A Model for Evaluation of Professional Organizations Using AHP ...

Uzoka and Seleka 23the rows. This synthesis yields the percentage of relative priorities, which is expressed in alinear form to give the eigenvector. The implication of the eigenvector is that it expresses therelative importance of an attribute over another in the minds of the decision maker. Theeigenvalues/ eigenvector computations can be expressed mathematically as follows:VEij=Tij. j(1)where E ij is the eigenvalue of cell {aij}, Vij is the value of PWC matrix for cell {aij}, andis the sum of the values on column jT.jThe eigenvector for variable k is a column vector given as:n∑Ekjj = 1λk=(2)nwhere k is the eigenvector value corresponding to variable k, Ekj is the eigenvalue of cell {akj},(j = 1,2, …,n), and n is the number of evaluation variablesThis initial table of eigenvalues and eigenvector helps to establish priority model. It isimportant to note that the pairwise comparisons are also carried out for elements of the subcriteria(variables) of all evaluation criteria (factors). The eigenvalues and eigenvector for thelevel 2 criteria are shown in Table 5.Table 5 – Level 2 Eigenvalues and EigenvectorPFD FNB MBS HRM EigenvectorPFD 0.662 0.643 0.741 0.467 0.6283FNB 0.111 0.107 0.074 0.200 0.1230MBS 0.132 0.214 0.148 0.267 0.1903HRM 0.095 0.036 0.037 0.067 0.0588The next step is the rating of the professional organizations based on the respective variables.The evaluation of the ten professional bodies used in this study was carried out using anevaluation sheet that was designed to generate evaluations in terms of the twenty onevariables identified in Figure 1. These evaluations were carried out by the seventy twoexperts. A crucial component of the questionnaire was the determination of the level ofconfidence x (0