Developing a Construction Delay Prediction Model as a Delay-Avoidance Strategy for Public Construction Projects

Abstract

Delays in construction projects result in financial losses, project mismanagement, and conflicts between stakeholders. Although previous research has identified general factors contributing to delays, many studies primarily relied on survey-based data. The absence of data-driven insights from real-world cases limits the practical application of these findings. Additionally, only a few studies have rigorously examined the relationship between delays and increased project costs. This study addresses this gap by incorporating actual project data and offering a predictive tool for estimating delays and associated costs. A mixed-methods approach was adopted, combining quantitative and qualitative data from 32 public construction projects. Regression analysis was used to identify key delay factors, to develop and validate a delay prediction model, which estimates delay times based on specific project characteristics. The study also explored how integrating this model into project planning and contracts can reduce the impact of delays. The findings provide an early estimation of potential delays, enabling more efficient resource allocation and reducing the risk of budget overruns. This study not only advances academic understanding of construction delays but also delivers practical strategies for enhancing public project performance.