A comparison between singular value decomposition and eigenvector method in group decision making
In any group decision making exercise, the issues of having justified and consistent decisions are always of major concerns, especially when the group members come from diverse backgrounds, selection expectations and priorities, and there are a number of selection criteria to consider. This paper...
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| Format: | Article |
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Penerbit ukm
2008
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| Online Access: | http://journalarticle.ukm.my/1859/ http://journalarticle.ukm.my/1859/ |
| Summary: | In any group decision making exercise, the issues of having justified and consistent decisions
are always of major concerns, especially when the group members come from diverse
backgrounds, selection expectations and priorities, and there are a number of selection criteria
to consider. This paper looks at these issues in the faculty member selection domain where the
objective is to select the best candidate to be the new faculty member. Two hypotheses are
tested using two-way ANOVA; overall candidates’ ranking depends on their own performance
and competencies, and overall candidates’ ranking does not depend on individual selection
committee members’ different roles. Selection committee members were treated as treatment
factor while the candidates as the blocking factor. Singular value decomposition (SVD) and
eigenvector method (EM), two different methods in analytic hierarchy process (AHP) were
used to obtain the rankings. The statistical tests showed that both SVD and EM resulted in the
same conclusion, that is the overall candidates’ ranking does not depend on the difference in
the selection committee members’ selection criteria preferences, but on the individual
candidates’ performance and competencies. Hence, all parties can be assured of an unbiased
evaluations and the selection process itself is conducted in the most professional manner |
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