective Decision Making Technique
Jason C.H. Chen, Ph.D.
Professor of MIS
School of Business
Gonzaga University
Spokane, WA 99258

2. Analytical Hierarchy Process
In many situations one may not be able to assign weights to the different decision factors. Therefore one must rely on a technique that will allow the estimation of the weights.
What is a solution?
One such process, The Analytical Hierarchy Process (AHP), involves pairwise comparisons between the various factors.

3. Analytical Hierarchy Process (cont.)
The process is started by the decision maker creating the value tree associated with the problem.
Then proceed by carrying out pairwise comparisons, both between
Alternatives on each factor, and
Factors at a given node.

4. Application Case of AHP
Jane is about to graduate from college and is trying to determine which job offer to accept. She plans to choose between three offers by determining how well each offer meets the following criteria (objectives):
High starting salary
Quality of life in city where job is located
Interest of work
Nearness of job to family

5. Assumptions
Jane has hard time in prioritizing those criteria. In other words, she needs to find one way to decide the weights for those criteria. AHP provides such a function.

6. Determine the problem
What job offer will give Jane possibly highest satisfaction?
Structure the hierarchy by putting the top objective (satisfaction with job), criteria, and alternatives as follows.

7. Satisfaction with a Job
Structure of the Problem
Satisfaction with a Job
criteria;
n=4
Starting Salary
Nearness to
Family
Life Quality
Interest
Job A
Job B
Job C

8. Satisfaction with a Job
Structure of the Problem
Satisfaction with a Job
Starting Salary
Life Quality
Interest
Nearness to
Family
Job A
Job B
Job C
Web site:

9. The Principle of the AHP …
The principle of the AHP relies on the pairwise comparison. This comparison is carried out using a scale from 1 to 9 as follows:
1 Equally preferred
2 Equally to Moderately preferred
3 Moderately preferred
4 Moderately to Strongly preferred
5 Strongly preferred
6 Strongly to Very Strongly preferred
7 Very Strongly preferred
8 Very to Extremely Strongly preferred
9 Extremely preferred

10. A pairwise comparison matrix for the criteria level
Satisfaction with a Job
We assume that “Starting Salary” is strongly more important than “Life Quality”. That is why 5 is entered into the Salary row and Quality column.
Compared to Interest, Salary is just a little bit more important. That is why 2 is entered into Salary row and Quality column.
Similarly, Salary is moderately to strongly preferred than “Nearness”. That is why 4 is entered into the Salary row and Nearness column.

11. A pairwise comparison matrix for the criteria level
Satisfaction with a Job
Web site:
Since n=4, there are 6 [n*(n-1)/2] judgments required to develop each matrix. Why?

12. Using the same steps of 3 and 4 (see handout) to determine the score of each alternative on each criterion. Take the first criterion “Salary” as an example. One pairwise matrix is constructed as follows (details see step 4 on the handout):
In terms of criterion of “Salary”, Job A is moderately important (“2”) than Job B. However, Job A is essentially more important (“4”) than Job C.

13. The next two pairwise matrices (for “Life Quality” and “Interest”) are as follows (see step#6 on the handout):

14. The last pairwise matrix (for “Nearness to family”) is listed below:

15. How to verify that the data entered in the comparison matrices is acceptable
Consistency Index (C.I) is computed as follows (see handout, p.5)
We then compare the value of C.I. to the value of random index (R.I). If the ratio of C.I. to R.I. is less than 10%, then we can say the judgment process is relatively consistent and the matrix is acceptable. Otherwise, the decision maker may need to re-examine the judgment process and re-compare criteria or alternatives. The consistency ratio (C.R.) is computed as follows:
C.R. = C.I. / R.I. = /0.9 = = 1.7% < 10%
Random Indices (R.I.) for Consistency Check n 2 3 4 5 6 7 8 9 10
R.I.
.58
.90
1.12
1.24
1.32
1.41
1.45
1.51

16. Satisfaction with a Job

17. We will open an existing model or
File name:
mbus673.jmd

19. Scroll down

20. Display the “weights” entered in the “Goal” or “Criteria”
1) Double click or 2) Select an “Element” then click Priorities then AHP
double
click
Double
click

21. (p.4 of Handout)

22. Result from double clicking “salary”

23. Result from double clicking “life quality”

24. Result from double clicking “interest”

25. Result from double clicking “nearness to family”

26. Perform Analysis
click

27. Perform Analysis

28. Result from “Analysis of Composite Priorities … “
click
According to the BAR chart, AHP suggests that Jane should take Job B. Why?

29. Result from “Analysis of Composite Priorities … “ – with Values
According to the “Values”, AHP suggests that Jane should take Job B (you need to “Add total” , see the next slide)

30. Result as Text Value Tree 0 satisfaction with a job 1 salary 0.512
2 job A 0.571
2 job B 0.286
2 job C 0.143
1 life quality 0.098
2 job A 0.163
2 job B 0.540
2 job C 0.297
1 interest 0.244
2 job A 0.088
2 job B 0.669
2 job C 0.243
1 nearness to family 0.146
2 job A 0.082
2 job B 0.315
2 job C 0.603
Composite Priorities
job A job B job C
salary
life quali
interest
nearness t
Overall
step 7 (p.5)

32. Your Turn -- Try It!

33. How to create an AHP model for “a Job Selection.”

34. Double click a node (element) will appear
Criteria level
Enter a name
Goal level

35. Edit the element’s Name (only if needed)
Select this

36. Steps of creating “Links”
2. Right click
1. Left click
Complete the remaining links

37. Complete the remaining links between “Criteria” and Alternatives”
Steps of creating “Links” (cont.)
Labels are changed
1. Left click
2. Right click
Complete the remaining links between “Criteria” and Alternatives”

38. Steps of creating “Links” – Final Model (cont.)
Labels are changed

39. Be sure that to save the model now (and periodically).
Enter “filename”

40. Enter “filename”
A “filename” is saved

41. Steps of assigning weights to different decision factors
Goal level (satisfaction with job)
Criteria level (salary, life quality, interest, and nearness to family)

42. Steps of assigning weights to different decision factors
We will first enter “pairwise comparison matrix” for the “Criteria” level
Click on “AHP”
Double Left click

43. Steps of assigning weights to different decision factors (cont.)
Drag the bar or enter a number
“Starting Salary” is strongly more important than “Life Quality”. That is why 5 is entered into the Salary row and Quality column.

44. Steps of assigning weights to different decision factors (cont.)

45. Steps of assigning weights to different decision factors (cont.)

46. Steps of assigning weights to different decision factors (cont.)

47. Steps of assigning weights to different decision factors (cont.)

48. Steps of assigning weights to different decision factors (cont.)

49. Steps of assigning weights to different decision factors (cont.)
This completes “pairwise comparison matrix” for the “Goal” level (i.e., “Satisfaction with a Job”)
Click OK when done

50. Steps of assigning weights to different decision factors (cont.)
Next, to complete “pairwise comparison matrix” for the “Criteria” level of “Salary”)
Double left click

51. Steps of assigning weights to different decision factors (cont.)

52. Steps of assigning weights to different decision factors (cont.)

53. Perform Analysis

54. Result from “Analysis of Composite Priorities … “
click
According to the BAR chart, AHP suggests that Jane should take Job B

55. Result from “Analysis of Composite Priorities … “ – with Values
According to the “Values”, AHP suggests that Jane should take Job B (you need to “Add total” , see the next slide)

56. Result as Text Value Tree 0 satisfaction with a job 1 salary 0.512
2 job A 0.571
2 job B 0.286
2 job C 0.143
1 life quality 0.098
2 job A 0.163
2 job B 0.540
2 job C 0.297
1 interest 0.244
2 job A 0.088
2 job B 0.669
2 job C 0.243
1 nearness to family 0.146
2 job A 0.082
2 job B 0.315
2 job C 0.603
Composite Priorities
job A job B job C
salary
life quali
interest
nearness t
Overall
step 7 (p.5)

57. Save your work again
click

58. Have a fun!
File name:
mbus673.jmd

59. The following slides might be skipped.

60. Sensitivity Analysis