Journal of Civil Engineering Vol 68 No 2

Volume 68 Number 2 June 2026  Journal of the South African Institution of Civil Engineering 10 agreed that enhancing the current grading system could assist in improving contrac- tors’ capabilities and performance outputs. The results are depicted in Figure 7. The results indicate a positive relation- ship between the efficacy of the grading and performance evaluation criteria and enhanced contractor capabilities and project performance. This suggests that improvements in the effectiveness of the grading and performance evaluation crite- ria are associated with enhanced contractor capabilities and improved project perfor- mance. Furthermore, the path modelling results (β = 0.418, t = 3.665, p = 0.000) con- firm that this relationship is positive and statistically significant. In other words, the efficacy of the grading and performance evaluation criteria has a substantial positive effect on enhanced contractor capabilities and project performance. Path modelling describes the relation- ship between observed or measured vari- ables and a theoretical construct (Roche et al 2011) and assesses the structural paths of a conceptualised research model (Anderson et al 1998). The purpose of the SEM procedure was to demonstrate and test the theoretical foundations of the study and the significance of the relationship between model constructs (Jenatabadi & Ismail 2014). The study found a positive relationship between the contractor grading system and grading criteria efficacy. This suggests that an effective contractor grading system is associated with higher grading criteria efficacy. The results further demonstrate that the contractor grading system has a significant positive effect on the efficacy of the grading criteria (β = 0.659, t = 11.288, p = 0.000). Path modelling also revealed that the relationship between these two constructs is the second strongest in the proposed model. Furthermore, the findings revealed a marginally positive relationship between the contractor grading system and enhanced contractor capabilities and pro- ject performance. However, the relationship was not statistically significant (β = 0.08, t = 0.71, p = 0.474) because the t-statistic was less than 1.96. Literature suggests that t > 1.96 indicates a significant relationship, and higher path coefficients indicate a strong relationship between latent variables (Zhang 2022). The findings confirm a positive relationship between the efficacy of the grading system and enhanced contractor capabilities and project performance. In other words, improvements in the efficacy of the grading system are associated with enhanced contractor capabilities and improved project performance. However, the path modelling results (β = 0.015, t = 0.215, p = 0.829) show that this relationship is extremely weak and statistically insig- nificant. This suggests that the efficacy of the grading system has a considerably smaller influence on enhanced contractor capabilities and project performance than construction entry requirements and the efficacy of the grading criteria. Testing the potential relationship between construction entry requirements and enhanced contractor capabilities and project performance revealed a posi- tive association between these variables. However, the relationship was statistically insignificant (β = 0.041, t = 0.530, p = 0.596). The Durbin–Watson value was 2.094, which falls within the acceptable range of 1.5 to 2.5, thereby satisfying one of the assumptions for bivariate and multivariate correlation analyses. Based on these results, as presented in Table 5, it can be concluded that the model is accurate and reliable for contractor grading and performance assessment. The study model indicates that the efficacy of the grading and performance evaluation criteria has the strongest positive influence on enhanced contractor capabilities and project performance (β = 0.452), followed by construction entry requirements (β = 0.262) and the efficacy of the grading system (β = 0.076). In contrast, the contractor grading system shows a neg- ative relationship with enhanced contractor capabilities and project performance (β = −0.103). These findings suggest that a more effective contractor grading system is associated with improved contractor capabilities, whereas inefficiencies in the system may have a detrimental effect. The results further indicate that a one-unit increase in the efficacy of the grading Table 5 Results of the regression analysis Independent variables Standardised coefficients t-statistics Sig Collinearity statistics Beta coefficients Tolerance VIF Techno-overload -0.103 -0.966 0.336 0.401 2.496 Techno-complexity 0.262 2.697 0.008 0.485 2.064 Techno-invasion 0.076 1.045 0.298 0.861 1.162 Techno-uncertainty 0.452 4.783 0.000 0.510 1.960 R square 0.343 F 18.804 Significance of F value 0.000 Durbin-Watson 2.094 Percentage (%) 40 35 30 25 20 15 10 5 0 Main criteria Experience Plant and equipment Financial status Past performance Management capability OHS Technical capacity 19.9% 19.9% 3.8% 7.1% 2.3% 9% 38% Figure 8 Main criteria weights