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

More documents

Recommendations

Info

Uzoka and Seleka 25The ratings in Table 6 show that the organization with identification number 0002 rankedfirst, while 00001 ranked second, and so on. After the application of the PBEFI on Table 6,the final ranking shows that organizations 00003 and 00004, which were both tied on thethird position in the initial ranking, now rank third and fourth respectively (Table 7).Organization with identification number 00006, which ranked fourth in the initial ranking,now ranks seventh. The results show that AHP is able to provide a mathematical formalismfor refining the results of the initial rakings of the professional organization, which could serveas an initial basis for decision making concerning the performance of these professionalorganizations.With the introduction of the confidence levels of the experts on the ratings of theorganizations (Table 8), a further refinement of the evaluation results is carried out throughthe scaling of the results obtained in Table 7 using the relationship:1S = A. (7)TCwhere S is the final score matrix, A is the matrix shown in Table 7 less the last two columns,while C T is the transpose of the matrix shown in Table 8.Table 7 – Evaluation Result based on AHPOrg. CDS PSP TCV WSS CFS RPB MCP DBV PFI BGP RGT JIT PFE ARB MBD SBS STR STD STC STM00001 0.375 0.241 0.061 0.363 0.179 0.135 0.458 0.032 0.117 0.028 0.225 0.023 0.258 0.035 0.286 0.111 0.023 0.043 0.012 0.000002 0.500 0.181 0.048 0.605 0.179 0.180 0.916 0.024 0.117 0.042 0.300 0.017 0.322 0.023 0.286 0.148 0.045 0.064 0.016 0.000003 0.375 0.121 0.036 0.363 0.143 0.088 0.458 0.016 0.117 0.056 0.225 0.012 0.193 0.023 0.214 0.111 0.034 0.064 0.012 0.000004 0.375 0.060 0.036 0.484 0.179 0.135 0.229 0.024 0.088 0.028 0.225 0.012 0.193 0.023 0.286 0.111 0.034 0.064 0.016 0.000005 0.250 0.121 0.036 0.242 0.107 0.090 0.229 0.008 0.088 0.028 0.150 0.006 0.193 0.012 0.214 0.074 0.023 0.043 0.008 0.000006 0.250 0.060 0.036 0.363 0.107 0.090 0.229 0.016 0.059 0.028 0.150 0.012 0.193 0.023 0.214 0.074 0.034 0.043 0.008 0.000007 0.375 0.181 0.048 0.242 0.143 0.135 0.229 0.016 0.088 0.028 0.150 0.012 0.193 0.023 0.214 0.074 0.023 0.043 0.008 0.100008 0.125 0.121 0.036 0.363 0.107 0.090 0.229 0.008 0.088 0.028 0.500 0.006 0.258 0.012 0.214 0.074 0.034 0.043 0.008 0.000009 0.125 0.121 0.024 0.242 0.107 0.045 0.229 0.016 0.059 0.028 0.075 0.006 0.193 0.012 0.143 0.037 0.023 0.043 0.008 0.000010 0.250 0.121 0.036 0.242 0.072 0.045 0.229 0.008 0.059 0.028 0.150 0.012 0.193 0.023 0.214 0.074 0.023 0.043 0.008 0.0The implication of the relationship in (7) is that if the average confidence level of the raterson a given variable is high, then their ratings would have averaged close to the realistic value,but if the average confidence level is low, then the reciprocal of the confidence value wouldeither increase or reduce the ratings accordingly in order to approximate the realistic value.Table 8 – Average Confidence Levels of Experts on the RatingsOrg CDS PSP TCV WSS CFS RPB MCP DBV PFI BGP RGT JIT PFE ARB MBD SBS STR STD STC STM00001 0.9 0.7 0.8 0.7 0.9 0.6 0.6 0.7 0.7 0.8 0.7 0.5 0.5 0.6 0.6 0.9 0.4 0.5 0.6 0.600002 0.7 0.6 0.7 0.9 0.8 0.7 0.7 0.8 0.5 0.4 0.6 0.9 0.7 0.5 0.8 0.8 0.7 0.6 0.6 0.400003 0.5 0.5 0.6 0.6 0.7 0.5 0.5 0.6 0.7 0.5 0.6 0.8 0.8 0.7 0.7 0.7 0.6 0.8 0.9 0.700004 0.6 0.8 0.8 0.7 0.8 0.5 0.3 0.6 0.8 0.6 0.6 0.6 0.6 0.7 0.5 0.8 0.5 0.8 0.5 0.400005 0.4 0.7 0.7 0.7 0.5 0.4 0.4 0.7 0.5 0.6 0.6 0.5 0.6 0.9 0.8 0.5 0.8 0.5 0.4 0.800006 0.9 0.6 0.6 0.8 0.5 0.5 0.7 0.4 0.7 0.7 0.6 0.4 0.7 0.8 0.6 0.6 0.9 0.7 0.6 0.600007 0.8 0.6 0.7 0.7 0.6 0.6 0.5 0.6 0.8 0.8 0.4 0.6 0.5 0.5 0.9 0.8 0.7 0.7 0.7 0.900008 0.6 0.8 0.6 0.8 0.5 0.3 0.8 0.6 0.9 0.4 0.7 0.6 0.9 0.7 0.4 0.6 0.4 0.8 0.5 0.700009 0.7 0.5 0.6 0.8 0.6 0.4 0.6 0.9 0.6 0.5 25 0.8 0.8 0.8 0.7 0.6 0.9 0.7 0.6 0.8 0.800010 0.9 0.6 0.7 0.7 0.7 0.5 0.4 0.6 0.4 0.5 0.7 0.6 0.6 0.8 0.7 0.8 0.9 0.9 0.6 0.6
Uzoka and Seleka 26Applying equation (7) to Tables 7 and 8 produces the final evaluation result, shown in Table9. This is a refinement of the evaluation result obtained by AHP to include the confidencelevels of the experts evaluating the organizations.Table 9 – Final Evaluation ResultOrg Id Final Rating Rank00001 4.518893 400002 5.732718 100003 4.574631 300004 4.577952 200005 3.607595 700006 2.979794 800007 3.664917 600008 3.713016 500009 2.380044 1000010 2.942111 9From Table 9, it could be observed that the organizations with ids. 00002, 00003, 00009,and 00010 still retained their first, third, tenth and ninth positions respectively. However,the following organization pairs interchanged positions respectively: {00001, 00004},{00005, 00006}, {00007, 00008}. The implication is that the initial ratings producedresults which may have been affected by the degree of confidence of the experts who ratedthe organizations. However, this was refined by using the confidence levels to deflate theinitial ratings.The study further reveals that high premium is placed on professional development, which hasan eigenvector value of 62.83% (equation 4). In particular, professional organizationsemphasize codes and standards (12.51%), and workshops/seminars (12.10%) as keydeterminants of performance.5. Conclusion and RecommendationsMeasuring performance of a service oriented organization such as a professional body is acomplex managerial function that requires the combination of quantitative and qualitativedecision variables. These variables are in most cases, hierarchically structured. The decisionsupport model proposed in this study, constructs a hierarchy of decision criteria, which aremainly qualitative in nature. This can be effectively used to carry out the performancemeasurement of professional organizations and a comparative measurement, with a view toranking the professional organizations. Furthermore, the classical method of AnalyticHierarchy Process is used to construct a pairwise comparison matrix of all the decisionvariables to obtain a matrix of eigenvalues and eigenvector, which aids the eventual ranking ofthe professional organizations. This was further refined based on the levels of confidence ofthe experts rating the organizations. The level of confidence is affected by the relevance ofthe expert’s discipline to the organization in question, his years of experience, qualifications,and other organizational factors. The results of the study show that a stepwise refinement ofthe results of the initial evaluation process can be achieved to attain some level of optimality26
Page 1 and 2: International Review of Business Re
Page 3 and 4: Uzoka and Seleka 18input for collec
Page 5 and 6: Uzoka and Seleka 203. MethodologyTh
Page 7 and 8: Uzoka and Seleka 22Performance Deci
Page 9: Uzoka and Seleka 24n∑W i= λ R µ
Page 13 and 14: Uzoka and Seleka 28ReferencesBernol

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

Create successful ePaper yourself

Delete template?

Save as template?