In the ever-evolving landscape of construction, accurate cost estimation remains a cornerstone of successful project management. However, the early stages of building construction projects are often plagued by uncertainty, with limited data making preliminary cost estimates challenging. This is particularly true in regions like Iraq, where infrastructure development is crucial for economic growth. A groundbreaking study led by Hassanean S. H. Jassim, a researcher at the Faculty of Civil Engineering, College of Engineering, University of Babylon, Hilla, Iraq, aims to change this narrative.
Jassim’s research, published in ‘Frontiers in Built Environment’ (which translates to ‘Frontiers in the Built Environment’), introduces an innovative mathematical model designed to enhance the accuracy of preliminary cost estimations in building construction projects. The model leverages a support vector machine (SVM) to integrate various factors from both historical and new projects, providing a more comprehensive and reliable cost forecast.
The model considers several key factors, including total floor area, construction duration, number of floors, average floor height, location index, project quality standards, project complexity, and facilities provision. “By incorporating these factors, we can better predict the costs associated with a new project, even in the early planning stages,” Jassim explains. This approach not only improves cost estimation but also helps stakeholders evaluate the feasibility of a project more effectively.
One of the standout features of Jassim’s model is its ability to account for inflation rates, a critical aspect often overlooked in preliminary cost estimations. By integrating an inflation rate impact scenario, the model can anticipate future economic effects on building costs, ensuring that cost estimates remain relevant over time. “Inflation is a significant factor that can drastically alter project costs,” Jassim notes. “Our model addresses this by providing a more dynamic and adaptable cost estimation process.”
The research highlights that building area, average floor height, and the number of floors are the dominant factors influencing cost variations between similar projects over different periods. This insight is invaluable for decision-makers, enabling them to plan alternative options and make informed decisions within the project’s constraints.
The implications of this research are far-reaching. For the construction industry, particularly in regions undergoing rapid development, accurate preliminary cost estimations can lead to more efficient resource allocation and better project outcomes. This, in turn, can drive economic growth and infrastructure development, benefiting both the construction sector and the broader economy.
As the construction industry continues to evolve, driven by technological advancements and increasing demand for sustainable practices, Jassim’s model offers a timely solution to a long-standing challenge. By providing a more accurate and adaptable cost estimation tool, this research has the potential to shape future developments in the field, paving the way for more efficient and effective building construction projects.
