Modeling the Impact of Delay Causal Factors Using PLS-SEM Approach in the Context of Highway Projects in India

This paper addresses the core problems of modeling delay causal factors, their interaction effects, and assessments using the structural equation modeling approach. The research forms part of a larger study aimed to develop a delay management framework for handling delays in highway projects in India. A total of 32 delay causal factors (identified from literature review) were part of the questionnaire survey and analysis. These were grouped into five categories, namely client-related (six factors), contractor-related (seven factors), finance-related (five factors), site-related (nine factors), and quality-related (five factors). PLS-SEM approach was used in the study to model the delay causal factors. A measurement model and a structural model were developed and validated as per the PLS-SEM procedure using SmartPLS-3 software. The results from the analysis revealed that site-related problems are the most significant category contributing to a major portion of project delay. The top three variables under this category were poor survey data/investigations, excessive variation of quantities, and obstruction to site work. The second important category contributing to a significant portion of delay was contractor-related category followed by the client-related category and finance-related category. It was found that the impact of the client-related category and finance-related category was higher if the site-related category was present at the same time. Also, the impact of the finance-related categoryincreased if the quality-related category was present at the same time. The contractor-related category alone had a significant impact on project delay and its effect appeared to relatively lessen when client-related and finance-related categories were present in the project. The presence of multiple categories of delay causal factorsat the same time will greatly add to project delay. The study greatly contributes to filling the gap in understanding the impact as well as interrelationships of delay causal factors on project duration. The study will prove to be helpful for project managers and construction managers in targeting their actions for ensuring project completion with a minimum amount of delay.