Predicting construction duration during the planning phase for public building projects in Uganda.

Abstract

Time overrun is one of the major challenges faced by the construction industry today both nationally and globally. This has partly been attributed to the absence of a scientifically developed mechanism for determining construction project time frames which leave clients setting unachievable time frames for construction projects. Copying construction durations from previous projects without accounting for influencing factors is common. To avoid liquidated damages, time extension costs, and ensure effective planning and budgeting, accurately determining project duration during the planning phase is essential. This study aimed at developing a model to predict construction duration of public building projects during the planning phase. Public buildings have garnered particular attention due to their tendency to experience more significant time overruns when compared to private buildings. These public projects are executed using taxpayer-funded resources and often face stringent budget constraints. As a result, they are subject to heightened public scrutiny to ensure the efficient use of limited resources. In contrast, delays in private building projects primarily impact a smaller group of stakeholders associated with that specific project. Factors that determine construction duration were identified through literature review. These were used in the development of the questionnaire. Based on the collected data, the relative importance of the factors was determined using Relative Importance Index. Linear regression analysis using IBM SPSS Statistics 27 was used to develop a regression model to predict construction duration from the data collected on the most important factors. The study found gross floor area and cost to be the significant determinants of construction duration during the planning phase. It was discovered that an increase in both gross floor area and cost led to a corresponding increase in construction duration, and vice versa. Approximately 90% change in construction duration was attributed to changes in gross floor area and cost. As a result, precise estimation of these factors is essential to obtain an accurate construction duration. The developed model exhibits a strong predictive capacity and remains reliable for forecasting construction durations in the initial planning stages of public building projects in Uganda. As such, it is recommended for adoption to establish construction timelines, mitigating the inherent subjectivity associated with relying solely on estimators' judgments.