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 R² 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.

Construction labors play critical roles in executing the project. Therefore, the purpose of this study is to provide and review using partial least square structural equation modeling (PLS-SEM) approach that the skilled and unskilled labor force impact on project performance which has been overlooked in the previous literature in the context of the public construction industry in developing countries, like Pakistan. To achieve the objective of this study, a hypothetical model was developed and empirically examined by using Structural Equation Modeling. Data were gathered through a questionnaire survey method. In total, 400 construction practitioners responded to the questionnaire on behalf of their organization. The results revealed that unskilled labor has a significant negative impact on project performance during the construction phase, whereas the results confirmed that skilled labors have a significant positive impact on project performance in enhancing the success rate of the project in the public construction industry. These results could be used by construction experts to elaborate a broader and rooted view of the labor skills affecting the project performance. The results provide adequate information to policy and decision makers concerning labor skills being a compulsory part of the operational strategy in accelerating the better execution and success of construction projects. The current study adds to the construction project management literature by examining the effect of labor skills on project performance positively or negatively, and the hypothesized model was developed that should be adopted by practitioners to ascertain labor skills for the successful execution of the project.

Public construction infrastructure projects have been recognized as one of the fundamental tools in enhancing community socio-economic conditions for community development. The purpose of this study is to empirically investigate the impacts of socio-economic factors on community development of rural regions. Through a questionnaire survey administrated in Pakistan, public construction practitioners’ views were sought and evaluated. Empirical support for the argument originated from the data collected from 213 respondents in Pakistan’s public construction industry. The questionnaire’s data were evaluated employing the partial least square structural equation modeling (PLS-SEM). The study’s findings showed that economic and social factors influence the community development of rural regions. The result obtained from PLS-SEM proposed a more viable method to realize community development and objectives. The study’s results have offered precious lessons for local authorities, policymakers, and project stakeholders to strengthen the drive for achieving community development goals. Strategies supporting community development in rural regions are indispensable for local community development. This study provides empirical confirmation for the understanding and combining the community development concept; it illuminates absent knowledge about community development, especially in rural regions. This is one of the few studies investigating the influencing dimensions of community development in rural regions. To the authors’ best knowledge, this is the first research article providing empirical evidence of the influencing dimensions of community development in rural regions in a developing country.

Project delays are a large and prevalent problem in the Gilgit-Baltistan construction industry, and delays can distinctly affect project duration, budget, and also community needs. The purpose of this study is to highlight and rank delaying factors in the Annual Development Programme public sector building infrastructure projects and examine them through a relative importance index. A total of 52 delaying factors were identified through a detailed literature review and categorized into eight major groups, and a pilot study with 16 experienced construction experts was conducted. A questionnaire survey was conducted to collect the importance of each factor from public construction experts. In total, 102 respondents participated in the survey. The study determined that difficulties in financing projects by contractors, delays in progress payments, dispute on land usage, improper project feasibility studies, award project to the lowest bid price, extreme weather conditions, inadequate contractor experience, and insufficient data collection and survey before design were among the top eight critical delaying factors. In addition, Spearman’s rank correlation tests revealed that there was no difference in perception between owners and contractors. A comparison of the top five delay factors was done with eight preferred construction industries in Asia to validate the results of this study. The findings are likely to be a solid contribution to the Gilgit-Baltistan construction industry in mitigating future construction delays.