Identify and Ranking Cost Overrun Factors in Military Construction Projects using FMEA

Global Journal of Economic and Finance Research Vol. 02(12): 1423-1434, December 2025 Home Page: https://gjefr.com/ e-ISSN: 3050-5348 p-ISSN: 3050-533X DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1423 Identify and Ranking Cost Overrun Factors in Military Construction Projects using FMEA Masoud Ghasem Zadeh1, Morteza Abbasi2*, Jafar G. Kheljani3 1PhD Candidate, Passive Defense Department, Malek Ashtar University of Technology, Tehran, Iran. 2,3 Associated Professor, Management and Industrial Engineering Department, Malek Ashtar University of Technology, Tehran, Iran. KEYWORDS: Cost Overrun, Construction Project, FMEA, Military projects. Corresponding Author: Morteza Abbasi Publication Date: 23 December-2025 DOI: 10.55677/GJEFR/10-2025-Vol02E12 License: This is an open access article under the CC BY 4.0 license: https://creativecommons.org/licenses/by/4.0 ABSTRACT Controlling and preventing cost overruns in defense construction projects remain a core, ongoing challenge for project managers. Due to the strategic significance of these endeavors and the numerous factors that drive cost increases in construction, extensive research has been conducted on this subject. Literature review indicates that the identification of cost overrun factors often relies solely on literature review and expert interviews. This research utilizes the Failure Mode and Effects Analysis (FMEA) technique, treating the identified causes of cost overrun as potential failure events. The identified factors are subsequently ranked using the Risk Priority Number (RPN) index. Finally, these factors are categorized, and corresponding risk response scenarios are proposed for their prevention or control. The resulting ranking clearly indicates that external macroeconomic shocks, specifically General Inflation (RPN=810) and Currency Exchange Volatility (RPN=729), represent the most significant threats due to their high inherent severity and difficulty of detection. This research thus provides a prioritized framework, demonstrating that effective cost management in this sector requires a strategic shift toward contractual and financial engineering to buffer against systemic instability, rather than focusing solely on internal project execution efficiencies. 1. INTRODUCTION The construction sector is foundational to national economies globally, serving as both a major employer and a significant driver of investment. The development of a nation’s infrastructure, which is directly managed by this industry, is a crucial prerequisite for achieving broader economic growth (Ashmita, 2019). Fundamentally, the construction industry operates by organizing and coordinating diverse resources, including personnel, equipment, materials, and capital, within a temporary organizational structure to meet specific targets (Abrar Husen, 2011). Furthermore, the presence of robust infrastructure is known to encourage equitable regional development (Nur Sahid, 2019). Despite this significance, the sector contends with persistent issues that impede its success. Among these challenges, cost overruns represent the most significant obstacle reported across project lifecycles. Addressing this issue requires substantial attention from all stakeholders, as identifying the underlying causes is essential for improving cost efficiency. Prior research investigating factors that influence construction schedules consistently identifies the planning and implementation phases as the dominant source of project delays (Thapanont, 2018, Susanti 2023). The fundamental objective is to enhance the productivity of defense construction projects while actively mitigating all forms of cost overruns. Consequently, the primary concern of project managers is identifying cost overrun factors, ranking them, and proposing prevention/control strategies. Accordingly, this research centers on a systematic approach for identifying the root causes of cost escalation, then employing a robust ranking mechanism to prioritize these causes, and finally, formulating concrete recommendations for proactive prevention and reactionary control measures. Following an initial literature review and factor Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1424 elicitation through expert interviews, this paper applies FMEA to systematically rank the identified factors. This prioritization enables a focused discussion on the most influential variables and outlines strategic managerial interventions. 2. LITERATURE REVIEW Cost overruns represent a pervasive and financially significant challenge in the construction industry, with substantial impacts on project viability, stakeholder satisfaction, and overall economic efficiency. A wide body of research has identified numerous interrelated factors that contribute to these overruns. Early studies highlight technical and planning-related deficiencies as primary drivers. Eri (2003) attributes cost overruns to incomplete design documentation, inaccurate supplier selection, errors in material cost estimation, delays in material delivery, volatile material prices, shifting economic conditions, and the introduction of additional scope or change orders. These issues often stem from inadequate upfront planning and poor risk anticipation during the pre-construction phase. Human resource limitations also play a critical role. Yuanita (2003) observes that substandard supervisory competence— particularly among foremen—and delays in labor mobilization significantly contribute to budget deviations. Labor-related inefficiencies, including low productivity and absenteeism, further exacerbate cost pressures. Equipment management represents another major source of waste. Wisnu (2003) identifies several equipment-related inefficiencies that can escalate costs, including inappropriate investment decisions, excessive rental expenses, mismatched equipment capacity, overutilization, premature equipment obsolescence, inadequate maintenance practices, improper repairs, frequent rework, and a high incidence of breakdowns requiring repair. More recent studies expand the scope of contributing factors to include systemic and institutional challenges. Khanal and Ojha (2020) emphasize the influence of flawed procurement systems and political interference, while Ahwal et al. (2016) point to delayed payments for completed work, weak contract administration, the use of outdated or unsuitable construction methods, ineffective site supervision, poor communication among stakeholders, insufficient project management support, financial instability on the part of the client, regulatory constraints, and a shortage of skilled professionals. Further corroborating these findings, Khanal and Ojha (2020), Ahwal et al. (2016), and Arjroody et al. (2023) collectively identify recurring operational and financial stressors including elevated labor costs, excessive overtime, labor absenteeism, project schedule delays, late payments by owners, and owners’ financial constraints, as key contributors to cost overruns Recent studies continue to expand the understanding of the multifaceted causes of cost overruns in construction projects. Arjroody et al. (2023) identify a broad range of material, labor, equipment, and finance related factors. These include frequent theft of construction materials, volatile and rising material prices, inappropriate material selection, improper storage leading to damage, inaccurate forecasting of market trends, and unplanned changes in required material quantities. On the labor front, the study notes that wage fluctuations, labor shortages, substandard workmanship, low productivity, and the misallocation of personnel significantly contribute to budget deviations. Equipment-related issues, such as high mobilization and demobilization expenses, poor organization of equipment storage, delays in equipment delivery, and the selection of unsuitable heavy machinery, further compound cost inefficiencies. Additionally, weak field-level cost control practices, delayed payment mechanisms, high interest rates on financing, insufficient financial capacity, and elevated equipment acquisition or rental costs are cited as critical financial drivers of overruns. Complementing these findings, Abdelalim et al. (2025) emphasize deficiencies in the pre-construction phase as root causes of cost escalation. Specifically, they highlight inadequate initial budgeting, poor planning of material costs, inaccuracies in detailed quantity take-offs for both labor and materials, and the failure to account for inflation-driven increases in material prices. Khanal and Ojha (2020) offer a more holistic perspective, framing cost overruns within a broader project ecosystem. They associate overruns with interrelated dimensions such as project implementation timelines, socio-cultural contexts, financial management, labor dynamics, accuracy of cost estimates, quality of planning documentation, organizational structure and staffing, on-site coordination and working relationships, field logistics, material availability, and adherence to the project schedule. Collectively, these studies underscore that cost overruns are rarely attributable to a single cause; rather, they emerge from a confluence of planning gaps, operational inefficiencies, market volatility, and institutional or contextual constraints. Effective mitigation thus requires integrated strategies that address technical, human, financial, and managerial dimensions throughout the project lifecycle. This study uses quantitative methods to analyze the factors that cause cost overruns on construction projects from the perspective of contractors and consultants. In general, this study is divided into 3 (Three) steps: Step (1) Identify critical factors driving cost overruns in defense construction by synthesizing findings from the literature, expert interviews, and empirical case studies, using Delphi process. Step (2) A structured questionnaire, based on the FMEA methodology, was administered to a panel of 30 subject matter experts, each possessing over several years of relevant experience in construction projects. Step (3) The most critical cost overrun factors in defense construction projects will be identified, and corresponding response scenarios will be developed for their mitigation. The critical factors driving cost overruns in defense construction were synthesized from the literature review, expert interviews, and empirical case studies. These factors were then systematically organized into six distinct categories, as presented in Table 1. Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1425 Table 1. Critical factors causing cost overrun No Category Variable Causes of Cost Overrun Sources 1 External Factors Rule changes Abdelalim et al.(2025) 2 Socialization of land acquisition Eliasson(2025), Abdelalim et al.(2025) 3 Land acquisition issues Tayyab et al.(2023) 4 Public awareness about toll roads Eliasson(2025), Abdelalim et al.(2025) 5 Unclear legal basis Eliasson(2025), Abdelalim et al.(2025) 6 Soil condition Abdelalim et al (2025) 7 Risks of natural change Tayyab et al.(2023) 8 Labor strike Abdelalim et al (2025) 9 Political intervention Abdelalim et al (2025) 10 Conflict of ministries Abdelalim et al (2025) 11 Project location Abdelalim et al (2025) 12 Natural disasters Tayyab et al.(2023) 13 Bad weather outside forecast Tayyab et al.(2023) 14 Material Factors Theft of materials Zhu et al.(2021), Belay&Torp (2023) 15 An increase in material prices Zhu et al.(2021), Belay&Torp (2023) 16 Material selection Zhu et al.(2021), Belay&Torp (2023) 17 Errors in organizing material storage Zhu et al.(2021), Belay&Torp (2023) 18 Material quantity change Abdelalim et al (2025) 19 Less precise in predicting the market material prices Susanti (2023) 20 Incomplete image design Susanti (2023) 21 Less precise in determining the supplier Susanti (2023) 22 Errors in the estimation of material costs Susanti (2023) 23 Delay in material delivery Kermanshachi (2023) 24 Project implementation delay Khanal&Ojha(2020), Ahwal et al.(2016), Arjroody et al.(2023) 25 The presence of additional work Susanti (2023) 26 Material prices fluctuate Susanti (2023) 27 Poor material procurement Susanti (2023) 28 Specification changes Abdelalim et al (2025) 29 Labor Factors Fluctuations in labor wages Olaniran et al.(2015), Amini et al.(2023), Ankrah et al.(2023) 30 Labor shortage Olaniran et al.(2015), Amini et al.(2023), Ankrah et al.(2023) 31 Poor Quality of Labor Olaniran et al.(2015), Amini et al.(2023), Ankrah et al.(2023) 32 Labor productivity Olaniran et al.(2015), Amini et al.(2023), Ankrah et al.(2023) 33 Less appropriate in the placement of personnel Olaniran et al.(2015), Amini et al.(2023), Ankrah et al.(2023) 34 Planning and making schedules Yuanita.S (2003) 35 High cost of work Khanal&Ojha(2020), Ahwal et al.(2016), Arjroody et al.(2023) 36 Labor productivity Khanal&Ojha(2020), Ahwal et al.(2016), Arjroody et al.(2023) 37 Poor quality Foreman Yuanita.S (2003) 38 Delay in the Provision of Labor Yuanita.S (2003) 39 Heavy overtime / Overtime Kermanshachi (2023), Khanal&Ojha(2020), Ahwal et al.(2016), Arjroody et al.(2023) 40 Limited human resources Adepu et al.(2024), Ahwal et al.(2016), Arjroody et al.(2023) 41 Labor absenteeism Adepu et al.(2024) 42 High price/rental of equipment Zhu et al.(2021), Belay&Torp (2023) Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1426 No Category Variable Causes of Cost Overrun Sources 43 Equipment Factors High equipment mobilization/demobilization costs Zhu et al.(2021), Belay&Torp (2023) 44 Late delivery of equipment Zhu et al.(2021), Belay&Torp (2023), Kermanshachi (2023) 45 Machine selection Zhu et al.(2021), Belay&Torp (2023) 46 Errors in organizing equipment storage Zhu et al.(2021), Belay&Torp (2023) 47 Errors in equipment investment Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 48 The high cost of rent Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 49 Tool capacity does not match Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 50 The tool works too heavy Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 51 The low economic life of the equipment Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 52 Poor tool maintenance Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 53 Repair of unsuitable tools Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 54 Change of job/rework Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 55 Limited funding sources Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 56 Equipment availability Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 57 High frequency of tool repair Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 58 Subcontract or Factors Less experienced contractors Youssefi&Celik (2023) 59 Unprofitable contracts Youssefi&Celik (2023) 60 Poor supervision of construction projects Youssefi&Celik (2023) 61 Errors in predicting field conditions Youssefi&Celik (2023) 62 Low productivity Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 63 Lack of contractor experience Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 64 Lack of coordination (contractors) Isfahani et al.(2023), Khanal&Ojha(2020), Ahwal et al.(2016) 65 Slow payment for completed work Kansal&Agarwal (2022), Ma et al.(2024) 66 Poor contract management Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 67 Outdated or unsuitable construction methods Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 68 Poor site management and supervision Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 69 Slow flow of information between parties Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 70 Poor project management help Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 71 Owner's financial difficulties Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 72 Obstacles from the government Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 73 Lack of expert power Kansal&Agarwal (2022), Ma et al.(2024), Abdelalim et al (2025) 74 Financial difficulties of the contractor Hong Anh Vu(2016) 75 Finance Factors Inflation Abdelalim et al (2025) 76 Currency exchange rate changes Abdelalim et al (2025) 77 Changes in economic conditions Susanti (2023) 78 Tax increase Abdelalim et al (2025) 79 Poor cost control in the field Zhu et al.(2021), Belay&Torp (2023) 80 Untimely payment method Zhu et al.(2021), Belay&Torp (2023) 81 High-interest rates on bank loans Zhu et al.(2021), Belay&Torp (2023) 82 Lack of funding/financial capability Zhu et al.(2021), Belay&Torp (2023) 83 Poor financial control Khanal&Ojha(2020), Ahwal et al.(2016), Arjroody et al.(2023) 84 late payment by the owner Khanal&Ojha(2020), Ahwal et al.(2016), Arjroody et al.(2023) 85 financial difficulties of the owner Khanal&Ojha(2020), Ahwal et al.(2016), Arjroody et al.(2023) Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1427 3. RESEARCH METHODOLOGY FMEA is an analytical technique that tries to identify and rank the potential risks, in the desired risk-assessment range, and find their related causes and effects. It is a method that predicts breakdowns, defects, and deficiencies probable in the design of a product or in its production process; hence, it prevents such problems and reduces related costs. First, it was officially introduced in the US in the late 1940s for military purposes, then Ford Co. introduced it in the automobile industry in the late 1970s and today it is widely used in various industries. The steps of this technique are shown in Figure 1. Figure 1. Hierarchy in FMEA method (AIAG, 2008) RPN (risk priority number) is a product of S (severity), O (occurrence probability) and D (detection probability). RPN= S * O * D Eq. (1) Now, risks are ranked based on their priority numbers limited by the FMEA system (AIAG, 2008). Severity, occurrence probability and detection probability of risks are determined as following sections. 3.1. Risk Severity Risk severity means its "effect" and its quantitative indices are scaled from 1 to 10 (Table 2). 3.2. Occurrence Probability Occurrence probability determines the frequency of the cause/mechanism of a potential risk and Table 3 helps specify this probability on a 1-10 scale. Reviewing past records/documents, control processes, standards, work rules/requirements and how they are used can help reach this number (AIAG, 2008). Table 2. Risk severity Rank Severity 10 No alarming 9 Alarming 8 Very high 7 High 6 Average 5 Low 4 Very low 3 Low 2 Almost none 1 None Checking control processes Collecting data Identifying potential risks Examining effects of each risk Determining causes of each risk Finding risk severity Checking exportability of a risk Calculating RPN Finding probability rate Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1428 Table 3. Risk occurrence probability Rank Occurrence probability 10 9 Quite high – almost unavoidable 8 7 High - repetitive risks 6 5 4 Average 3 2 Low 1 Improbable - unlikely 3.3. Detection Probability Risk detection probability rate (Table 4) helps detect risks before they occur and examining the standards control, processes requirements / rules and how they are applied can highly help reach this number (AIAG, 2008). Table 4. Risk detection probability Rank Detectability 10 Absolutely none 9 Very low 8 Low 7 Very low 6 Low 5 Average 4 Relatively high 3 High 2 very high 1 Almost certain 4. FUNDINGS From the results of descriptive analysis to obtain the dominant factor in SPSS program statistics. get the results in the form of Severity, Occurrence, Detection and RPN in Table 5. Table 5. Result in FMEA Analysis of Cost Overrun Factors Factor Category Factor Severity (S) (Est.) Occurrence (O) (Est.) Detection (D) (Est.) RPN (S×O×D) Rank Factor External Rule changes 8 9 8 576 3 Socialization of land acquisition 8 7 6 336 14 Land acquisition issues 8 8 7 448 9 Public awareness about toll roads 5 4 5 100 43 Unclear legal basis 8 8 8 512 6 Soil condition 7 6 3 126 37 Risks of natural change 7 3 3 63 47 Labor strike 8 3 4 96 44 Political intervention 9 8 9 648 1 Conflict of ministries 9 7 9 567 4 Project location 6 5 4 120 39 Natural disasters 9 2 6 108 41 Bad weather outside forecast 6 4 5 120 38 Factor Material Theft of materials 7 5 5 175 34 An increase in material prices 9 10 9 810 2 Material selection 6 4 5 120 36 Errors in organizing material storage 5 6 4 120 35 Material quantity change 7 5 6 210 29 Less precise in predicting the market 8 9 8 576 2 Incomplete image design 8 6 7 336 15 Less precise in determining the supplier 7 7 7 343 12 Errors in the estimation of material costs 7 8 6 336 16 Delay in material delivery 8 8 7 448 8 Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1429 Factor Category Factor Severity (S) (Est.) Occurrence (O) (Est.) Detection (D) (Est.) RPN (S×O×D) Rank Project implementation delay 9 7 7 441 10 The presence of additional work 8 7 6 336 17 Material prices fluctuate 9 10 9 810 2 Poor material procurement 7 7 7 343 11 Specification changes 8 6 7 336 18 Factor Labor Fluctuations in labor wages 8 9 8 576 5 Labor shortage 8 7 7 392 19 Poor Quality of Labor 7 6 5 210 28 Labor productivity 6 7 5 210 27 Less appropriate in the placement of personnel 6 5 5 150 32 Planning and making schedules 7 6 6 252 25 High cost of work 8 8 7 448 7 Labor productivity (Duplicate) 6 7 5 210 26 Poor quality Foreman 7 5 6 210 30 Delay in the Provision of Labor 7 6 7 294 22 Heavy overtime / Overtime 7 6 5 210 31 Limited human resources 7 6 6 252 24 Labor absenteeism 5 5 4 100 42 Factor Equipment High price/rental of equipment 8 8 7 448 10 High equipment mobilization/demobilization costs 7 7 6 294 21 Late delivery of equipment 7 7 7 343 13 Machine selection 6 5 5 150 33 Errors in organizing equipment storage 5 5 4 100 45 Errors in equipment investment 7 5 6 210 28 The high cost of rent (Duplicate) 8 8 7 448 11 Tool capacity does not match 7 5 6 210 28 The tool works too heavy 6 4 5 120 40 The low economic life of the equipment 7 5 6 210 28 Poor tool maintenance 7 6 5 210 28 Repair of unsuitable tools 7 5 6 210 28 Change of job/rework 8 7 7 392 20 Limited funding sources 9 7 8 504 7 Equipment availability 7 5 5 175 34 High frequency of tool repair 7 6 5 210 28 Factor Subcontractor Less experienced contractors 8 7 7 392 23 Unprofitable contracts 8 8 7 448 12 Poor supervision of construction projects 7 8 7 392 23 Errors in predicting field conditions 7 7 6 294 20 Low productivity 7 7 6 294 20 Lack of contractor experience 8 7 7 392 23 Lack of coordination (contractors) 7 7 6 294 20 Slow payment for completed work 8 6 7 336 19 Poor contract management 7 7 8 392 23 Outdated or unsuitable construction methods 6 6 5 180 33 Poor site management and supervision 8 7 7 392 23 Slow flow of information between parties 7 7 6 294 20 Poor project management help 8 7 7 392 23 Owner’s financial difficulties 9 6 8 432 13 Obstacles from the government 9 8 9 648 1 Lack of expert power 7 6 5 210 28 Financial difficulties of the contractor 9 7 8 504 8 Factor Finance Inflation 9 10 9 810 2 Currency exchange rate changes 9 9 9 729 3 Changes in economic conditions 9 9 8 648 5 Tax increase 8 6 7 336 15 Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1430 Factor Category Factor Severity (S) (Est.) Occurrence (O) (Est.) Detection (D) (Est.) RPN (S×O×D) Rank Poor cost control in the field 7 7 5 245 26 Untimely payment method 7 6 6 252 25 High-interest rates on bank loans 8 7 7 392 23 Lack of funding/financial capability 9 7 8 504 7 Poor financial control 7 6 5 210 28 late payment by the owner 8 7 7 392 23 financial difficulties of the owner 9 6 8 432 13 Based on the high-risk assumptions for military construction projects, the factors that require the most immediate attention (highest estimated RPN) are selected and categorized as Table 6. Table 6. Rank of Cost Overrun Factors using FMEA Analysis Rank (by Avg. RPN) Categorized Risk Area Contributing Factors (Original) Severity (S) Occurrence (O) Detection (D) RPN 1 General Inflation and Material Price Escalation Inflation 9 10 9 810 1 An increase in material prices; Material prices fluctuate 9 10 9 810 2 Currency Exchange Volatility Currency exchange rate changes 9 9 9 729 3 Governmental/Political Interference Political intervention; Conflict of ministries 9/9 8/7 9/9 648 / 567 4 Subcontractor Government Obstacles Obstacles from the government (Subcontractor) 9 8 9 648 5 Regulatory & Rule Changes Rule changes 8 9 8 576 Labor Wage Fluctuation Fluctuations in labor wages 8 9 8 576 Material Market Uncertainty Less precise in predicting the market (Material) 8 9 8 576 6 Subcontractor Financial Instability Financial difficulties of the contractor 9 7 8 504 7 Legal/Contractual Ambiguity Unclear legal basis 8 8 8 512 8 Owner/Client Financial Risk Owner’s financial difficulties (Combined) 9 6 8 432 9 Project Timeline Delays Project implementation delay 9 7 7 441 10 High Unit Cost of Work High cost of work (Labor) 8 8 7 448 Unprofitable Subcontracts Unprofitable contracts 8 8 7 448 11 Equipment Cost/Rental High price/rental of equipment; The high cost of rent 8 8 7 448 12 Material Delivery Delays Delay in material delivery 8 8 7 448 13 Land Acquisition Issues Land acquisition issues 8 8 7 448 The primary focus for mitigation efforts must be on Economic Risk Mitigation (Rank 1 & 2) through hedging strategies, robust escalation clauses in contracts, and securing long-term material pricing agreements where possible. The secondary focus should be on Government Interface and Subcontractor Management (Rank 3, 4, 6). Since the detection scores (D) for the top risks are generally high (meaning they are hard to detect once started), proactive risk monitoring, contingency planning, and robust contractual vetting processes are essential controls to drive down the RPNscores in future iterations. Using expert consultation, proposed responses targeting the highest-priority cost-increasing factors were suggested. The top recommendations are presented in Table 7. These proposals are segregated into their respective columns based on whether they primarily improve Severity (S), Occurrence (O), or Detectability (D). Morteza Abbasi (2025), Global Journal of Economic and Finance Research 02(12): 1423-1434 DOI URL:https://doi.org/10.55677/GJEFR/10-2025-Vol02E12 pg. 1431 Risk responses can adhere to one of four general strategies: 1. Risk Acceptance, 2. Risk Mitigation, 3. Risk Transfer, or 4. Risk Avoidance. Project Management Institute (2021) In this table, the impact of each action on RPNreduction is calculated as a percentage, the required resources are quantified on a 1-to-9 Likert scale, and the desirability rating (or Adjusted Efficiency Index, AEI) for each response scenario is calculated by dividing the RPNimprovement percentage by the required resources and normalizing the result to a scale of 1 to 100." Table 7. Proposed Actions to Cost Overrun Factors and their Adjusted Efficiency Index (AEI) Rank Risk Category Action for Severity ( S ) (Resources , RPN Improvement %, AEI) Action for Occurrence ( O ) (Resources , RPN Improvement %, AEI) Action for Detection ( D ) (Resources , RPN Improvement %, AEI) 1 General Inflation (RPN = 810) Implement an Escalation Clause in the contract for inflation rate adjustment. 7, 10%, 14.28 Negotiate fixed exchange rates for predictable international cost components. 8, 10%, 12.5 Launch a weekly dashboard monitoring official inflation indices and contractor inflation forecasts. 7, 5%, 5.0 Material Price Increase (RPN =810) Set a Price Cap for key materials within contracts. 8, 15%, 18.75 Secure long-term guaranteed purchase agreements with strategic suppliers. 9, 20%, 22.22 Establish a Buffer Stock for critical materials. 8, 10%, 12.5 2 Exchange Rate Volatility (RPN =729) Transfer volatility risk via Futures/Forwards contracts or insurance. 8, 12%, 15.0 Set a fixed reference exchange rate for international payment calculations. 7, 15%, 21.42 Daily reporting on exchange rate fluctuations and their impact on project cash flow. 8, 3%, 3.75 3 Political/Government Intervention (RPN ≈600) Form a high-authority stakeholder management team for immediate issue resolution. 9, 15%, 16.66 Designate a formal, fixed communication channel with key decision-making bodies. 9, 20%, 22.22 Conduct regular quarterly meetings with senior officials for strategic alignment. 9, 5%, 5.55 4 Contractor Governmental Barriers (RPN =648) Guarantee direct payment to subcontractors if the Employer causes delays. 6, 10%, 16.66 Develop a comprehensive checklist for permit prerequisites before work commencement. 6, 15%, 25.0 Assign a dedicated expert to exclusively track permit files within government agencies. 6, 5%, 8.33 5 Regulation Change (RPN =576) Reduce the scope of work heavily impacted by unstable regulations (Partial Avoidance). 4, 10%, 25.0 Actively participate in standards drafting committees to anticipate future changes. 4, 10%, 25.0 Conduct periodic (monthly) legal audits by a specialized consultant on new legislation. 4, 5%, 12.5 Labor Wage Fluctuation (RPN =576) Utilize multi-skilled labor and high trainability (reducing reliance on expensive specialists). 5, 5%, 10.0 Sign labor supply contracts with a clearly defined minimum annual increase. 5, 10%, 20.0 Create an internal index to track the average regional wage rate. 5, 5%, 10.0 6 Contractor Financial Instability (RPN =504) Require strong bank guarantees or use contractor receivables insurance. 7, 15%, 21.42 Re-evaluate the financial health of key contractors after every payment milestone. 7, 20%, 28.57 Implement a contractor financial rating system with quarterly updates. 7, 10%, 14.28