A Study of Identifying Significant Variables of Delays in Road Construction Via Structural Equation Modelling (SEM)

Abstract

Delays have always been a major concern in road construction projects throughout the world, with significant financial and social impacts for stakeholders, and the occurrence of schedule delays has a serious impact on project investment, efficiency, cost, and reputation. Libya is one of the countries faces all these delay issues. This study explored variables of delays in road construction via Structural Equation modelling SEM. Drawing upon an earlier studies, combined with interviews of road experts. Confirmatory factor analysis CFA was applied to extract significant variables based on the questionnaire results to verify the relationships between the significant variables [8 Factors and 3 Effects] identified in road construction. Eleven variables were found to have significant impacts on delays in road construction. The results of the goodness of fit [GOF] showed that chi square is significant at 0.000 levels. Overall, Based on the CFI, TLI, and IFI indices with values more than the cut off value of 0.9 the model had good fit of data. Further. The root-mean-square error of approximation [RMSEA] was 0.033 which was within the perfect fit range. Additionally. The Relative CMIN/df [1.276] was less than 5 showed the good fit of the model and it was found that the unstandardized regression weights were all significant by the critical ratio test [> ±1.96, P < 0.001]. So the study has shown that CFA can quantify comprehensive relationships among a broad range of variables and contribute to resolving problems commonly experienced in the road construction industry.