Civil Engineering Standard Measurement Method Adoption Using a Structural Equation Modelling Approach

Abstract

The adoption of a standardized technique of measuring in civil construction projects is influenced both by the drivers and the strategies used, particularly in emerging nations such as Malaysia. So, the authors of this study used structural equation modeling and the PLS-SEM technique to inquire into the connection between the driver and strategy elements of the adoption. Quantity surveyors at quantity surveying consultancy companies using the standard measurement technique were polled using a questionnaire. Using the PLS-SEM technique provided by the SmartPLS 3 software, a hierarchical model was created to determine the components and their impacts on the adoption of the measuring method. The results indicated that all classes considerably influence the adoption of the standard technique of assessment, but the barrier factors had the most impact. The adoption of a standardized technique of measuring was significantly impacted by the driver and strategy elements. The coefficient of determination (R-squared value) of 0.400 indicates that the dependent variable(s) can be explained by the predictor variable(s) in the model. Moreover, Q2 is significantly different from zero, suggesting that endogenous latent components may be predicted by the conceptual model. Because of its high explanatory power, the created model has given a goodness-of-fit (GoF) index of 0.214. This means that the model adequately represents the link between the variables that affect measuring technique adoption and the effects of these factors. The first stage in determining what motivates people to utilize the most up-to-date standardized measurement approach in civil engineering construction projects is to develop a research model of the variables and to explain the connection between the driver and strategy factors on standard adoption.

Investigating the mediating role of self-efficacy between digital leadership capability, intercultural competence, and employability among working undergraduates

“…Recent studies have emphasized the importance of R 2 in assessing the explanatory power of the model and the individual predictors (Muzafar et al, 2023) and highlighted the significance of the R 2 value as a critical metric in PLS-SEM for evaluating the strength of the structural model. Additionally, Dzin and Lay (2021) emphasized the relevance of R 2 in assessing the validity and reliability of adapted self-efficacy scales using the PLS-SEM approach, further underlining the importance of R 2 in structural model assessment.…”