PSI - Issue 64

Rubina Canesi et al. / Procedia Structural Integrity 64 (2024) 1712–1719 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

1715

4

initiative. The larger the projects, such as infrastructure ones, with high construction budgets and long design and construction timelines, the higher the recorded cost overruns (Avotos, 1983; Flyvbjerg et al., 2018; Pehlivan & Öztemir, 2018). Managing cost increases throughout all project life stages involves developing models and strategies capable of analyzing the probabilities and the risk of certain unexpected events occurring (Love et al., 2016). Cost overruns can occur due to various factors such as inaccurate estimation, unforeseen circumstances, changes in project scope, delays, inflation, or unexpected increases in material or labor costs. Several studies focused on potential and highly impact causes on costs overrun, categorizing these potential causes into four primary groups: technical, economic, psychological, and political (Asiedu & Adaku, 2020; Cantarelli et al., 2012; Flyvbjerg et al., 2002; Herrera et al., 2020; Park & Papadopoulou, 2012; Subramani, 2014). The failure to adequately factor in construction costs during the project design phase often leads to significant underestimations, a common pitfall in large-scale endeavors like infrastructure projects. In light of the unpredictable nature of unforeseen circumstances, assessing risk must be approached probabilistically. This entails gauging the likelihood of adverse outcomes deviating from the project's initial baseline and budgetary projections. To address this challenge and allocate risk appropriately between public and private sectors, the National Anti-Corruption Authority (ANAC) has devised a risk management and mitigation framework. In a previous study, we adapted this tool, developed by ANAC, using the risk classification and probability/impact matrix proposed within it. In this previous study, risks with the highest impact and probability of occurrence associated with the construction of a transportation infrastructure in the National territory were identified and assessed (Canesi & Gallo, 2023). Recently, several studies have been conducted on how and why construction costs and cost overruns have been globally impacted by the COVID-19 Pandemic and the war in Ukraine (Alajmani et al., 2023; Canesi, 2022; Canesi & Marella, 2023; Chen et al., 2023; Gabrielli et al., 2023; King et al., 2021; Namous & Al Battah, 2021; Sami Ur Rehman et al., 2022; Sierra, 2022). Considering these studies, the matrix proposed by ANAC, as previously tested, requires a revision to assess the impact that the recent drastic increase in costs may have on the proposed model. This model adaptation can be useful to verify how the recent increased trend of cost can be interpreted and utilized in forecasting future escalation infrastructure projects ’ costs . 3. Materials and Methods In this study, we want to verify the adaptability of the risk matrix proposed by ANAC in light of the increase in construction costs recorded in recent years. ANAC proposed an easily adaptable risk assessment tool for the analysis and monetization of risks. In order to evaluate potential monetary discrepancies that may have been initially estimated during project configuration and design, ANAC has introduced a "risk matrix" tool, which we have previously adopted in a research study. ANAC's tool, recognizing the stochastic nature of unforeseen events, assesses risk in probabilistic terms. We addressed the potential for unfavorable outcomes compared to initial projections by populating the matrix with five classes of occurrence probability and four categories of cost impact. ANAC proposed an assessment matrix which crosses the probability of occurrence of a specific risk with the impact on costs that each risk can have on the overall construction project. This tool has been previously applied to a transport infrastructure project located in the Province of Treviso, known as "State Road No. 51 of Alemagna Vittorio Veneto Variant" (SR51). This project has a significant design history and was partially developed between 2017 and 2019, as outlined in a prior study (Canesi & Gallo, 2023). As a result of the Risk Matrix applied to the aforementioned project, out of the identified 17 Risk Types associated with the infrastructure project, three were classified as "High," four as "Medium," two as "Low," and eight as "Minimum." This classification corresponds to a crossed combination of probability of occurrence and cost impact on the project, identifying "High Risk" as those requiring immediate corrective actions, "Medium Risk" as those needing urgently scheduled corrective actions, "Low Risk" as those necessitating corrective actions in the medium short term, and "Minimum Risk" as those not requiring improvement actions. After identifying the categories and types of risks with a higher potential impact, the respective possible cost increases were estimated, defined as potential cost overruns, according to a Risk Value Assessment Tool, as presented in Table 1. Increase Level ( i ) corresponds to five different clusters, from none to grave. Each one corresponds to a different deviation class (Increase in Value - IV i ), falling within a specified percentage range that determines its impact on estimated costs. The third column calculates the Increased Costs (IC i ), which is the base value increased by the associated percentage (IV i ) for each respective increment type ( i ). In the fourth column, the difference between the IC i and IC i-1 has been calculated,