Mitigation of Time Overruns in Construction Projects in Afghanistan by Applying Risk Management

Abstract

Construction industry in Afghanistan is crucial for economic and social advancement, particularly after years of instability. However, the construction industry has been already confronting huge time overruns, affecting all stakeholders. This research aims to identify the various risks associated with time overruns in construction projects within Afghanistan and to explore effective risk management strategies to mitigate these challenges. To address time overruns, this study employed Monte Carlo simulations using RiskPert to assess time overruns by combining expert judgment with historical data. This study assesses construction project historical data from 2002 to 2023, emphasizing the political and economic circumstances of that period using a literature review and an examination of 74 construction project reports, in addition to semi-structured interviews with industry experts to determine schedule-related risks and their frequent causes. This research found 29 distinct risk indicators classified into eight categories, facilitating a methodical integration of risks into the simulation model. The Monte Carlo Simulations conducted with @RISK software (version 8.0, Palisade Corporation, New York, NY, USA) assessed the influence of these risks on project performance over 10,000 iterations, demonstrating a robust association with actual project results and a standard deviation of ±15% in durations. Time overruns in projects are linked to socio-political, organizational, and financial risks. The findings emphasize the significance of these factors on project outcomes and recommend strategies for their mitigation to improve decision-making and ensure project management success.

1. Introduction

The construction industry presents lower productivity and efficiency compared to other sectors, demanding improved management measures to boost competitiveness [1]. Traditional methods frequently prove insufficient due to the inherent uncertainties and risks associated with construction projects. Effective risk management is essential for identifying and mitigating potential risk, especially in complex projects, and requires a systematic strategy comprising planning, identification, analysis, response formulation, execution, and monitoring of risks [2,3]. The Project Management Institute highlights the significance of risk management for effective project execution [4,5].

Mitigating time overruns in construction projects through efficient risk management requires the comprehension and management of both known and unknown risks. Known risks can be managed by planning and preparation, however unknown risks need the creation of a risk reserve due to their natural uncertainty. Risk management strategies in the construction industry include mitigation, control, transfer, distribution, and acknowledgement, which are essential for handling risks that could affect project schedules, budgets, and quality. The construction industry encounters elevated risks due to extended project timelines, complex processes, and budget constraints, frequently resulting in project overruns and negative impacts on stakeholders [4]. A systematic approach to risk management enables the identification and prioritizing of critical risks, which is essential due to the difficulty of comprehensive risk management in construction. Ultimately, the success of construction projects is measured by time, cost, and quality, with prior research demonstrating subpar performance attributed to schedule overruns. Construction project delays can be categorized as justified (either with or without compensation), unjustified, or mutually influencing the liability of the parties involved [5].

Project delay is described as the time overrun that exceeds either the completion date stipulated in the contract as well the mutually agreed timeline for project delivery, or a segment of both [6]. In construction projects, there are different types of delays that can affect who is liable. These include delays that are excusable with compensation, delays that are excusable without compensation, delays that are non-excusable or contractor accountable, and delays that occur simultaneously [7]. Project completion delays in the construction sector are frequently related to numerous significant risks and uncertainties. Research has repeatedly shown that these risks vary among projects and are affected by factors such the geographical location, procurement processes, and the exact type of construction. Numerous studies underscore the need of concentrating on certain project categories that exhibit similar issues, despite the absence of extensive research on the categorization of risks across different sectors of the construction industry [7].

The construction industry in Afghanistan is crucial for economic and social advancement, particularly after years of instability [8]. However, research identifies significant challenges and knowledge gaps persist within construction projects, particularly regarding time overruns, which impede effective project execution. The necessity for enhanced research on these risks is increasingly evident, as large-scale construction projects frequently encounter considerable delays. Addressing these research gaps is crucial for mitigating project management issues and facilitating infrastructure improvements essential for developmental prosperity. The construction industry in Afghanistan deals with delays primarily due to a limited understanding of the dynamic nature of projects and the absence of robust frameworks to address these delays. Despite extensive research on time overruns, critical knowledge gaps remain, highlighting the need for advanced methodologies such as Monte Carlo simulations and risk-based models to improve forecasting and mitigation strategies. The RiskPert model has been recognized for its efficacy in time forecasting and project management. This research introduces an innovative simulation-based risk assessment methodology that differentiates between behavioral and statistical factors contributing to time overruns, thereby enhancing traditional models through the integration of expert judgment. This approach seeks to address the limitations of existing studies, which often rely on small sample sizes or focus narrowly on individual projects. Furthermore, this study analyzes 74 completed construction projects in Afghanistan utilizing a RiskPert-based simulation framework, providing insights into time overruns in conflict-affected regions. Efficient risk management procedures are essential for identifying and evaluating potential risks in diverse projects. A comprehensive risk assessment is essential for analyzing data and identifying these risks. Monte Carlo Simulation is acknowledged as the most effective tool for evaluating time overruns in Afghan construction projects. This strategic approach aims to mitigate the adverse consequences of project delays, ensuring more reliable project execution and resource allocation [9]. Multiple studies indicate that delays in significant civil engineering projects frequently occur due to numerous complications during construction [10]. To ensure a project remains secure and within financial constraints, all team members must sustain rigorous concentration on their responsibilities, as problems may result in additional complications later [11]. The incorporation and management of construction projects are extremely difficult, especially when dealing with resources, financial, and time restrictions. A significant issue is the regular failure to finish projects on schedule, which frequently results in time overruns. The present study offers a thorough examination of significant construction projects in Afghanistan that have encountered delays, employing a literature review and case studies based on official completion reports from various authoritative entities, including the Government of the Islamic Republic of Afghanistan, the Asian Development Bank, the World Bank, and the United Nations. The outcomes demonstrate that time overruns continue to be a significant concern that requires further research. Recent study has identified numerous adverse factors that cause delays for construction projects; yet these challenges continue to hinder the successful completion of projects. In accordance with the problem statement and to achieve a definitive, practical, and robust conclusion, the present study was conducted to address the following question.

Research question: What are the various risks of time overruns that could hinder a construction project in Afghanistan, and how can these risks be mitigated through the implementation of risk management strategies?

This study outlines principal risk factors that lead to delays in construction projects in Afghanistan. The objective is to fill a significant research gap by analyzing data from programs supported by prominent entities, with a particular emphasis on projects that encountered delays. This research seeks to examine the adverse factors affecting construction project time frame variables and their effects, to use data from industry firms, classify the main risk factors that cause construction project time overruns, and establish the relationship between the different types of risks (Construction, Environmental, Financial, Organizational, Technical, Physical, and Socio-Political) to understand how they impact the project’s completion dates. Furthermore, simulation models will be constructed utilizing expert judgments and historical risk data via RiskPert distribution to evaluate time overruns and verify the precision of these simulation results by contrasting them with the actual durations of finished projects. The objective is to improve risk assessment, forecasting, and project planning in the construction sector by identifying significant adverse challenges and evaluating necessary and recommended mitigation strategies to mitigate their impact. This research aims to offer critical insights into construction-related risks to guide policy formulation and enhance decision-making processes, hence facilitating more effective risk management.

2. Literature Review

The construction sector is crucial to the economy, exhibiting its fluctuations and advancements. Construction projects encounter numerous risks that might adversely affect their schedule, costs, and quality. These risks may be internal or external, are frequently interconnected, and encompass elements such as the workplace environment, monetary policies, political circumstances, social challenges, climatic conditions, and governmental laws [12]. Comprehensive risk management solutions are essential for attaining project objectives. This literature review aims to identify and mitigate risks in construction projects in Afghanistan by assessing prior studies and categorizing the causes of time overruns.

2.1. Risk Management in Construction Industry

Project Risk Management includes the activities of developing risk management plans, identifying risks, analyzing risks, preparing responses to risks, implementing response plans, and monitoring risks throughout a project. The primary goals of project risk management are to enhance the likelihood and magnitude of favorable risks while reducing the likelihood and magnitude of unfavorable risks, with the aim of maximizing the likelihood of project success [4]. Effective risk management aims to maximize favorable risks while minimizing unfavorable ones, ensuring projects are completed on time, within budget, and to quality standards [13]. Risk management in the construction industry is essential due to the inherent risks associated with complex projects. Rather than attempting to eliminate risk, effective risk management acknowledges that all projects carry some degree of risk and focuses on systematically identifying, analyzing, and minimizing these risks to ensure compliance with project requirements [14]. The risk management process is divided into three main phases: risk identification, risk analysis and evaluation, and risk responses [5]. The risk identification process entails assessing project risks and overall project risk variables, incorporating input from diverse stakeholders including project managers, team members, risk specialists, and area of expertise authorities. Involving all project stakeholders is essential for taking ownership of identified risks and for the success of risk response procedures. Systematic standards for identifying and documenting risks improve clarity and comprehension. Risk owners are appointed during this step, with their validation taking place in the qualitative risk analysis process. Preliminary risk answers are recorded for subsequent assessment in the plan risk responses procedure [4]. Risk management in the construction sector is crucial due to the inherent risks associated with construction operations [15]. Effective risk management strategies (Avoidance, Reduction, Transfer, and keeping) are essential for informed decision-making and improving project profitability [16,17]. Moreover, many construction projects fail due to insufficient evaluation and monitoring, which are essential for analyzing project performance against defined scopes and plans [17].

2.2. Types of Risks in Construction Industry

The construction sector is inherently risky, with all projects encountering uncertainties that might affect critical objectives in terms of scope, time frame, cost, and quality. Risks are characterized as uncertain events having a likelihood of occurrence exceeding 0% yet remaining below 100% [18]. Failure to identify or manage risks may result in project failure [19]. Risks may arise from multiple factors, including inadequate personnel or insufficient expertise, leading to increased expenses and delays. Although many risks may be effectively mitigated by comprehensive planning and contingency strategies based on previous data, unknown risks continue to pose significant challenges to management. Furthermore, certain risks may have potential benefits and, if accounted for, might be accepted in the expectation of beneficial consequences [20]. Managing risks in construction projects includes systematically seeking out and assessing potential risks and then coming up with a methodical strategy to deal with or avoid them. Due to the inherent risks associated with construction projects, risk management is an essential step in seeing them through to a successful conclusion. B. Landage, Mhetre, and Konnur (2016) classify the following as the main types of construction-related risks [17,19].

• Construction Risk: These encompass efficiency in labor, labor disputes, site conditions, failures of equipment, design modifications, excessively high-quality standards, and the implementation of new technologies.
• Environmental Risks: Natural disasters encompass dangers such as earthquakes, floods, extreme weather, landslides, and localized risks, all of which heighten safety concerns and need adherence to environmental regulations.
• Financial Risks: Financial risks are affected by increased material costs, uncertain currency fluctuations, payment delays, defective estimation, and low market demand.
• Organizational Risks: Organizational risks encompass a wide range of factors, such as contractor experience, participant attitudes, a lack of experience among employees, and problems with communication.
• Physical Risks: Physical risks encompass possible harm to infrastructure and machinery, employee injuries, and events such as fire and theft of supplies and equipment, as well as problems arising from inadequate safety regulation.
• Socio-Political Risks: Contamination of the environment, ethical behavior, unlawful payments, changes to regulations, corruption, official approvals, war, community dispute, and insecurity are all examples of socio-political risks.
• Technical Risk: Technical risks encompass risks linked to defective design, lacking specifications, poor site inspections, changes in scope, method of construction, and limited resource availability.

2.3. Time Overrun

In the last thirty years, research has concentrated on understanding the factors that hinder the success of civil engineering projects, particularly focusing on time overruns. This emphasizes the need to identify negative schedule-related factors that contribute to delays in construction projects [10]. Time management is crucial in construction projects, which have specific start and finish dates outlined in contracts. The “time of contract” refers to the maximum duration allowed for project completion, with any delays beyond this period considered time overruns. Delays occur when the actual completion date exceeds the anticipated finish date, and they can stem from various factors, leading to extended task execution. Such delays can cause financial and scheduling issues in both developed and developing nations [10]. A study by Assaf and Al-Hejji found that 70% of analyzed construction projects experienced time overruns. They identified and ranked 73 sources of delay, with “change order” being the most significant cause, as reported by contractors, consultants, and clients in their survey [6]. In India, delays in construction projects are often attributed to climate, topography, variation orders, and labor availability. Similarly, in Ghana, projects can be delayed by up to 82% beyond the expected completion date due to changes in project scope by professionals, poor quality work from contractors, and late payments from clients [21]. Callegari et al.’s research on Brazilian megaprojects revealed that larger projects involve significant, unanticipated risks, with average project delays increasing by 74.28% [22]. Construction projects in Vietnam often exceed deadlines due to unclear time assessments, poor change management, and delays in government approvals. Key issues include mismanagement between designers and contractors, inadequate communication, and administrative obstacles like corruption and lengthy permit processes. Efforts to expedite development through additional time do not enhance project outcomes. The main challenges are cultural and managerial, highlighting weaknesses in project planning, communication, and construction management practices in Vietnam [23]. The Nigerian construction industry faces major time overruns, with 70% of projects exceeding their schedules. Key factors contributing to these delays include financial and payment issues, poor planning, inaccurate project schedule estimations, frequent design changes, non-compliance with contract terms, ineffective management, government regulations, unavailability of materials, delays in approving changes, and poor communication among teams [24]. Construction projects in Saudi Arabia often experience extended durations due to factors such as inadequate planning and scheduling, financial limitations, procurement issues, insufficient contractor supervision, and the tendency to award contracts to the lowest bidder [21]. Government construction projects in Saudi Arabia often experience delays due to client-related issues, including change orders, poor planning, ineffective communication, and insufficient payments for progress [25].

2.4. Time Overruns in Afghan Construction Projects

The construction industry is crucial for economic and social advancement in both developed and developing nations, particularly in Afghanistan, where adherence to budget and schedule requirements is essential for projects. This industry greatly contributes to economic growth, accounting for around 10% of the national GDP [8]. The construction industry ranks as the third most significant industry in Afghanistan’s economic development, following agriculture and mining. Although its substantial economic contribution, the industry’s efficiency and growth have declined in recent years, with key infrastructure projects encountering delays, budgetary limitations, and diminished productivity [26]. Afghanistan required infrastructure for economic success following decades of instability, including modern roadways, bridges, and electrical power plants, along with the capability to maintain them. Construction projects are the primary driver for Afghanistan’s development [27]. The time overruns of construction projects in Afghanistan pose significant challenges for construction companies and their personnel. The construction sector in Afghanistan encounters obstacles such as project delays. Currently, the implementation of risk management in the construction sector has demonstrated enhancements in mitigating risks that adversely affect project objectives, including time, cost, and quality [28]. Afghan development projects, like the Kamal Khan Dam illustrates significant time overruns and budgetary complications. Kamal Khan is a hydroelectric project and irrigation dam located on the Helmand River in the Chahar Burjak region of Nimroz province, Afghanistan. The construction of the dam was set for 1974 but was suspended due to various considerations. In the last decade, the Afghan government has been working on its reconstruction. The dam reconstruction occurred in three phases. The first two phases, involving surveying, design, and land acquisition, took place from 2012 to 2015 with an $80 million budget. The project faced delays due to funding issues. The final phase began in 2017 and was completed in 2021 [27]. Similarly, the Afghan government has struggled to implement large projects, such as Sharake Jadid, which will house three million people. The project’s master plan, developed by French, German, and Afghan engineers, resulted in a $60 million investment in 2008, with each residency unit investing $1,000,000. Approximately 10 ministries and governmental organizations formed the New Kabul City Development Authority partnership to work on these projects, but no progress has been made. Moreover, the interruptions in the construction of the 32.805 km urban asphalt road project in Maimana city in Afghanistan were attributed to (insecurity, corruption, the contractor’s technical team’s insufficient experience, delayed invoice payments by the project owner, inadequate site management and oversight by the contractor, and issues arising from the contractor’s joint venture) [29,30]. Rafi et al. incorporated additional components into the Maimana projects (Overall, failures and project shortcomings have separated citizens from the government, highlighting its inadequacy in project implementation throughout Afghanistan) [30]. Additionally, outlines the results of a literature analysis of the several elements that substantially influence project delays. The principal risks faced by the construction industry in Afghanistan encompass (corruption, security concerns, and delays in progress payments from clients, Contractor’s financial issues, Frequent change orders issued by the client during construction, Market inflation, Errors and inconsistencies in design documentation, Unsuitable method of project bidding and awarding, Protracted bureaucracy in governmental institutions, Delayed approval of design documentation, Deficiency in the supply of necessary construction materials. Variations in the prices of construction and ancillary materials, Delay in subcontractors’ work. Insufficient pre-contract project coordination, Deficiency of proficient workforce, Enhancements to conventional drawings throughout the building phase, Inadequate qualifications of the contractor’s technical personnel, Inadequate site administration and oversight by the contractor. Inadequate planning and scheduling of the job by the contractor, Inadequate communication and coordination by the contractor with other stakeholders. Regular alteration of subcontractors due to their ineffective performance) [28]. Similarly, the top ten factors influencing construction efficiency in Afghanistan are security problems, payment delays, corruption, along with drawing and specification errors, Insufficient scheduling and coordination, modification during implementation, material delivery delays, construction methods, site health and safety events, and raw material quality issues [31]. Moreover, a significant number of construction projects in Afghanistan fail to meet their contractual deadlines, which hinders the country’s development. Consequently, these delays can lead to project failures, obstructing reconstruction efforts and negatively impacting both local and global businesses. For instance, the Mes Aynak copper mine ($350 million) and Hajigak iron ore ($550 million) face security issues, causing delays and additional costs [32].

Numerous road construction projects in Afghanistan have had delays attributable to various circumstances, including security issues, procurement challenges, payment delays to contractors for completed work, inadequate subcontracting policies, and design complications [33]. Additionally, an analysis of Management Information System (MIS) data from the Ministry of Public Works and the Ministry of Rural Rehabilitation and Development reveals that almost all rural road projects finalized between 2015 and 2020 had scheduling issues. It causes concerns inside the Afghan administration about the increasing frequency of delays in rural construction of roads. There are sixteen factors that have been found to contribute to these delays, including environmental factors, problems with the owners, contractors, consultants, and weather and climate [34].

Construction projects in Afghanistan must prioritize effective risk management to achieve project objectives related to cost, time, and quality. The integration of risk management into project processes is increasingly recognized across various industries. Implementing risk management measures and fostering an innovative mindset can enhance the successful completion of complex projects. In this context, risk assessment involves systematically identifying and analyzing potential risk factors associated with project activities [35]. An extensive risk management strategy is crucial for minimizing delays in construction projects in Afghanistan. This study highlights the necessity for comprehensive risk assessments and focuses on several risk assessment methodologies, notably the Monte Carlo Simulation technique. This technique allows stakeholders to carefully evaluate risks and uncertainties, resulting in enhanced decision-making and project planning, hence minimizing time overruns and improving project efficiency.

2.5. Monte Carlo Simulation

Risk assessment is an essential component of risk management; nevertheless, there has been limited study on selecting suitable models. Numerous approaches have been suggested to assist contractors and subcontractors in identifying high-risk projects and making informed decisions. These models are essential for predicting and mitigating potential construction risks, and project management teams presently have numerous options available [36]. Organizations need to select a risk assessment model tailored to their specific needs, as no universal method exists. Key considerations in this decision include implementation costs, the necessity for external approval, the organization’s structure, existing agreements, and factors like flexibility, complexity, risk level, and security philosophy. The complexities involved in the decision-making process make the task of selecting an appropriate risk assessment model quite challenging [37]. Classical quantitative methods used for risk assessment in the construction industry include Monte Carlo simulation, sensitivity analysis, critical path method, fault tree analysis, event tree analysis, failure mode, effects and criticality analysis. Because these approaches rely only on quantitative data, high-quality data is essential for making good use of these advanced quantitative techniques [36,37]. The domain of risk management has garnered considerable acknowledgment within the realm of project management in the past few decades. Project managers and upper management found that the identification, analysis, and assessment of potential project risks significantly enhance the development of risk mitigation along with contingency strategies for complex projects [38]. In this context, Monte Carlo simulation is a sophisticated risk assessment technique extensively employed in project management and other scientific disciplines. It facilitates continuous assessment of risks and opportunities, measuring the probability of different parameters. Since its introduction in the 1940s, advancements in computing have enhanced accessibility, resulting in its increasing acceptance as a favored approach for creating probability distributions of exposure and risk. This method is becoming increasingly relevant for risk assessors to measure uncertainty, particularly as dissatisfaction with conventional point estimate calculations rises [39]. This study explores the use of Monte Carlo simulation in experimental research, highlighting its advantages in overcoming challenges faced by traditional experiments, particularly related to sample size and analysis duration [40]. The Monte Carlo method improves analytical efficiency by facilitating numerical simulations without strict sample limitations. Moreover, it is a mathematical framework employed to model complex structures and forecast their behavior across diverse contexts. In risk management, notably within project management, it facilitates the evaluation of realistic project outcomes in the face of uncertainty. Utilizing probability distributions assists project managers in assessing the likelihood of meeting to schedules and budget constraints while also recognizing potential execution issues. This methodology enhances forecasting and decision-making by quantifying uncertainty in project dynamics [4,41]. Risk in construction is closely linked to time overruns, often leading to significant delays in infrastructure and construction projects [40,42]. Creating a simulation model, defining the problem, specifying the parameters of the input variables and their relationships, and finally, simulating and designing new trials are the primary steps in a simulation study. Currently, Monte Carlo computer simulations are the norm when it comes to simulating anything [42]. Creating simulation models is essential for mitigating risks by demonstrating problems, identifying causes, and developing new trials. Monte Carlo simulations are essential for predicting project outcomes and evaluating risks through probability distributions. In dynamic contexts like Afghanistan, where project risks and data conditions vary significantly, this method accurately assesses uncertainty in schedules and improves decision-making for project managers.

3. Methodology

This section outlines the methodological approach employed to achieve the objectives of the present research. It clarifies the procedures performed for data collection and the methods employed for data analysis. This study comprises a thorough literature review and case studies that employ a substantial dataset obtained from the evaluation and analysis of official project completion reports from government organizations, the United Nations, the Asian Development Bank, and other organizations in Afghanistan. This study combined and analyzed various project reports during the data preparation phase to extract appropriate data concerning the project’s scope, planned and actual duration, budget, performance, and associated risk factors. Figure 1 illustrates the comprehensive research methodology and the implementation procedures employed in this project. The flow diagram delineates the sequential process from problem identification and data collection to risk modeling, simulation, and model validation.

3.1. Data Collection

This study on time overruns in the construction industry began with a thorough review of existing literature, followed by an empirical analysis to identify causes of delays in construction projects. Seventy-four projects with comprehensive data on time overruns were selected for the investigation, which concentrated on compliance with schedules. Secondary data pertains to information and records that have been aggregated and systematically distributed by international organizations and governmental bodies. The World Bank, ADB, AFDB, and the US Department of Transportation are among the organizations that routinely publish their project statistics. It is beneficial to use secondary data in research offers several benefits, such as reduced data collection time and costs, along with enhanced quality, objectivity, accuracy, authenticity, and reliability [43].

The structured dataset comprises essential variables including project specifics (name, identification number, donor, sector, geographical region, and implementation dates), assessments of time overruns (planned and actual duration in days, percentage of time overrun), and insights derived from semi-structured interviews with construction experts to analyze schedule-related risks. Researchers conducted semi-structured interviews with 33 construction professionals, as summarized in

Table 1. Demographic Information of Experts.

Categories	Sub-Categories	Summary (%)
Educational Background	Ph.D.	3%
	Masters	48.5%
	Bachelor	48.5%
Employment Position	Project Manager	24.2%
	Consultant	12.1%
	Quality Assurance	18.2%
	Site Engineer	9.1%
	Other Senior Technical/Managerial Roles	36.4%
Professional Experience	≥15 years	42.4%
	5–10 years	18.2%
	3–5 years	24.2%
	1–3 years	12.2%
	<1 year	3%
Organization Associations	International Organizations	39.4%
	Government Organizations	27.3%
	NGOs and Private Sectors	33.3%

several construction specialists, including project engineers, managers, and donor program officials, to ascertain methodologies for modeling schedule-related risks. The interviews aimed to assess the minimum, most likely, and maximum percentages of time overruns in construction projects, identify common causes of these overruns that are often not documented in historical data, and highlight specific risk factors associated with the Afghan construction sector. The responses were utilized to generate RiskPert distributions for each relevant project or risk aspect. The distributions were subsequently employed to simulate time overruns. The PERT (Program Evaluation and Review Technique) distribution was employed to replicate the values proposed by experts. The PERT distribution employs three-point estimates to generate a skewed probability curve that emphasizes the most probable value. This renders it an effective instrument for modeling subjective assessments.

3.2. Classification of Risks

A systematic classification framework was developed to incorporate risk factors into a Monte Carlo simulation model, standardizing and quantifying the various ricauses of project delays identified in reports of selected construction projects. Through project reports and expert interviews, 29 unique risk causes were identified as risk factors for time overruns. The risks were classified into eight general categories, as is typical in the construction industry. This method enabled the systematic and statistically robust integration of risk into the simulation model.

Table 2. Types of construction project risks reported to cause time overruns.

Risk Code	Risk Causes	Reference
R1	Budget Constraints	[27,44]
R2	Construction Materials Price	[28]
R3	Contract Termination	[17]
R4	Contractors, Sub-Contractors, Poor Contractor Capacity	[8,28,29,30,31,32,34]
R5	Corruption and Fraud	[27,28,29,30,33,34,45,46]
R6	COVID-19	[17]
R7	De-Scoping	[17,28,47]
R8	Engineering Personnel/lack of Professional People	[17,28,33]
R9	Financial issues	[8,17,28,29,30,33,34,44,47]
R10	Geographical condition and access to projects	[17,27]
R11	Geotechnical Surveys	[17]
R12	Insufficient Supervision	[17,30,31,33,34,45]
R13	Internal Community Conflicts	[17]
R14	Land Acquisition and Resettlement Plan (LARP)	[17,33]
R15	Logistical issues	[17,28,32,34]
R16	Natural Disaster	[17]
R17	Political, governance	[8,17,28,32,33,44,46]
R18	Poor Management	[28,30,31,44]
R19	Poor Site Selection	[17,27,47]
R20	Price escalation	[17,28]
R21	Procurement	[8,27,28,30,33,45,46]
R22	Project Management	[17,28,33,34,46,47]
R23	Quality	[17,27,46]
R24	Safety	[17]
R25	Security	[8,17,28,31,32,33,45,47]
R26	Design issues	[8,17,28,31,46]
R27	The Contractor’s inadequate Performance	[17,30,34]
R28	Variation order	[8,17,27,28,29,33,46]
R29	Weather	[27,34]

presents a detailed description of the identified construction project risks and their impact on project schedules, as recorded in project reports. It defines the risk codes linked to diverse risk factors resulting in time overruns, supported by references within these reports. Semi-structured interviews with construction professionals highlighted the “Unknown Causes for Schedule Delay” risk category, often overlooked in risk assessments. Monte Carlo Simulation combines residual or unidentified risks to account for uncertainty in finished construction projects in cases of poor data. It reduces overly optimistic projections due to construction’s inherent flaws. The unknown causes for schedule delay category covers risks that were missed during risk assessment.

Table 3. Types of Risk Categories with Min, most likely and Max% impacts on project schedules (expert judgment).

Risk Categories	Min%	Most Likely%	Max%
R00-1 (Construction Risk)	10	20	35
R00-2 (Environmental Risks)	3	6	12
R00-3 (Financial Risks)	8	15	30
R00-4 (Organizational Risks)	5	12	25
R00-5 (Physical Risks)	2	5	15
R00-6 (Socio-Political Risks)	10	18	40
R00-7 (Technical Risks)	5	10	20
R00-T (Unknown Causes for Schedule Delay)	5	20	50

below provides a comprehensive overview of the many types of risks identified in the projects, including the minimum, most likely, and maximum percentage impacts on project schedules as assessed by experts. The identified risk variables were categorized into broader groups according to their characteristics and origins for more systematic analysis. This classification facilitated a more systematic examination of their impact on project performance. The risks were categorized using risk codes (e.g., R00-1, R00-2) that classified them into groupings based on similar themes, including financial risks, technical risks, etc., as it is illustrated in literature review.

Each project conducted independent simulations with a customized risk profile, meaning that relevant risk factors were activated according to their relevance, represented by binary coding (1 for relevant risks and 0 for irrelevant risks). For example, if a project’s risks deal to weather and contractor-related concerns, the relevant cells, such as R00-2 and R00-4, would be designated with a 1, while the remaining risk categories would be assigned a 0, resulting in distinct simulation outcomes for each project. This coding method is essential for separating certain risk classification without suggesting their probability. Risks were evaluated using probabilistic modeling, utilizing RiskPert distributions to measure uncertainty and impact, while recognizing the variance among projects. An Unknown Causes for Schedule Delay risk category was introduced to account for unforeseen or undocumented risks, which are similarly assessed using probabilistic methods. The categorization of risk factors as statistically independent arises from data limitations, potentially leading to an overlooked of extreme outcomes; this constraint has been acknowledged in the analysis. This classification of risks offered two principal advantages:

✓

Simulation Input Design: The existence of risk can be employed to generate average risk input values, especially for time overruns modeling using expert-derived RiskPert formulas.

✓

Post-Simulation Risk Analysis: By connecting the precision of simulation results (Excellent, Good, Moderate, Poor) with the incidence of each risk category, patterns of substantial risks can be identified and highlighted.

3.3. Software and Configuration of Simulation

To tackle the complex aspects of the project schedule regarding time overrun, and to facilitate rapid and ongoing analysis throughout the project lifecycle, it is essential to support the risk analysis methodology with specialized software and computing equipment that enables swift and efficient information management, encompassing numerous mathematical calculations integral to the stochastic model and Monte Carlo simulation [48]. A Monte Carlo simulation model was developed using @RISK software (version 8.0, Palisade Corporation, New York, NY, USA), an Excel-based risk analysis software, to evaluate the impact of identified risks on the project’s performance. The objective of the simulation was to quantify the uncertainty surrounding the project’s schedules, utilizing both historical data and expert judgments. Each project in the simulations underwent 10,000 iterations, enabling a statistically robust demonstration of various risk indicators. The method utilized expert assessments and historical data to determine the risk exposure of specific projects. The simulation method incorporated expert assessments of 29 distinct risk variables that potentially lead to project delays. Eight primary categories of these risk factors were identified: (Construction Risk, Environmental Risk, Financial Risk, Organizational Risk, Physical Risk, Socio-Political Risk, Technical Risk and Unknown Cause for Schedule Delay). Each project was simulated independently, including a customized risk profile with just pertinent risk categories enabled. Due to data limitations, clear statistical correlations among these categories were not established in the simulation design. This approach emphasizes the simultaneous occurrence of risks recognized in previous projects and functions as a simplifying assumption inside the simulation framework. Researchers employed binary values, with 1 denoting the presence of a risk and 0 its absence, to monitor the risks associated with each project, linking them via designated risk codes. To determine the potential delay for each project, it utilized an estimation method based on RiskPert. To determine the anticipated percentage of delay, the following formula is utilized.

Time Risk Input (%) = RiskPert(Min, most likely, Max, RiskName(“R00-1”))

(1)

The computed Time Risk Input (%) was included in the simulation model utilizing the subsequent equation:

Simulated Duration (days) = Planned duration × (1 + Time Risk Input/100)

(2)

Setting Up and Running the Simulation

The simulation was executed with the subsequent global configurations in @RISK:

• Number of iterations: 10,000 (to guarantee convergence and reliability).
• Sampling method: Latin Hypercube Sampling for enhanced variability management.
• Confidence intervals: Results were analyzed at the 90% and 95% confidence levels.
• Captured Outputs
  • Simulated values for duration.
  • Histograms and S-curves (Probability distribution of results).
  • Tornado charts (sensitivity analysis of input risk factors).
  • Summary statistics (mean, min, max, standard deviation).

3.4. Accuracy Classification

The next phase after conducting Monte Carlo simulations for time overrun was to assess the closeness of the simulated values to the real project results. A mechanism was implemented to classify each project based on the absolute percentage difference between the simulated mean values and the actual recorded data. Each project was categorized into one of four accuracy levels. The accuracy classification level was established in the following order: Excellent (≥80%), Good (60–79%), Moderate (40–59%), and Poor (<40%). The objective of these ranges was to provide an effective means of assessing the degree of accuracy of the simulation in relation to actual project behavior. The method enabled the assessment of the model’s anticipated reliability in a real-world context, determining the percentage of projects simulated with acceptable accuracy. The classification was performed independently for time simulations, based on the data accessible for each project. The absolute error was determined using the subsequent formula:

Accuracy Error (%) = |(Simulated Mean-Actual Value)/Actual Value|*100

(3)

The accuracy assessment serves two purposes: Firstly, it evaluates model performance by quantitatively measuring the alignment of RiskPert simulation findings with actual project outcomes, hence proving the modeling approach’s reliability. Secondly, it involves a risk correlation analysis that investigates the relationship between accuracy groups and defined risk categories to determine if specific risk types were consistently linked to higher prediction errors. This facilitated the identification of the risk categories that most significantly contributed to uncertainty or model variance.

4. Data Analysis and Finding

4.1. Construction Projects

A thorough literature review on time overruns in construction projects focused on projects that experienced delay in completion, analyzing the factors contributing to these adverse outcomes. Time overruns in research projects are distributed as shown in Figure 2. Time overruns were frequent among the projects included in this study; in fact, 35.14 percent of those projects experienced delays exceeding 100% of the anticipated duration. In addition, 20.27 percent of delays were between 0 and 25 percent, while 57.17 percent of projects exceeded 50% of their anticipated duration. Time overruns were observed across all 74 analyzed projects.

4.2. Simulation Outputs and Results

The primary output variables in managing a project encompass Scheduled Duration (established timeframe), Actual Duration (completion time), Simulated Duration (anticipated duration derived from Monte Carlo simulation), Time Risk Input (%) (The weighted average of risk-adjusted delay input), Simulated Overrun (%) (discrepancy between simulation results and baseline), Actual Overrun (%) (deviation from actual data relative to baseline), P90 Duration (duration within a 90% confidence interval), and Accuracy (%) (difference between actual and simulated overruns).

The simulation illustrates the impact of time overruns on project schedules. The simulation process is clarified using visual tools like histograms, S-curves, and tornado diagrams, which examine a standard project and emphasize the behavior and sensitivity of critical risk factors affecting schedule execution. The histogram displays many potential delay situations, whilst the S-curve displays the overall probability of project delays, signifying the possibility of surpassing specified project schedules. The tornado diagram identifies the most influential risks, with R00-6, R00-3, and R00-4 emerging as the principal factors contributing to increases in simulated duration. The risks are especially significant in projects with considerable overruns, highlighting their essential impact on schedule efficiency.

The sensitivity analysis utilizing regression coefficients indicates that risks R00-6, R00-3, and R00-4 exhibit significant positive correlations with simulated durations, emphasizing their significant impact on project delays. The accuracy classification for the simulated time overrun in

Table 4. Accuracy classification for simulated time overrun.

Category	Accuray Range (%)	Projects	Percentage
Excellent	≥80%	28	37.84
Good	(60–79)%	26	35.14
Moderate	(40–59)%	12	16.22
Poor	<40%	8	10.81
Total		74	100.00

demonstrates that the simulation method attains an overall accuracy of 72.98%, it is categorized as Excellent/Good, underscoring its effectiveness in assessing schedule-related risks.

Table 5. Accuracy of Risk-Based Classification.

Risk Code	Excellent	Good	Moderate	Poor	Total	%Poor
R00-1	5	1	0	0	6	0
R00-2	5	1	0	0	6	0
R00-3	11	11	4	6	32	18.75
R00-4	13	15	5	5	38	13.16
R00-5	1	2	1	1	5	20
R00-6	18	20	8	6	52	11.54
R00-7	6	5	2	0	13	0
R00-T	9	6	6	2	23	8.70

displays the distribution of projects based on risk code across different accuracy levels. The “% Poor” column indicates the quantity of projects within each risk group that were simulated with inadequate accuracy. Significantly, no projects received a “Poor” rating in areas R00-1, R00-2, and R00-7, indicating either negligible influence on time overruns or that the simulation model corresponds to reality. Conversely, R00-5 had a notable frequency of 20% of projects assessed as below “Poor” accuracy, succeeded by R00-3 at 18.75%, R00-4 at 13.2%, and R00-6 at 11.54%.

Figure 3 illustrates the frequency with which risks occur across all projects. The prevalence of Risk R00-6 across projects indicates that it has the most significant effect on time overruns. Following this, Risks R00-4 and R00-3 were also frequently observed, reflecting their considerable impact on project timelines. Considering the findings, these risks are more prevalent and ought to be given a greater amount of consideration while developing for future endeavors and determining measures to mitigate them.

According to

Table 6. Summary of Statistics for Project Durations: Planned, Actual, and Simulated with P90 Values.

Statistic	Planned Duration (Days)	Actual Duration (Days)	Simulated Duration (Days)	Actual Time Overrun (%)	Simulated Overrun (%)	P90 Duration
Mean	1119	1944	1569	111	40	1681
Min	149	288	231	−13	14	235
Max	3823	5559	4500	1001	69	4889
Std.dev.	678	1080	971	155	13	1041

, which summarizes the project durations and overruns percentages statistically, the actual completion time was 1944 days, which is much longer than the average planned duration of 1119 days. As a realistic approximation of performance, the mean simulated duration of 1569 days falls somewhere in the middle of the planned and actual durations. There was a significant underestimating of delays in actual projects, as the simulation predicted around 40% of the time, while the actual time overrun averaged about 111%. While the predicted overrun showed significantly less variation −13%, suggesting consistent results from the model, the substantial standard deviation for real time 1080 days indicates great variability among projects. It appears that certain projects were finished ahead of schedule, as shown by the occurrence of a negative minimum overrun. The P90 duration values represent the 90th percentile of the simulated duration distribution, which provides a statistical estimate of project completion even if conditions are unclear. It compares the simulation model to the project’s real results to determine its accuracy.

The study outlines the creation of a framework intended to investigate the causes and consequences of project overruns. It highlights the significance of understanding the sources and consequences of fundamental risks. Simulation findings are provided, estimating the effects of various risks on construction project schedules while analyzing patterns, risk correlations, and data with actual applications. The results are contrasted with real project performance and current literature to derive insights into effective risk management strategies for mitigating project overruns. It prepares for future discussion in the outcomes section, where recommendations will be presented. The simulation method is emphasized as an essential instrument for planners and decision-makers.

5. Discussion

This section analyzes the Monte Carlo simulation outcomes on time overruns in construction projects, emphasizing their methodological and practical importance. The results indicate that the simulated project durations closely align with actual outcomes, predominantly when expert judgment is integrated, hence enhancing the dependability of the employed simulation framework. The simulation results show that Socio-Political Risks-R00-6 (Corruption and Fraud, Internal Community Conflicts, Land Acquisition and Resettlement Plan (LARP), political, governance, and security), Organizational Risks-R00-4 (Contract Termination, De-Scoping, Insufficient Supervision, Poor Management, Project Management, The Contractor’s Inadequate Performance, Variation Order), and Financial Risk-R00-3 (Budget Constraints, Construction Material Price, Financial issues, Price Escalation, Procurement issues) cause more delays in the project than any other risk. This study indicates that risk trends in construction projects in underdeveloped nations align with Monte Carlo analyses, in contrast to developed countries where technical and contractual risks dominate. The differences are attributed to diverse institutional and governance situations. This research recommends the use of specific strategies to mitigate the primary risks leading to delays in construction projects.

5.1. Mitigation Measures and Recommendations for Identified Risks

The tendency of natural disasters has markedly increased in recent decades, intensifying limitations on construction projects and raising worries regarding potential failures if unaddressed [49]. Weather profoundly influences the completion of projects in construction, with elements such as heavy rainfall, storms, and extreme temperatures resulting in delays and higher costs [50,51]. The sector, accounting for 12% of global GDP, is increasingly vulnerable to weather-related disruptions caused by climate change, requiring customized mitigation methods [52,53]. Adverse conditions may cause productivity disruptions, equipment damage, and access challenges, leading to financial consequences such as increased labor expenses and prolonged rental periods. This difficulty is especially evident in areas with erratic weather patterns, intensifying budget limitations [51]. Weather-related risks have a negligible influence on project schedule performance. This conclusion indicates that, although there is a prevalent emphasis on weather-related risks in construction management, they are among the least impactful elements influencing construction schedules in Afghanistan.

To mitigate weather-related effects, two primary techniques have been identified: physical methods that enhance logistics and management, along with administrative methods focused on optimizing requirements for contracts and project scheduling [51]. The construction sector analyzes weather modeling from three perspectives: meteorological formation, construction impact, and project scheduling. Accurate meteorological data is essential for formulating adaptation and mitigation measures for weather impacts on construction. The sector uses computational models that integrate climate change prediction to improve construction scheduling. Severe weather profoundly impacts construction projects, with elements such as climate and location impacting planning and design.

The financial risks linked to construction projects in Afghanistan are complex and closely connected to external financial factors. The instability of material pricing, influenced by variable foreign exchange rates and dependence on imports, intensifies the difficulties encountered by project managers. Prolonged payment delays and procurement challenges worsen the financial environment, resulting in possible miscalculations and adverse tax consequences. The reliance on an unstable Afghan currency for domestic transactions introduces additional complexity, potentially resulting in considerable differences in budgeting and financial planning. Furthermore, delays in invoice processing could hinder cash flow, threatening timely payments to subcontractors and suppliers, which are crucial for sustaining project progress. The consequences of these financial risks extend beyond immediate cost increases; they may lead to extended project schedules, increasing operational costs, even legal consequences, and reputational damage.

Corrective actions for financial risks in Afghanistan entail the establishment of strict rules and regulations, the augmentation of financial understanding among citizens, the enhancement of transparency in financial dealings, and the development of international alliances to fortify the financial system. It includes enhancing risk assessment processes and guaranteeing financial institutions comply with optimal practices in risk management.

Longer project timelines present considerable technical risks, possibly jeopardizing safety and quality while raising the probability of accidents, errors, and subsequent repair and rework expenses. To effectively manage these risks, it is essential to prioritize economically viable offers throughout the bidding and contract award procedure, while assuring the selection of experienced and qualified contractors. Moreover, formulating accurate and detailed project plans and timetables is crucial for preventing delays resulting from insufficient preparation. Recruiting dependable engineering people is essential for project stakeholders, especially owners, as it assures access to reliable equipment and vendors, hence improving project execution and minimizing the risk of technical failures.

The socio-political challenges impacting project execution include corruption, community conflicts, instability in politics, and land acquisition and resettlement plan, highlighting the necessity for thorough risk management measures in construction projects. Corruption, fraud, and scandals inherent to the construction sector severely affect from project performance in terms of time, cost, quality, safety, and overall satisfaction, in addition to compromising the benefits provided. Corruption, characterized as the use of authority for individual benefit, encompasses unethical and unlawful actions, leading to significant ecological, social, societal, and economic consequences. Consequently, addressing these socio-political variables is essential for guaranteeing project success. Construction corruption is caused by personal aspirations, corrupt stakeholder relationships, unethical managerial practices, poor legal frameworks, and insufficient enforcement. Corruption rises in environments without transparency and accountability due to political governance. Poorly regulated political regimes with inadequate rule of law and regulatory enforcement increase construction risks. Conditions that enable corruption allow unethical activities to endure, causing additional expenses and delays in project completion [53].

Implementing efficient strategies can reduce illicit activity, enhance cost efficiency, and guarantee timely project completion. Significant measures encompass enhancing legal compliance, encouraging ethical conduct via professional development, boosting transparency through the publication of contracts, developing oversight and accountability mechanisms, and developing integrity within both governmental and construction sectors.

Property issues and social difficulties often cause internal community conflicts, which delay construction projects. Lessons derived from development agencies functioning in Afghanistan reveal that improper land acquisition procedures, uncertain compensation frameworks, and minimal community involvement are prevalent causes of delays. Proactive stakeholder engagement, transparent communication of project advantages, and the implementation of land acquisition and resettlement planning in accordance with internationally accepted norms are successful ways for mitigating social disputes and lessening time overruns. Political and security challenges can considerably delay project scope and schedules, frequently worsening legal delays, insufficient compensation mechanisms, and societal conflicts related to land acquisition and relocation processes. Lessons learned from project implementation experiences reveal that poor institutional governance and insufficient coordination among stakeholders worsen these issues. Strengthening institutional capacity, refining legal and regulatory frameworks, boosting stakeholder alignment, and integrating security assessments and contingency planning into project design can mitigate such risks. Furthermore, rapid urbanization and population expansion have heightened the demand for infrastructure, making land acquisition for construction of roads especially difficult in the Afghan region. Property-specific activities frequently begin parallel with project development; yet, heightened public knowledge of infrastructure projects can elevate land values, affecting acquisition of land agreements. Resistance from landowners to governmental compensation proposals could increase costs and extend conflicts, negatively impacting schedules for projects. Consequently, proficient land acquisition management is crucial for guaranteeing timely and economical execution of construction projects. Poorly managed land acquisition operations may result in project delays, financial overruns, community disagreements, loss of agricultural land and productivity, unemployment among displaced farmers, disruptions to livelihoods, alterations in land ownership patterns, and ongoing compensation-related disputes.

5.2. Corrective and Preventive Actions

Project managers and team members must guarantee the timely completion of projects. Prior research suggests that recognized adverse factors provide a foundation for policymakers, planners, and project managers. Investigating the causes and origins of negative events are essential. It offers guidance, advice, and proposals for practitioners to avert or mitigate the effects of these detrimental factors. Notwithstanding prior investigations, only a limited number of studies have thoroughly examined and suggested remedies to mitigate the impact of recognized detrimental factors on project schedules. The research findings on these adverse risk causes are detailed in

Table 7. Identified Risk Causes in Construction Projects.

Risk Code	Risk Causes	Corrective Action	Preventive Action
R1	Budget Constraints	Corrective actions for managing budget constraints in construction projects include assigning liability for supplementary payments to the responsible contractual party and holding prompt meetings with contractors to reach satisfactory resolutions. Additional measures involve timely adjustments within the executing or advisory firm, revising budgets, and prioritizing ongoing or suspended work.	Preventive actions for addressing budget constraints in construction projects encompass precisely describing the scope of work, informing clients about the consequences of scope alterations, and guaranteeing comprehensive document verification prior to submission. Essential practices include performing comprehensive project assessments before bidding, utilizing precise data for estimations, and engaging experienced designers and estimators. It is essential to verify errors, dismiss unrealistic estimations, and develop budgets with the assistance of experienced professionals. Moreover, evaluations by external specialists and the modification of cost units to align with local market values are essential. Ultimately, aligning designs with budgets and including explicit contract provisions for additional work are essential.
R2	Construction Material Price	Corrective actions to mitigate construction material price issues encompass initial forecasting and study of inflation and foreign exchange rates before project commencement. Measures entail incorporating contractual provisions for price stability, allocating risks appropriately, and securing goods via advance payments to mitigate possible cost increases. Organizations should anticipate currency fluctuations, formulate strategic contingencies, do regular contract evaluations, and include stakeholders to effectively manage material price risks.	Preventive actions to mitigate construction material price volatility include creating detailed lists of suitable materials with their advantages and disadvantages, accelerating approval processes through expert consultations, and utilizing lessons from past projects to improve efficiency. Additionally, reducing bureaucratic procedures and leveraging advanced technologies for enhanced collaboration can improve decision-making effectiveness.
R20	Price Escalation	The integration of price escalation clauses in contracts, the application of fixed pricing mechanisms, and the continuous observation of price trends are vital strategies in contract management. It is important to secure labor and material costs for specified durations while also ensuring that the risks associated with inflation are equitably shared between the client and the contractor.	Preventive actions to mitigate construction material price escalation include renewing contractual terms, adjusting budgets and timelines, substituting materials with cost-effective alternatives, optimizing resource use, minimizing waste, revising cost plans, and implementing effective procurement strategies.
R21	Procurement	Corrective actions encompass temporarily utilizing internal client or contractor resources to address deficiencies, improving construction processes, eliminating non-essential operations, adjusting project schedules, reducing durations of essential duties, and executing independent tasks simultaneously.	Preventive actions in procurement emphasize the early engagement of qualified advisors, empowering them with decision-making authority, and assuring early payments in advance to maintain seamless operations. Precise contract provisions defining responsibilities and risks, in combination with comprehensive security evaluations prior to project commencement, substantially mitigate procurement delays and conflicts.
R3	Contract Termination	Corrective action for contract termination encompasses immediate replacement of the terminated party to prevent delays, the adjustment of the project timeline for a seamless transition, arranging of urgent meetings to address unresolved concerns, and the enforcement of contractual clauses to protect financial and legal interests. Moreover, using internal resources or engaging proficient consultants can facilitate the continuity of project advancement throughout the period of transition.	Preventive actions for preventing contract termination include comprehensive contractor assessment and selection based on expertise and competence, sustaining ongoing communication among project stakeholders, reducing scope and design modifications, implementing strict site oversight, and establishing fixed-price contracts with clear risk distribution. Moreover, implementing contingency plans and fostering confidence in internal project management improve stability and diminish conflicts that may result in termination.
R7	De-Scoping	Corrective actions entail eliminating unnecessary expenses, implementing rigorous budgeting strategies, reallocating resources effectively, and revising project components in accordance with the adjusted scope while avoiding delays.	Preventive techniques for de-scoping encompass precise original scope definition, extensive site investigations, complete comprehension of client needs, rejection of unrealistic scope modifications, and periodic feasibility assessments to mitigate scope creep.
R12	Insufficient Supervision	Corrective actions include improving supervision quality, enhancing communication, rescheduling duties, and adopting appropriate construction methods to diminish time overruns.	Preventive actions for insufficient supervision include hiring proficient project managers, enabling efficient communication, implementing continual monitoring, and offering employee training.
R18	Poor Management	Corrective actions for poor management include adjusting project timelines, enhancing team skills by adding qualified personnel, and improving client communication. In severe cases, legal action or contract changes may be necessary, alongside strategies like overtime or resource reallocation. Engaging external advisors and following revised timelines can help mitigate delays caused by poor management.	Preventive actions emphasize the recruitment of senior and competent project managers and personnel who possess familiarity with similar project situations. Develop successful communication lines among all stakeholders to maintain understanding in the project’s goals and ongoing collaboration. Implementing comprehensive training and establishing a culture of responsibility alongside regular supervision can further mitigate failures in management.
R22	Project Management	Corrective actions encompass immediate detection of performance deficiencies with contractors, substitution of inadequate subcontractors, implementation of innovative technologies, rescheduling of work, and legal recourse when required. Moreover, prolonging working hours and enhancing labor productivity assists in reducing delays. Collectively, these techniques boost project success by proactively mitigating risks and efficiently addressing arising issues.	Preventive actions encompass comprehensive site assessments, precise scope description, prompt delivery of accurate blueprints, selection of senior contractors and proficient personnel, and reduction of design or scope modifications throughout construction. Facilitating timely payments and promoting effective communication and collaboration among project stakeholders are essential.
R27	The contractor’s Inadequate Performance	Performance monitoring ensures project adherence to timelines and quality standards. It may be necessary to replace subcontractors or contractors to maintain project integrity. Implementing strategies to increase productivity optimizes resource utilization, while consulting experts can provide valuable insights for project improvement. Controlling work scope prevents scope creep, and effective management of contractual liabilities mitigates risks and upholds legal obligations.	To prevent inadequate contractor performance, it is imperative to emphasize appropriate contractor selection, engage proficient personnel, and establish training programs. Efficient communication and resource allocation are essential for project success. Preventing modifications in design or scope ensures project integrity, while employing fixed-price contracts with explicit provisions guarantees accountability. Moreover, timely payments are essential to cultivate favorable relationships with contractors.
R28	Variation Order	Corrective actions for handling variation orders in construction projects entail a rapid start of change management, schedule compression, and the accurate issue of modifications by the owner. Essential steps involve evaluating new scope elements, revising pricing, and employing contractual clauses for justifying additional time and compensation. Moreover, comprehensive documentation, official client approvals, and modifications to project expenses and schedules are essential for reducing disagreements and mitigating negative effects on project duration.	Preventive actions for variation orders include providing full and precise project details at the time of tender, outlining modifications to scope directions in the contract of employment, and receiving customer written agreement before making any changes. Changes must be managed financially, and project stakeholders must communicate. Design modifications should be managed by authorized staff using robust change management methods. Gaining knowledge from previous projects and monitoring progress reduce construction time overruns.
R5	Corruption and Fraud	Corrective actions to mitigate corruption and fraud risks in construction projects include regularly scheduled stakeholder meetings to resolve issues, reallocating resources, redefining responsibilities, streamlining activities, utilizing competent staff members, and integrating novel technologies. These measures seek to minimize delays, manage expenses, and improve the project’s overall efficacy.	Preventive actions regarding corruption and fraud in construction projects include improving transparency, establishing effective auditing procedures, applying rigorous laws and regulations, streamlining administrative processes, enhancing capacity through training, delegating authority to reliable personnel, and ensuring equitable compensation.
R13	Internal Community Conflicts	Corrective actions include performing comprehensive evaluations that determine the community’s needs and desires, therefore preventing the selection of projects that might create resistance or conflict. Projects that do not match with the community’s agreement are likely to encounter challenges, including denial of utilization of contractors and insufficient community participation in oversight.	Preventive actions to avoid internal community conflicts involve selecting projects with the consent of local residents, consequently promoting community support and engagement in execution, monitoring, and supervision. It provides a conducive atmosphere for project implementation.
R14	Land Acquisition and Resettlement Plan (LARP)	Corrective actions concentrate on mitigating time overruns via efficient land acquisition methods, settling compensation conflicts with landowners to minimize rising costs and civil disturbance, and tackling challenges associated with urbanization and population increase to improve LARP success.	Preventive actions for Land Acquisition and Resettlement Plans (LARP) encompass early involvement of stakeholders, clear communication of project value, and compliance with international standards, community engagements being essential for developing support and mitigating conflicts.
R17	Political, Governance	Corrective actions for resolving political issues in construction projects encompass lawsuits for compensation, strengthening project management with experienced specialists, altering activities, altering plans, halting work for protecting assets and security, possibly ending contracts, filing insurance claims, swapping goods with other options, adhering to revised schedules, hiring local labor, increasing performance to recover lost time, securing funding, engaging specialists, and strengthening communication with clients.	Preventive actions for governance challenges in construction projects encompass steering clear of unstable areas, performing comprehensive political risk evaluations, obtaining insurance and governmental assurances, employing fixed-cost and collaborative agreements, and integrating provisions for delays and price hikes. Supplementary techniques include pre-acquisition of materials, engaging seasoned professionals, sustaining efficient communication, guaranteeing legal readiness, facilitating adaptable rescheduling, and employing local labor in international projects to mitigate political risks and reduce project delays.
R25	Security	Risk mitigation planning for construction projects involves many tactics designed to diminish the probability and consequences of security concerns. Essential elements encompass stakeholder collaboration, executing comprehensive security evaluations, ongoing surveillance, and formulating contingency strategies. Moreover, training and raising awareness within project teams, along with strengthening involvement with local stakeholders, is crucial. Flexible project scheduling facilitates flexibility in risk management, ensuring that both corrective and preventive actions are implemented to efficiently handle possible security threats.

, along with the appropriate corrective and preventive actions.

To mitigate time overruns in the Afghan construction industry, several critical recommendations may be proposed:

• Governments and acquiring agencies should take steps to reduce land acquisition delays. If possible, prevent land acquisitions and thoroughly analyze landowners and assets before bidding. Land purchases before civil works can be accelerated by learning from earlier projects. Timely compensation for impacted individuals requires appropriate pre-allocated cash based on average annual land income, modified for land usage type like harvesting, agriculture, or housing.
• An effective approach must incorporate unified risk mitigation frameworks that use technical resources, improve capabilities, engage communities, and follow stringent legal rules. These steps ensure project quality and minimize cost and schedule implications. It emphasizes the significance of using digital technology, standard rules, and stakeholder interaction to manage socio-political risks and ensure projects satisfy social goals and public trust.
• Effective communication and contingency planning are essential for improving safety in construction firms. Developing a proactive safety culture is essential, as it promotes robust emergency response capabilities to address safety issues and derive lessons from it.
• Construction firms, especially in regions like Afghanistan that encounter extreme weather conditions such as thunderstorms, hailstorms, and flooding, must adopt proactive measures to mitigate weather-related risks. Essential strategies encompass anticipating adverse events, incorporating buffer periods into project schedules, and employing weather-resistant methodologies. Moreover, developing efficient communication among stakeholders is essential for the early identification of risks, while continuous evaluations of weather effects on project limitations facilitate required modifications.
• Many Afghan individuals lack sufficient management experience, highlighting the necessity for investment in their education and development to enhance project management skills. Moreover, sustaining regular interaction among stakeholders is essential for reducing delays and executing effective risk management methods, which also entails improving engineering and project management skills.
• Construction companies employ de-scoping to address financial difficulties by lowering costs and prioritizing projects, while also maintaining client satisfaction and integrity. Construction risks encompass poor supervision, alterations in project scope, technical challenges, poor management, contractor deficiencies, and difficulties in material procurement. To improve project outcomes, it is advisable to employ proficient project engineers for scheduling, ensure early supervision, and uphold quality standards. Moreover, efficient communication among customers, contractors, and stakeholders is essential for quickly solving scope alterations and technical issues.
• Prioritize early material acquisition via market analysis, ensure efficient planning for mobilization and logistics from project start to completion, conduct regular assessments of environmental and related risks during the design phase, and strengthen management standards and oversight to enhance contractor performance and address material procurement challenges.

6. Conclusions

This research performed an extensive analysis of seventy-four large construction projects in Afghanistan to determine the factors contributing to time overruns. This study discovered inefficiencies in time management that impact productivity and suggested appropriate corrective and preventive actions. Following a comprehensive analysis of project reports and expert consultations, a total of 29 distinct risk variables were identified. These risk variables were then organized into eight groups and systematically included into the simulation models. The most important elements impacting the efficiency of time overruns in construction projects were found to be financial risks, organizational risks, and socio-political risks. The simulation exhibited an average time overrun accuracy of 70.58%, indicating a substantial similarity between simulated and actual project durations. This indicates that time risk inputs based on judgment from experts successfully identified critical elements contributing to project delays. The findings indicate that simulations often correspond with real-world results, particularly when significant expert input is employed. Expert judgment inputs provide dependable evaluations of a project’s prospective success, with the simulated durations of most projects deviating by no more than ±15% from actual values. The P90 estimates provide decision-makers with various scenarios to improve confidence in risk reduction. Moreover, accuracy ratings facilitate the comparison of different models, thereby informing the development of criteria for future expert judgment contributions. This study underscores the necessity for various mitigation strategies to address time overruns in construction projects in Afghanistan by efficient risk management.

The study goal is to improve project management within Afghanistan’s construction sector by improving monitoring, stakeholder collaboration, and proactive planning to diminish time overruns. The sector faces challenges in risk management due to poor institutional frameworks and coordination, resulting in reactive decision-making and increased likelihood of schedule delays. This research identifies multiple causes of delays in construction projects, such as inadequate planning and design, financial difficulties, political interference, alterations in project scope, and insufficient compliance with contracts, compounded by poor coordination and inaccurate estimations of costs. In summary, preventive actions including securing funding for the project prior to contract execution, maintaining precise cash flow estimations, finalizing precise project designs, and enforcing rigorous procurement protocols are essential for mitigating time overruns. A systematic approach to risk management is thus necessary, underpinned by frequent training, sufficient resource allocation, and precise assignment of risk management responsibilities. The utilization of quantitative methods, including Monte Carlo simulation, can improve project outcomes by accurately identifying, assessing, and managing risks, while promoting stakeholder engagement and complying with the demands of the industry.

This study has many limitations that must be acknowledged, including its reliance on historical data and the subjective characteristics of expert judgment in the RiskPert design, potentially introducing bias. The effectiveness of the created RiskPert simulation framework for real-time project control has not been assessed, as it was solely examined in an ex-post analytical context. Future research should seek to expand the framework’s applicability to diverse regions and incorporate additional risk indicators and actual project data. The authors plan to pursue ongoing research and further investigations on these topics in future studies.