Forecasting and assessing project costs, considering internal and external risks based on the design of the integrated model
Articles in Press, Accepted Manuscript, Available Online from 19 July 2026
A. A. Kamalizadeh, M. Ravanshadnia, M. Khanzadi
Abstract BACKGROUND AND OBJECTIVES: In massive construction and civil engineering projects, project financing is of particular importance. This is because the majority of problems arising in construction projects, which lead to prolonged durations and even the loss of the project's economic justification, stem from disruptions in financing. One of the most significant causes of this is the failure to identify and forecast risks properly and to prioritize them based on their individual impact on project costs. METHODS: In this research, after reviewing methods and studying the internal and external risks of projects, as well as examining cost estimation methods and selecting the most appropriate one, the influencing factors were first gathered using a questionnaire. The consistency of this data was then measured using Cronbach's alpha coefficient. Subsequently, the risks were prioritized using the DEMATEL method, and their impact and probability of occurrence were surveyed. Finally, the probability of occurrence and the impact of each risk were estimated as a probability density function, and the problem was simulated using the Monte Carlo method. FINDINGS: In a Monte Carlo simulation, risk analysis is performed by constructing models of potential outcomes, substituting a range of values from probability distributions for every factor that has inherent uncertainty. It then recalculates the results repeatedly, each time using a different set of random values from the probability distributions. Depending on the number of uncertainties and their specified ranges, it can perform thousands or tens of thousands of recalculations before completing, thereby producing distributions of possible outcome values. CONCLUSION: For this purpose, MATLAB software was used to simulate the Monte Carlo method for analyzing this research problem, to obtain the mean impact of the 7 prioritized risks. The impact of these 7 risks on the objective function was assessed based on the frequency of risk occurrence, the probability of occurrence during construction, and the range of their impact on the project cost. The probability density functions for each risk and the distribution functions for the impact ranges of each risk were derived based on the sample data collected via the questionnaire.