Structural Equation Model for Evaluating Factors Affecting Quality of Social Infrastructure Projects

Abstract

The quality of the constructed social infrastructure project has been considered a necessary measure for the sustainability of projects. Studies on factors affecting project quality have used various techniques and methods to explain the relationships between particular variables. Unexpectedly, Structural Equation Modeling (SEM) has acquired very little concern in factors affecting project quality studies. To address this limitation in the body of knowledge, the objective of this study was to apply the SEM approach and build a model that explained and identified the critical factors affecting quality in social infrastructure projects. The authors developed a quantitative approach using smart-PLS version 3.2.7. This study shed light on the views of different experts based on their experience in public construction projects in Pakistan. Particularly, the authors aimed to find out the relationships between construction, stakeholders, materials, design, and external factors, and how these relate to project quality. The findings of this study revealed that the R 2 value of the model was scored at 0.749, which meant that the five exogenous latent constructs collectively explained 74.9% of the variance in project quality. The Goodness-of-Fit of the model was 0.458. The construction related factor was the most important out of the five constructs. This study determined that better planning and monitoring and evaluation should be developed to better address and control the quality defects by decision-makers, project managers as well as contractors. These findings might support practitioners and decision makers to focus on quality related problems that might occur in their current or future projects.

A Perception Study of an Integrated Water System Project in a Water Scarce Community in the Philippines

“…Therefore, this study confirmed that PLS-SEM could be an alternative approach for predicting behavioral intention in C-TAM-TPB models. However, it should be noted that, relatively, PLS-SEM has a great advantage over multiple linear regression in terms of convenience [29], flexibility [20], and other functions [30,31]. This is an initial study for the development of an Integrated Water System in the municipality of Mulanay.…”

“…Further, aside from the assessment of each path coefficient through bootstrapping, in PLS-SEM, the significance of the indirect effects of each variable on endogenous variables can also be verified [30]. Moreover, the behavior of exogenous variables on endogenous variables can also be predicted in PLS-SEM using a blindfolding process [31]. This can serve as a guide to improve the model.…”

“…Moreover, the behavior of exogenous variables on endogenous variables can also be predicted in PLS-SEM using a blindfolding process [31]. This can serve as a guide to improve the model.…”

Social Effects of Economic Crisis: Risk of Exclusion. An Overview of the European Context

“…For our Structural Equation Modelling analysis, the Smart-PLS (v.3.2.7) (GmbH, Boenningstedt, Germany). was the software instrument [57] whose effectiveness for casual analysis is recognized and widely used [58].…”

Development of Balanced Score Card Framework for Performance Evaluation of Airlines

“…Shahid Hussain et al, (2018) applied SEM approach to identify the critical factors affecting quality in social infrastructure projects. The authors developed a quantitative approach using smart-PLS version 3.2.7.…”