AHP - 1 Dr. Chen – Business Intelligence 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 [email protected]BUSINESS PERFORMANCE MANAGEMENT
24
Embed
Analytical Hierarchy Process (AHP): A Multi-Objective Decision Making Technique
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 [email protected]. Analytical Hierarchy Process. - PowerPoint PPT Presentation
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
AHP - 1Dr. Chen – Business Intelligence
Analytical Hierarchy Process (AHP): A Multi-Objective Decision
Making Technique
Jason C.H. Chen, Ph.D.Professor of MIS
School of BusinessGonzaga UniversitySpokane, WA 99258
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.
AHP - 3Dr. Chen – Business Intelligence
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.
AHP - 4Dr. Chen – Business Intelligence
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
AHP - 5Dr. Chen – Business Intelligence
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.
AHP - 6Dr. Chen – Business Intelligence
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.
AHP - 7Dr. Chen – Business Intelligence
Satisfaction with a Job
Job A Job B Job C
Structure of the Problem
Starting Salary Life Quality Interest Nearness to
Family
criteria; n=4
AHP - 8Dr. Chen – Business Intelligence
Satisfaction with a Job
Starting Salary Life Quality Interest Nearness to
Family
Job A Job B Job C
Structure of the Problem
Web site:http://www.hipre.hut.fi/
criteria; n=4
AHP - 9Dr. Chen – Business Intelligence
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
AHP - 10Dr. Chen – Business Intelligence
A pairwise comparison matrix for the criteria level
12/124/12122/12/12/115/1
4251
NearnessInterestQualitySalary
NearnessInterestQualitySalarySatisfaction 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.
AHP - 11Dr. Chen – Business Intelligence
A pairwise comparison matrix for the criteria level
12/124/12122/12/12/115/1
4251
NearnessInterestQualitySalary
NearnessInterestQualitySalarySatisfaction with a Job
Web site:http://www.hipre.hut.fi/
Since n=4, there are 6 [n*(n-1)/2] judgments required to develop each matrix. Why?
AHP - 12Dr. Chen – Business Intelligence
12/14/1212/1421
1
CJobBJobAJob
CJobBJobAJobSALARY
A
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.
AHP - 13Dr. Chen – Business Intelligence
1333/1123/12/11
2
CJobBJobAJob
CJobBJobAJobQuality
A
The next two pairwise matrices (for “Life Quality” and “Interest”) are as follows (see step#6 on the handout):
13/133173/17/11
3
CJobBJobAJob
CJobBJobAJobInterest
A
AHP - 14Dr. Chen – Business Intelligence
12714
7/14/112/14
CJobBJobAJob
CJobBJobAJobNearness
A
The last pairwise matrix (for “Nearness to family”) is listed below:
AHP - 15Dr. Chen – Business Intelligence
0159.03
40477.41
.. max
n
nIC
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:
How to verify that the data entered in the comparison matrices is acceptable
Display the “weights” entered in the “Goal” or “Criteria”1) Double click or 2) Select an “Element” then click Priorities then AHP
AHP - 20Dr. Chen – Business Intelligence
(p.4 of Handout)
AHP - 21Dr. Chen – Business Intelligence
Result from “Analysis of Composite Priorities … “
click
According to the BAR chart, AHP suggests that Jane should take Job B
AHP - 22Dr. Chen – Business Intelligence
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)
AHP - 23Dr. Chen – Business Intelligence
Result as Text Value Tree0 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 0.293 0.146 0.073 life quali 0.016 0.053 0.029 interest 0.021 0.163 0.059 nearness t 0.012 0.046 0.088 Overall 0.342 0.408 0.249