Journal of Civil Engineering Vol 68 No 2

Journal of the South African Institution of Civil Engineering Volume 68 Number 2 June 2026 9 In terms of management capability, the contractor must demonstrate that it has several managerial staff with relevant business-related qualifications and skills who contribute to the sustainability of the business. Over and above these criteria, the cidb must consider occupa- tional health and safety to establish and maintain effective systems and manage the risks to the occupational health and safety of employees arising from the construction work. A Microsoft Excel spreadsheet-based program, set up using the AHP principle, was used to calculate the criteria priority vectors and project priority vectors, check- ing the consistency of pairwise compari- sons and producing the overall ranking of the grading alternatives. Tanyimboh and Kalungi (2009) indicate that matrix A is an n × n real matrix, where n is the number of evaluation criteria considered. Each entry ajk of matrix A rep- resents the importance of the j th criterion relative to the k th criterion. If: ajk > 1: j th criterion is more important than the k th criterion ajk < 1: j th criterion is less important than the k th criterion ajk = 1: j th criterion is of the same importance as the k th criterion. A = … … 1 a 12 1 1 a 1 n a 12 1 a 2 n 1 1 a 2 n a 1 n … … … … … (1) Where A is the matrix and the numerical values that the criteria may take as indi- cated in Table 1. After building matrix A , the normalised pairwise comparison matrix B , depicted as b jk , can be derived from matrix A by making the sum of entries on each column equal to 1; see Equation 2. b jk = a jk ∑ n a jk i = 1 (2) Where b jk is matrix B and a jk is the criteria value divided by the total value of the over- all criteria values. Finally, the priority vector P is then obtained by averaging the entries in each row of matrix B . p j = ∑ n b jk n k= 1 (3) Priority vector P rates the seven main criteria listed in Figure 1 according to their importance to the overall goal, which is performance evaluation of contractors. The consistency ratio (CR) is defined by Equation 4. CR = CI RI (4) Where CI , the consistency index (see Equation 7), is the matrix of comparisons A (Equation 1), the priority vector P = (p 1 , . . . , pn ) (Equations 2 and 3), the column vector X = (x1, . . . , xn)T (Equation 5) and λ max the maximum eigenvalue (Equation 6) of the pairwise comparison matrix A . X = AP (5) λmax = 1 n ∑ n x i p i (6) CI = λmax − n n − 1 (7) The comparison – the elements of A – is tolerated/considered satisfactory when Equation 8 is satisfied. CI RI ≤ 0.1 (8) A perfectly consistent comparison will be CI = 0. RI in Equation 8 is the random index, i.e. the consistency index when the entries of A are completely random. The values of RI for small problems ( n ≤ 10) are shown in Table 4. RESULTS AND DISCUSSIONS The questionnaire results indicated that the contractor grading system, construc- tion entry requirements, and the effective- ness of both the grading system and the grading and performance evaluation crite- ria may contribute to enhanced contractor capabilities and improved project per- formance, which represents the outcome variable. To determine whether there is a need to improve the current registration, grading, and performance evaluation pro- cesses for contractors in the construction sector, respondents were specifically asked to indicate whether enhancements to these processes are necessary. 90.6% (135) of the respondents indicated that enhancing the current construction sector entry requirements will assist in improving the performance outputs of the construction sector, while 84.6% (126) i= 1 Table 4 Values of the random index (RI) for small problems (Saaty 1987) n 2 3 4 5 6 7 8 9 10 RI 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.51 Enhanced contractor capabilities and project performancs Contractor grading system Construction entry requirements Efficacy of the grading system Efficacy of the grading and performance evaluation criteria 0.452 0.076 0.262 –0.103 Figure 7 The research model with beta coefficients