Aims: This study aims to establish a structured analytical framework that integrates macroeconomic variables specifically inflation, expected profit margins, cost components, advance payments, and payment schedules into a unified profitability assessment model. The central objective is to provide a more accurate and uncertainty-informed foundation for financial decision-making, addressing the shortcomings of traditional deterministic cash-flow approaches widely used in the construction industry. Methodology: The research employs Monte Carlo simulation framework specifically tailored to model the stochastic nature of economic indicators affecting construction project cash flows. Probabilistic distributions derived from historical inflation and cost data are used to generate a realistic spectrum of economic scenarios. The methodology incorporates inflation-adjusted cash-flow calculations to preserve the time value of money and embeds break-even analysis to identify profitability thresholds under varying conditions. Findings: The simulation results demonstrate that excluding inflation and expected profit margins during contractual and financial planning leads to systematically distorted profitability estimations. Such omissions increase the likelihood of cash-flow deficits, reduced net margins, and elevated financial risk throughout the project lifecycle. The proposed model captures variability and stress points that deterministic analyses fail to identify, revealing that financial exposure is significantly higher under realistic economic fluctuations. The integration of probabilistic modeling with inflation-adjusted cash-flow analysis enables a more robust understanding of risk patterns and strengthens the contractor’s capacity to manage liquidity and capital allocation. Conclusion: This research offers a comprehensive and methodologically advanced framework for profitability assessment in construction projects, combining break-even analysis with Monte Carlo simulation grounded in empirical economic behavior. The proposed approach enhances the reliability of financial forecasts and provides meaningful guidance for contractors within economically volatile environments. Although its effectiveness depends on forecast quality and computational capacity, the framework marks a substantive improvement over conventional financial evaluation techniques and contributes to more resilient economic planning and decision-making in construction project management.
Ildarabadi et al. (Sat,) studied this question.
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