Abstract:
The construction industry faces significant uncertainties due to fluctuating market conditions, regulatory complexities, and project-specific risks. Traditional capital budgeting tools like Net Present Value (NPV) and Internal Rate of Return (IRR) often fail to account for these uncertainties, leading to suboptimal investment decisions. This study investigates the impact of advanced risk analysis techniques—Monte Carlo Simulation (MCS), Sensitivity Analysis (SA), Risk Registers (PR), Decision Trees (DT), and Real Options Analysis (ROA)—on capital budgeting in construction projects. Risk Registers and Decision Trees had the strongest positive influence. The findings advocate for the adoption of dynamic and structured risk analysis tools in construction financial planning to improve budgeting accuracy, manage uncertainties, and support strategic decision-making. The study offers valuable insights for construction firms aiming to optimize investment outcomes in a high-risk environment.
