An Assessment of the Causes of Schedule and Cost Overruns in Megaprojects using a Z-BWM-MARCOS Integrated Method

Megaprojects are defined as complex and large-scale investments, and their development and construction take many years. Schedule and cost overruns are among the most common challenges in megaprojects worldwide. Exceeding planned budgets and schedules are key factors contributing to the failure of many megaprojects. The aim of this research is to provide an integrated framework for evaluating the causes of schedule and cost overruns in megaprojects.
In this research, for the first time, an integrated approach combining the Failure Mode and Effects Analysis (FMEA) method with the Best-Worst Method (BWM) and MARCOS, developed based on Z-number theory, has been used in three phases to analyze the causes of schedule and cost overruns in megaprojects. In the first phase, based on the literature, the causes and risks are identified using the FMEA method, and the factors determining the Risk Priority Number (RPN) are quantified. In the second phase, using the Z-BWM method, the weights of the criteria are calculated. In the third phase, based on the outputs of the previous phases, the causes are prioritized using the Z-MARCOS method. In addition to assigning different weights to the criteria and considering uncertainty, reliability is also incorporated in this approach through the theory of Z-numbers.
This study presents a novel methodology for assessing the schedule and cost overruns causes in megaprojects, utilizing the Z-BWM-MARCOS method to evaluate and prioritize 17 identified causes. The findings indicate that poor planning and scheduling, inadequate performance design, and a weak supplier network are the primary contributors to these overruns. To validate the proposed methodology, its results were compared with conventional methods, including FMEA, Fuzzy MARCOS, and Z-MOORA. The FMEA method exhibited significant shortcomings, notably, its failure to account for quality grades and conditions of uncertainty, which resulted in incomplete prioritization of failure causes. This limitation led to confusion among decision-makers regarding failure-related decisions. Similarly, while Fuzzy MARCOS addressed uncertainty, it still fell short in providing complete prioritization. In contrast, the Z-MOORA and Z-MARCOS methods effectively overcame these limitations by leveraging the advantages of Z-number theory, which incorporates both reliability and uncertainty. The implementation of the proposed approach demonstrated a strong correlation of 0.909 with the results of the Z-MOORA method, underscoring its effectiveness in delivering comprehensive rankings of causes.
Megaprojects are highly susceptible to significant cost overruns and schedule delays, posing major challenges for project management. The results of this study demonstrate the capability and superiority of the proposed approach compared to traditional methods such as FMEA and Fuzzy MARCOS in identifying the primary causes of cost and schedule overruns in megaprojects.