A Risk-Based Prioritization Framework for Contractual Claim Drivers in Public Construction Projects: Evidence from Kuwait

Abstract

Disputes are common in the intricate professional setting of the construction sector. When claims cannot be resolved kindly, they often escalate into conflicts that result in litigation. Identifying the root reasons of these claims and understanding their effects on project timelines, costs, and quality can help prevent poor performance in construction contracts. This study makes a unique contribution by developing a cause of claims breakdown structure (CCBS) that systematically categorizes the most frequent roots of claims identified in the building sector through an extensive literature review, and by subsequently assessing these categories using expert-based relative importance indices (RII). Using relative importance indices derived from specialist opinions, the research provides likelihood and influence quantities for 15 typical claim sources in the building sector. These values offer stakeholders in public construction projects a framework for assessing risks and planning mitigation strategies for construction claims. The study reveals the five most significant risk factors for contractual claims in the Kuwait building sector. These issues are ambiguities in contract language, followed by weather-related disruptions, ineffective communication among stakeholders, inadequate planning, and regulatory changes.

1. Background

Following the 2008 global financial crisis—which caused widespread economic and banking instability worldwide—Kuwait’s construction industry experienced a marked slowdown. The effects were particularly evident in reduced investment in public works and delays in project initiation. However, in the past few years, especially post-2020, the industry has started to recover, showing clear signs of growth within the country [1]. Since then, there has been a rise in public works contracts, accompanied by considerable funding provided by public organizations engaged in the construction industry. Similar to other markets, the construction sector encounters issues such as project delays and cost overruns, which frequently result in claims and disputes that often lead to litigation, adding extra costs for the parties involved.

Conflicts are likely to occur in this intricate work environment where various goals and advantages compete based on the viewpoints of all stakeholders [2]. When these disagreements cannot be resolved through amicable discussions or effective management strategies, they could lead to the filing of a claim, which is a demand for payment for losses suffered by any of the contract’s parties [3]. If the opposing party denies this claim, it can lead to a dispute, which often becomes prolonged, especially if it escalates to litigation [4]. Consequently, a disagreement begins to emerge when a claim is filed and rejected [5], which can significantly impact contract performance. Understanding the reasons behind these claims and their effects on project timelines, costs, and quality is expected to improve the successful execution of construction projects.

A literature assessment was first carried out, focusing on studies related to construction industry claims since 1990. This review was primarily based on publications indexed in Scopus and the Web of Science (WoS) databases, complemented by targeted searches on Google Scholar to capture additional accessible sources, where many academic works containing the words ‘construction claims’ or ‘disputes’ were recognized. From this collection, 60 study papers were selected for in-depth content examination. The selection criteria included only freely accessible articles that provided a list of causes for contract claims. As detailed in Table 1, eighteen of these studies focused on identifying and assessing the causes of claims, while others explored various methodologies for dispute resolution, and two addressed both aspects. Additionally, some studies examined issues related to claims management, and four proposed specific frameworks for negotiating claims. Four studies analyzed the argument escalation procedure [6], asset risks linked to claims [7], and stakeholders’ views on fairness within the organization and their collaborative actions in claims management [8]. Lastly, Olalekan et al. [9] wrote a paper on construction arguments, highlighting that most existing study has centered on resolving disputes through litigation, adjudication, and alternate dispute resolution (ADR), underscoring a significant gap in preventive approaches.

The examination of the reviewed articles exposed that key kinds of databases were used. Information was gathered through literature reviews, questionnaires, interviews, case studies, or a mixture of these approaches. Notably, the studies covered construction claim study across various countries, reflecting a significant geographical diversity. This variation is expected, given the differing legal and political frameworks of construction sectors worldwide, which suggests that findings from one country may not necessarily apply to others. As a result, no studies specifically examining contract claims within the Kuwait construction sector were identified.

The analysis revealed that a majority of academic studies, despite differing emphases, consistently identified recurring factors contributing to claims within their specialized contexts. Notably, scholars like Ali et al. [10], Arditi et al. [11], and Yusuwan et al. [12] concentrated their investigations specifically on extension of time (EOT) claims. In contrast, Ballesteros et al. [13] constructed a predictive model by analyzing how adverse climate circumstances lead to work strikes and reduced output, ultimately causing project delays. Their prototype provides critical insights for anticipating weather-linked productivity declines during the planning phase, enabling proactive mitigation strategies.

The analysis highlighted divergent approaches in claim cause investigations across studies. While some scholars examined a narrow range of factors, others explored extensive catalogs of claim drivers, as illustrated in Table 1. Yousefi et al. [14] pinpointed many risk elements contributing to claims, organizing them into nine groups of knowledge areas in project management. Their methodology involved creating a probability-impact matrix and integrating the analytical hierarchy process (AHP) with artificial neural networks (ANNs) to predict claim occurrences in projects. In parallel, Chau [15] utilized ANN-based models to estimate claim settlement outcomes before legal proceedings. More recently, Mukilan et al. [16] developed an efficient claim management assurance system for EPC contracts using an improved monarch butterfly optimization algorithm, demonstrating the potential of metaheuristic approaches in automating and optimizing claim management processes. Meanwhile, Cakmak [17] applied the analytical network process (ANP) to identify contractor-related issues and their subcomponents as the dominant sources of contractual disputes within Turkey’s construction sector. These varied methodologies underscore the complexity of claim prediction and management across different analytical frameworks.

The examination of stakeholder perspectives on claim significance in construction revealed methodological contrasts between two studies. Iskandar et al. [18] and Mishmish et al. [3] both investigated variations in how distinct stakeholder groups prioritize claims, yet diverged in their approaches to data gathering. Iskandar et al. [18] employed survey-based questionnaires to capture stakeholder perceptions, whereas Mishmish et al. [3] combined documented case studies with questionnaire responses to analyze differences in claim prioritization. In addition, Deacon et al. [19] examined claim events from the perspective of contract administrators under the JBCC Principal Building Agreement in South Africa, emphasizing how contractual frameworks and local practices shape the perception and management of claim events. This methodological disparity highlights the diversity of tools available for assessing stakeholder viewpoints in construction dispute research.

Scholars have extensively studied the recurring sources of claims in specialized project contexts. For example, Nabi and El-Adaway [20] analyzed 40 interconnected claim drivers specific to U.S. modular construction projects, demonstrating that disputes in this sector stem from multifaceted issues rather than isolated factors. Complementing these studies, Ghosh and Karmakar [21] analyzed the causes of claims in highway construction projects through a detailed case study from a practitioner’s perspective, highlighting recurring issues such as delays, design deficiencies, and contractual ambiguities as critical drivers of claims. Similarly, Bakhary et al. [22] investigated contractual claim triggers in Malaysian infrastructure projects across transportation, oil, and gas industries. Their research highlighted critical challenges such as insufficient on-site staff awareness to identify claim opportunities, obstacles in retrieving contractual documentation, and adversarial negotiations between contractors and contracting authorities (CAs). In another study, Kisi et al. [23] evaluated transportation projects via questionnaire-based surveys, identifying variations, unforeseen site conditions, and project delays as the most frequent contractual claim categories. These studies collectively emphasize the complexity and context-dependent nature of claim causation across diverse project types and geographical regions.

In a comprehensive global study of contractual claim management, Shen et al. [24] analyzed claim causation across diverse project types, identifying three primary drivers. These include (1) external environmental risks such as socio-political instability, physical site challenges, and financial volatility; (2) client-side organizational practices like delayed payments, excessive change orders, and bureaucratic inefficiencies; and (3) contractual ambiguities stemming from ill-defined technical requirements or work boundaries. Their research demonstrated that the interplay of these elements—external uncertainties, client operational patterns, and contractual vagueness—can substantially influence the likelihood and severity of disputes in international project execution, emphasizing the need for proactive risk allocation and contract clarity.

In an initiative to integrate digital innovations into claim management frameworks, Ibraheem and Mahjoob [25] investigated building information modeling (BIM) as a solution to reduce disputes stemming from quantity estimation inaccuracies, frequent change orders, design flaws, documentation errors, and interdisciplinary communication gaps. Their research emphasized BIM’s capabilities, including 3D modeling, clash detection tools, multidisciplinary organization interfaces, and automated quantity take-off functions as mechanisms to preemptively resolve these challenges. The study was particularly notable for introducing structured claim management strategies in Iraq’s construction sector, where systematic approaches to contractual disputes were previously absent. By bridging gaps in documentation and design alignment, their work highlights how adopting advanced technologies like BIM could enhance operational transparency and collaborative workflows, thereby minimizing claim triggers in regions with underdeveloped contract management systems.

Focusing on sustainable construction practices in Turkey, Mohammadi and Birgonul [7] conducted a study to quantify the significance of risk categories influencing contractual disputes in green building projects. Through expert evaluations, they assessed the relative significance of factors across four domains: professional liability exposures, third-party certification uncertainties, financial vulnerabilities, and legal-contractual ambiguities. Their analysis, utilizing a relative importance index (RII), revealed that legal contractual risks were the predominant factor driving disputes among stakeholders in sustainable projects. This underscores the critical need for proactive risk identification and mitigation strategies during project planning phases to address ambiguities in contractual obligations and compliance standards specific to environmentally focused construction. The findings advocate for enhanced contractual clarity and adaptive risk frameworks tailored to the unique challenges of green building initiatives.

The synthesis of prior research underscores a concentrated scholarly focus on both the origins and predictive modeling of contractual claims in construction. However, this body of work reveals notable gaps, particularly the scarcity of contemporary investigations within the construction sector. Furthermore, cross-study comparisons of claim causation remain challenging due to inconsistent terminologies and categorization frameworks across existing research. To address these limitations, this study conducts a systematic content analysis of global case studies and academic literature, culminating in the development of a standardized cause of claims breakdown structure (CCBS). This framework systematically organizes 39 recurrent claim triggers documented in international projects, offering a harmonized taxonomy to enhance comparative analysis, risk assessment, and dispute mitigation strategies in diverse construction contexts, including regions like Kuwait where such methodological standardization has been absent.

This research contributes novel insights by advancing the analysis of globally recognized claim causes—identified through literature synthesis and content analysis—into a dual assessment of their likelihood and their perceived influence on critical project outcomes: schedule adherence, budgetary performance, and quality standards. Similar approaches have been recently adopted in the literature. Antoniou and Tsioulpa [26] proposed a comprehensive framework for assessing the delay, cost, and quality risks of claims in construction contracts, highlighting how a multidimensional evaluation of claim drivers can enhance understanding of their impact on project performance.

Bridging a methodological gap noted in Olalekan et al. [9], the study introduces a predictive risk assessment framework designed to prioritize claim drivers based on their probability-impact profiles. By translating theoretical findings into a practical mitigation tool, this work equips industry professionals with actionable strategies to preemptively address dispute triggers, thereby enhancing project resilience and aligning academic research with real-world risk management needs in construction practice.

The study addresses the following research questions (RQs) to evaluate both the likelihood and consequences of contractual claim drivers:

• Frequency of claims: How frequently do specific causes of claims arise in projects?
• Duration impact: What is the apparent influence of each claim reason on extending the project’s timeline?
• Cost overrun analysis: How do stakeholders perceive the effect of each claim trigger on escalating the project’s final expenses?
• Quality implications: To what extent are project quality standards compromised by these claim-related causes, as perceived by industry professionals?
• Risk prioritization: Which five claim causes, when assessed for their combined probability of occurrence and multidimensional impacts (time, cost, and quality), rank as the most critical threats to the successful performance of construction contracts?

These RQs aim to systematically quantify the prevalence and perceived severity of claim drivers, enabling the development of a risk-based framework to prioritize mitigation efforts and enhance contractual outcomes.

This research adopts a hybrid methodological framework, integrating qualitative and quantitative data collection through a structured questionnaire administered to 22 engineers currently practicing in Greece’s public construction sector, all of whom had active roles in procurement processes across multiple organizations. The survey instrument was designed based on insights synthesized from 50 peer-reviewed studies analyzing claim causation in public and private construction projects globally. Analytical techniques encompassed statistical summarization, internal consistency assessments (reliability testing), the calculation of a relative importance index (RII) to rank claim drivers, and probabilistic risk modeling to evaluate their implications. This approach ensures a robust, evidence-based understanding of claim dynamics within the unique regulatory and operational contexts.

Although the empirical data were collected in Kuwait’s public building sector, the study’s methodological apparatus—namely the cause of claims breakdown structure (CCBS) and the risk-based prioritization of claim drivers—remains transferable to other jurisdictions. Recent evidence shows that the anatomy of claims and disputes (e.g., payment issues, delay/disruption substantiation, price adjustment claims) recurs across different markets, albeit with context-specific prominence. Accordingly, practitioners in other countries can adapt the CCBS and the probability–severity benchmarks to their regulatory frameworks and delivery systems, enabling comparable prioritization and proactive mitigation.

The reset of this study is organized as follows: Section 2 specifies the methodological framework for constructing the cause of claims breakdown structure (CCBS), including the processes for data gathering and analytical techniques. Section 3 presents the findings and engages in a critical discussion of their implications within the context of existing literature. Section 4 synthesizes the study’s conclusions, acknowledges its constraints, and proposes directions for subsequent research to advance the understanding and management of claims in construction projects.

2. Study Methodology

2.1. Cause of Claims Breakdown Structure (CCBS)

It should be noted that while a number of studies have investigated claim causation in various international contexts, very limited research has specifically focused on the Gulf Region and the broader MENA context. For example, Mishmish and El-Sayegh [3] examined claim drivers in UAE road projects, and Zaneldin [27], Abdelalim et al. [28] explored claim types and frequency in the UAE. However, no comprehensive studies addressing the systematic categorization and prioritization of claim causes in Kuwait or neighboring Gulf countries were identified. This gap reinforces the novelty of the present study in providing evidence from Kuwait’s public construction sector.

Table 1 summarizes research that uncovered various claim causes using literature reviews, questionnaire surveys, and case studies. Each study subsequently classified and ranked these causes in its own way, and the number of causes examined varied between researchers. Developing a unified classification and coding system for claim causes in construction contracts could simplify the comparison of findings from international studies. A preliminary table was created to compare studies and their identified causes. Like other risk sources, the causes of claims can be systematically organized and coded to form a standardized representation, which not only enhances understanding, management, and communication at both project and industry levels but also simplifies the comparison of different research studies. A risk breakdown structure (RBS) is typically used as a hierarchical method to categorize risk sources. Accordingly [29], these factors were coded and organized within a cause of claims breakdown structure (CCBS), as depicted below. This structure provides a detailed yet comprehensive view of the main claim causes identified in the studies. Following the categorization framework suggested by Cakmak and Cakmak [17], the 15 factors were further sorted into five groups related to the contractual issues, project management factors, human factors, technical issues, and external factors. The CCBS typically consists of several key components, which can be organized into a hierarchical structure. These components may include:

Table 1. Literature review content study.

Research Scope	Authors (Year, Data Source)	Causes	Country
Bibliometric review of construction claim research	Olalekan et al. [9] (2021, LR); Mohammadi and Birgonu [7] (2016, Q); Cakmak [17] (2014, Q/CS)	0	International
Claims management	Abdul-Malak et al. [30] (2002, LR); Al-Sabah et al. [31] (2003, LR); Barman et al. [32] (2017, CS); Chan et al. [33] (2005, LR); Chan et al. [34] (2006, I); Cheung and Pang [35] (2013, LR); Cheung and Suen [36] (2002, LR/I); Cheung et al. [37] (2019, CS); Diekmann and Girard [38] (1995, Q/CS); Gardiner and Simmons [39] (1998, I/CS); Gould [40] (1998, Q); Ho and Liu [41] (2004, LR)	Various	Multiple (e.g., USA, UK, Turkey, Greece/UK)
Causes of claims	Ilter and Bakioglu [42] (2018, CS); Jahren and Dammeier [43] (1990, I); Kartam [44] (1999, LR); Kilian et al. [45] (2005, CS); Kululanga et al. [46] (2001, Q/CS); Kumaraswamy [47] (1998, LR/Q/CS)	Various	Multiple (e.g., Malaysia, Iraq, India, Turkey)
Dispute resolution	Ballesteros-Pérez [13] (2017, LR); Chau [15] (2007, LR); Cheung et al. [35] (2013, Q); Ren and Anumba [48] (2002, LR); Ren et al. [49] (2003, CS); Ren et al. [50] (2002, LR)	Various	Multiple (e.g., Spain, Hong Kong, UK)
Dispute development process	Mitropoulos and Howell [6] (2001, LR); Scott and Harris [51] (2004, Q/I); Semple et al. [52] (1994, CS); Stamatiou et al. [53] (2019, LR); Treacy [54] (1995, LR); Vidogah and Ndekugri [55] (1997, Q/I/CS); Viswanathan et al. [56] (2020, LR/Q); Wong and Maric [57] (2016, CS)	14	USA
Investment risks	Yogeswaran et al. [58] (1998, CS); Bakhary et al. [22] (2015, Q)	4	Turkey
Bibliometric review of construction claim research	Ren and Anumba [50] (2002, LR); Ren et al. [49] (2003, CS); Yuan and Ma [59] (2012, LR); Zaneldin [27] (2006, Q/CS)	Various	Not specified

LR = literature review; CS = case studies; I = interviews; Q = questionnaire.

Table 1. Literature review content study.

Research Scope	Authors (Year, Data Source)	Causes	Country
Bibliometric review of construction claim research	Olalekan et al. [9] (2021, LR); Mohammadi and Birgonu [7] (2016, Q); Cakmak [17] (2014, Q/CS)	0	International
Claims management	Abdul-Malak et al. [30] (2002, LR); Al-Sabah et al. [31] (2003, LR); Barman et al. [32] (2017, CS); Chan et al. [33] (2005, LR); Chan et al. [34] (2006, I); Cheung and Pang [35] (2013, LR); Cheung and Suen [36] (2002, LR/I); Cheung et al. [37] (2019, CS); Diekmann and Girard [38] (1995, Q/CS); Gardiner and Simmons [39] (1998, I/CS); Gould [40] (1998, Q); Ho and Liu [41] (2004, LR)	Various	Multiple (e.g., USA, UK, Turkey, Greece/UK)
Causes of claims	Ilter and Bakioglu [42] (2018, CS); Jahren and Dammeier [43] (1990, I); Kartam [44] (1999, LR); Kilian et al. [45] (2005, CS); Kululanga et al. [46] (2001, Q/CS); Kumaraswamy [47] (1998, LR/Q/CS)	Various	Multiple (e.g., Malaysia, Iraq, India, Turkey)
Dispute resolution	Ballesteros-Pérez [13] (2017, LR); Chau [15] (2007, LR); Cheung et al. [35] (2013, Q); Ren and Anumba [48] (2002, LR); Ren et al. [49] (2003, CS); Ren et al. [50] (2002, LR)	Various	Multiple (e.g., Spain, Hong Kong, UK)
Dispute development process	Mitropoulos and Howell [6] (2001, LR); Scott and Harris [51] (2004, Q/I); Semple et al. [52] (1994, CS); Stamatiou et al. [53] (2019, LR); Treacy [54] (1995, LR); Vidogah and Ndekugri [55] (1997, Q/I/CS); Viswanathan et al. [56] (2020, LR/Q); Wong and Maric [57] (2016, CS)	14	USA
Investment risks	Yogeswaran et al. [58] (1998, CS); Bakhary et al. [22] (2015, Q)	4	Turkey
Bibliometric review of construction claim research	Ren and Anumba [50] (2002, LR); Ren et al. [49] (2003, CS); Yuan and Ma [59] (2012, LR); Zaneldin [27] (2006, Q/CS)	Various	Not specified

LR = literature review; CS = case studies; I = interviews; Q = questionnaire.

A.

Contractual Issues

• A1. Ambiguities in contract language
• A2. Changes in scope
• A3. Delays in approvals

B.

Project Management Factors

• B1. Inadequate planning
• B2. Poor resource allocation
• B3. Ineffective communication among stakeholders

C.

External Factors

• C1. Weather-related disruptions
• C2. Regulatory changes
• C3. Economic fluctuations

D.

Technical Issues

• D1. Design flaws
• D2. Construction defects
• D3. Equipment failures

E.

Human Factors

• E1. Labor disputes
• E2. Skill shortages
• E3. Mismanagement of teams

2.2. Data Collection

In total, 22 completed questionnaires were obtained. All responses were checked for completeness, and since each item was set as compulsory (with the exception of the open-ended question), no questionnaires were excluded. Accordingly, all 22 surveys were considered valid and included in the analysis.

The survey respondents were selected using purposive sampling, aiming to capture the insights of professionals with substantial exposure to claim events in the Kuwaiti construction sector. The determination of sample size (22 valid responses) was guided by the principle of expert-based surveys in construction management research, where the emphasis is on respondent expertise rather than large statistical samples.

To ensure validity, participants were required to have a minimum of 10 years of professional experience in construction projects, including involvement in contractual and claim-related matters. While some respondents held only a first university degree (BSc), their extensive field experience—often exceeding a decade—qualified them to assess and justify claim causes reliably. Thus, the inclusion criteria were based primarily on years of practice and role responsibilities, rather than academic qualification alone.

The survey collected expert insights on 15 common factors leading to claims in construction projects, emphasizing: (a) the incidence of these factors, (b) their perceived impact on project timelines, (c) their perceived effect on overall project expenses, and (d) their supposed influence on the completed project.

The 15 factors included in the survey were not arbitrarily selected; they were derived from the outputs of the systematic literature review summarized in Table 1. Through this review, 39 claim drivers were initially identified across diverse international contexts (Asia, Europe, Middle East, North America). These were then consolidated and classified within the cause of claims breakdown structure (CCBS) (Section 2.1), from which 15 representative and recurrent factors were shortlisted for empirical assessment. While the sources covered a global scope, no prior comprehensive study on Kuwait was found, which highlights the relevance of applying this standardized set of factors in the Kuwaiti context. The study adopted a research design [60,61], integrating qualitative insights from expert opinions with quantitative data gathered through closed-ended survey responses. Quantitative analysis techniques, including Likert scale scores, RII, and risk value calculations, were applied to analyze the data. This methodology sought to quantitatively identify trends, attitudes, or opinions within a specific population, leveraging the qualitative perspectives of specialist participants in place of relying on real claims data from projects. This study-based approach, often termed “knowledge mining,” has been employed in construction research by the scholars to gather expert and practitioner insights on various topics. These include factors contributing to delays [62], cost overruns [63], contract forms [64], procurement systems [65,66], project manager attributes [67], and obstacles to building energy upgrades [68], safety management practices [69], and challenges in claims management [22].

The survey instrument was structured mainly with multiple-choice questions. The first segment comprised items designed to gather demographic and personal background information from participants, who were practicing engineers representing diverse engineering disciplines. The subsequent section centered on analyzing the root causes of claims in projects, assessing four critical dimensions: (1) how frequently such claims arise, (2) their influence on project timelines, (3) their effect on overall project costs, and (4) their implications for the quality of deliverables. This evaluation was conducted using a five-point Likert scale framework, supported by complementary scoring methodology: 1—never, 2—rarely, 3—often, 4—many times, and 5—always.

The participants expressed their level of agreement with every item using predefined measures, which were final converted into algebraic values ranging from 1 to 5 for analysis in SPSS. Furthermore, the questionnaire comprised an optional open-ended query inviting respondents to suggest strategies for reducing claims in public construction contract management.

From the outset, it was decided to target the questionnaire toward experts rather than the widespread public, given the specialized topic, which required expertise in contracting. Experts with experience in managing construction projects are more likely to have encountered contractual claims and disputes, allowing them to accurately identify their root causes. The authors utilized industry connections by sending private messages to inform potential participants about the survey’s objective. This convenience sampling method was implemented through LinkedIn posts and personal invitations sent via Messenger. The questionnaire was dispersed via Google Forms and was administered through 2024.

2.3. Data Analysis Methodology

The questionnaire data were examined by SPSS statistical software (version 28). When examining the Likert measure questions, it became clear that the mean was not particularly useful due to a clustering of responses around the neutral option. Therefore, the analysis shifted to calculating (RII) for each variable. This RII was then employed in a risk analysis to determine the risk value (RV), which assessed the impact of each contractual claim cause on project duration, cost, quality, and overall performance.

The relative importance index (RII) is widely used in construction studies to evaluate how recognized delay issues affect project time and cost increases [70,71,72,73,74], to rank the importance of various elements to facilitate analyses across different studies [75].

In this study, Microsoft Excel was utilized to calculate the RII using Equation (1) modified from Holt [76]. This calculation was performed for each of the 60 variables—derived from 15 causes across 4 research questions—each evaluated on a five-point Likert measure.

The relative importance index (RII) is calculated using the following formula:

$$\mathrm{R}\mathrm{I}\mathrm{I}={\sum }_{a=1}^m\left({\displaystyle \frac{\mathrm{P}\mathrm{i}\times \mathrm{U}\mathrm{i}}{\mathrm{n}\times \mathrm{N}}}\right)$$

(1)

Here is what each term represents:

• m: The number of digits on the scale. In this case, (since the scale ranges from 1 to 5);
• P_i: The rating values, which take on values from 1 to 5, indicating increasing levels of frequency;
• U_i: The number of respondents who selected each rating P_i;
• N: The total number of respondents;
• n: The possible rating on the scale, which is also 5 in this case.

Essentially, the RII aggregates the weighted responses (where each weight is a rating value multiplied by the number of respondents selecting that value) and normalizes this sum by the product of the highest rating and the total number of respondents.

It is important to mention that every question was compulsory—aside from the open-ended item—so that no responses were missing. Consequently, the RII varied between 0 and 1, representing a degree of the likelihood that a specific claim cause might occur. The minimum possible RII was 0.2, which would result if every respondent chose “never”.

Risk examination complemented the RII evaluation; while RII is active for rating the different causes of claims based solely on their detected frequency, it does not capture the value of their effect or the particular vulnerabilities that a construction project might face for each cause. Therefore, on its own, RII does not provide all the necessary insights for a comprehensive risk assessment of contractual claims in a project.

Risks in the effective completion of a construction contract are associated with uncertain events or conditions that could arise, potentially affecting the project’s objectives in both beneficial and detrimental ways. In this context, the reasons of claims are treated as risks that, if they happen, may adversely influence the project’s ability to be delivered on time, stay within the allocated budget, and meet the expected quality standards.

In this framework, risk is seen as a multidimensional concept that can be approximated using a single point estimate—the expected value, which is determined by multiplying the probability (P) of a claim cause occurring by its potential significance, severity (S) if it occurs. Therefore, the risk value (RV) associated with a particular source of claim can be estimated using the following equation:

RV = P_i × S_i

(2)

3. Results and Discussion

3.1. Personal Characteristics

Figure 1, Figure 2 and Figure 3 outline the demographic details and professional backgrounds of the participants. Every respondent had experience managing public contracts, having served as an engineer for construction contractors, for the contracting authority (CA), or in both roles. Specifically, (78.3%) participants reported experience in construction contract management as civil and architecture engineers, while 70.7% of participants indicated they had worked as civil engineers for the CA. Additionally, 50% of the respondents had experience in both positions. Overall, the sample was composed of professionals with extensive expertise in managing construction contracts.

As shown in Figure 3, participants reported experience across different types of construction projects. Since respondents were allowed to select more than one category, the percentages represent the proportion of respondents with experience in each category rather than summing to 100%. Out of the 22 participants, 10 indicated expertise in two types of projects, 6 in three types, and 2 in four or more types. This overlap highlights that many engineers had multidisciplinary exposure rather than a single specialized track.

In addition to academic and professional background, the survey also captured respondents’ work experience. On average, participants reported between 10 and 20 years of professional experience, with the majority having more than a decade in public construction projects. While most respondents’ professional activities were concentrated within Kuwait, approximately 25% indicated prior experience in other Middle Eastern countries, which provided them with a broader regional perspective on contractual claims.

3.2. Relative Importance Indices (RII)

The Cronbach’s alpha consistency index was determined for every of the four research questions by incorporating the 15 identified causes from the literature. The analysis revealed a strong internal consistency within the dataset, as indicated in Figure 4, with the Cronbach’s alpha standards surpassing 0.7 for all cases [77].

The assessment of the resulting relative importance index (RII) was conducted using an arrangement modified from Chen et al. [78] to align with the assessment scale utilized in the survey with high values exceeding 0.8.

Table 2. Numerical outcomes of study questions 1 to 4.

Code	Factor	No. of Occurrences in Literature	Frequency of Occurrence (Mean, RIIi)	Impact on Time (Mean, RIIid)	Impact on Cost (Mean, RIIic)	Impact on Quality (Mean, RIIiq)
A1	Ambiguities in contract language	28	3.73 (0.75)	3.77 (0.75)	3.91 (0.78)	2.82 (0.56)
A2	Changes in scope	14	3.05 (0.61)	3.82 (0.76)	3.23 (0.65)	2.45 (0.49)
A3	Delays in approvals	23	2.41 (0.48)	3.05 (0.61)	3.00 (0.60)	2.55 (0.51)
B1	Inadequate planning	24	3.32 (0.66)	3.82 (0.76)	3.41 (0.68)	2.86 (0.57)
B2	Poor resource allocation	22	3.41 (0.51)	3.91 (0.61)	3.18 (0.65)	2.73 (0.81)
B3	Ineffective comm. among stakeholders	11	2.82 (0.68)	3.82 (0.78)	3.27 (0.64)	3.45 (0.55)
C1	Weather-related disruptions	17	3.23 (0.65)	3.86 (0.77)	3.59 (0.72)	3.23 (0.65)
C2	Regulatory changes	12	3.23 (0.65)	3.36 (0.67)	3.50 (0.70)	2.91 (0.58)
C3	Economic fluctuations	8	3.14 (0.63)	3.23 (0.65)	3.23 (0.65)	2.64 (0.53)
D1	Design flaws	11	2.68 (0.54)	2.91 (0.58)	3.00 (0.60)	2.64 (0.53)
D2	Construction defects	17	2.18 (0.56)	3.68 (0.76)	3.36 (0.65)	3.55 (0.69)
D3	Equipment failures	10	2.27 (0.44)	3.18 (0.74)	3.05 (0.45)	3.09 (0.71)
E1	Labor disputes	13	3.73 (0.45)	3.77 (0.64)	3.91 (0.61)	2.82 (0.62)
E2	Skill shortages	13	3.05 (0.51)	3.82 (0.64)	3.23 (0.69)	2.45 (0.61)
E3	Mismanagement of teams	9	2.41 (0.50)	3.05 (0.63)	3.00 (0.60)	2.55 (0.59)

, Figure 5, Figure 6, Figure 7 and Figure 8 present the mean, and RII index for respondents’ answers to Research Questions 1 through 4, along with the frequency that each cause appeared in the studies. Analyzing the occurrence of claim causes based on their professional experiences, it was found that the most commonly mentioned cause in the Kuwait construction industry was “ambiguities in contract language (A1)” with an RII of 0.75. In response to Research Question 2, the factor that most significantly impacted project duration was “ineffective communication among stakeholders (B3)”, which had an RII of 0.78. Moreover, for Research Question 3, when evaluating the influence of various causes on total project cost, “ambiguities in contract language (A1)” exhibited the greatest effect, with an RII of 0.78. Finally, responses to Research Question 4 revealed that “poor resource allocation (B2)” was the primary factor affecting the quality of final projects in the Kuwait construction sector, with an RII of 0.81.

Table 3. Top causes of claims in terms of impact on duration, cost, and quality.

Frequency	(RIIi)	Rank	Duration	(RIIid)	Rank	Cost	(RIIic)	Rank	Quality	(RIIiq)	Rank
A1	(0.75)	1	B3	(0.78)	1	A1	(0.78)	1	B2	(0.81)	1
B3	(0.68)	2	C1	(0.77)	2	C1	(0.72)	2	D3	(0.71)	2
B1	(0.66)	3	A2	(0.76)	3	C2	(0.70)	3	D2	(0.69)	3
C1	(0.65)	4	B1	(0.76)	4	E2	(0.69)	4	C1	(0.65)	4
C2	(0.65)	5	D2	(0.76)	5	B1	(0.68)	5	E1	(0.62)	5
C3	(0.63)	6	A1	(0.75)	6	A2	(0.65)	6	E2	(0.61)	6
A2	(0.61)	7	D3	(0.74)	7	B2	(0.65)	7	E3	(0.59)	7
D2	(0.56)	8	C2	(0.67)	8	C3	(0.65)	8	C2	(0.58)	8
D1	(0.54)	9	C3	(0.65)	9	D2	(0.65)	9	B1	(0.57)	9
B2	(0.51)	10	E1	(0.64)	10	B3	(0.64)	10	A1	(0.56)	10
E2	(0.51)	11	E2	(0.64)	11	E1	(0.61)	11	B3	(0.55)	11
E3	(0.50)	12	E3	(0.63)	12	A3	(0.60)	12	C3	(0.53)	12
A3	(0.48)	13	A3	(0.61)	13	D1	(0.60)	13	D1	(0.53)	13
E1	(0.45)	14	B2	(0.61)	14	E3	(0.60)	14	A3	(0.51)	14
D3	(0.44)	15	D1	(0.58)	15	D3	(0.45)	15	A2	(0.49)	15

presents the top 15 ranked causes for each research question, emphasizing both the most commonly occurring issues and those deemed to have the greatest impact influence on project duration, cost, and quality. Interestingly, although “ambiguities in contract language (A1)” emerged as the most frequent cause, it was only significantly associated with cost (RII = 0.78) and duration (RII = 0.75), not quality. In contrast, “poor resource allocation (B2),” was identified as having the highest perceived impact on project quality. These causes are among the top ten claims that public work clients should work to avoid. The following section provides a detailed analysis of the risk findings related to all causes.

3.3. Risk Analysis

The level of risk involves both the probability of an event happening and the potential impact it may have. To determine probability values (P), the RII index was calculated based on how frequently respondents identified the causes, as shown in Table 3. The severity of impact (S) value is inherently particular and depends on the decision-maker’s risk tolerance and the unique conditions of each project. In this research, the RII indicators were derived from respondents’ assessments of the degree to which each cause influenced the project’s time (RIIid), cost (RIIic), and quality (RIIiq), as presented in Table 3. Subsequently, the risk values pertaining to time (RVd), cost (RVc), and quality (RVq) of the final scheme were determined using the following formulas:

RVD = Pi × Sid = RIIi × RIIid,

(3)

RVC = Pi × Sic = RIIi × RIIic,

(4)

RVQ = Pi × Siq = RIIi × RIIiq

(5)

The probability and severity of each claim factor were assessed using a 5-point Likert scale. To ensure consistency, the scales were benchmarked against commonly adopted risk management practices in construction studies [79,80]. Probability was defined as: 1 = very unlikely (<10%), 2 = unlikely (10–30%), 3 = possible (31–50%), 4 = likely (51–80%), and 5 = almost certain (>80%). Severity was defined in terms of potential impact on project performance: 1 = negligible (minimal cost/time/quality effect), 2 = minor (noticeable but manageable), 3 = moderate (requires intervention, e.g., 1–3 months delay), 4 = major (significant, e.g., 3–6 months delay or >10% cost increase), and 5 = severe/catastrophic (project failure risk, >6 months delay or >20% cost increase). These benchmarks provided respondents with a standardized frame of reference when assigning their evaluations.

Table 4. Ranking by risk values on project time, cost, and quality.

CCBS Code	RVDi	Rank RVDi	RVCi	Rank RVCi	RVQi	Rank RVQi	TRV1	Rank TRV1	TRV2	Rank TRV2
A1	0.56	1	0.59	1	0.42	2	0.53	1	0.55	1
A2	0.46	5	0.40	10	0.30	12	0.41	7	0.39	7
A3	0.29	13	0.29	14	0.24	14	0.28	14	0.28	14
B1	0.50	3	0.45	4	0.38	4	0.46	4	0.45	3
B2	0.31	11	0.33	12	0.41	3	0.34	10	0.35	9
B3	0.53	2	0.44	5	0.37	5	0.47	3	0.44	4
C1	0.50	4	0.47	3	0.42	1	0.48	2	0.47	2
C2	0.44	6	0.46	2	0.38	6	0.43	5	0.45	5
C3	0.41	7	0.41	7	0.33	10	0.39	8	0.40	6
D1	0.31	10	0.32	13	0.29	13	0.31	12	0.31	12
D2	0.43	8	0.36	9	0.39	8	0.40	6	0.38	8
D3	0.33	9	0.20	15	0.31	11	0.29	13	0.26	15
E1	0.29	14	0.27	16	0.28	15	0.28	15	0.28	13
E2	0.33	12	0.35	11	0.31	9	0.33	11	0.34	10
E3	0.32	15	0.30	15	0.30	12	0.31	12	0.31	11

displays the calculated risk values (RVD, RVC, RVQ) along with their rankings based on the assessed risks for project time (Rank RVD), total project cost (Rank RVC), and project quality (Rank RVQ). The three causes identified as carrying the highest risk for project duration, cost, and quality were “ineffective communication among stakeholders (B3),” “ambiguities in contract language (A1),” and “poor resource allocation (B2)”, as presented in Table 3. Among these, only “ambiguities in contract language (A1)” was viewed as having the most substantial impact with an RII of 0.75, while “poor resource allocation (B2)” ranked 10th with a notable RIIi value of 0.51. It is clear that ambiguities in contract language require time to implement, and design modifications necessitated by additional measures will also require extra time for completion. Similarly, poor resource allocation faced by the contractor will necessitate adjustments in resource planning, which will ultimately affect project progress. Lastly, any delays in work progression will negatively impact project completion.

When examining the riskiest causes of claims related to duration and rising project costs, “ambiguities in contract language (A1)” again topped the list. Interestingly, “regulatory changes (C2)” ranked second, followed by “weather-related disruptions (C1)” in third place concerning their risk value. This suggests that change orders and weather present a greater risk for cost overruns than payment-related issues. To mitigate significant impacts on project quality, it is crucial to implement preventive measures against claims arising from “weather-related disruptions (C1),” “ambiguities in contract language (A1),” and “poor resource allocation (B2).”

An effort was made to consolidate the findings to identify which causes exhibited the top overall risk level by taking into account all three risk values (RVD, RVC, and RVQ). To do this, weights were assigned to each risk level based on the consequences of the discrete risk values across the three variables, utilizing two distinct scenarios. In the first scenario, a weighting influence of 70% was assigned to project duration (wd), while 15% was allocated to total cost impact (wc) and 15% to quality impact (wq). This indicates that the decision-maker prioritizes the effect on duration over cost and quality. Conversely, in the second scenario, the weighting factors for the influences on duration, cost, and quality of the final project are measured as equally distributed, with each set at 33.3%.

Table 4 illustrates the outcomes of both Scenario 1 and 2, showing the ranking of all reason based on the calculated total risk value (TRV), which is determined by the following equation:

TRVi = wd × RVDi + wc × RVCi + wq × RVQi,

(6)

It is noted that both situations identified the same top five most significant causes of contractual claims that influence overall project performance, although in a varied sequence. These causes included “ambiguities in contract language (A1)” at the top, followed by “weather-related disruptions (C1),” “ineffective communication among stakeholders (B3),” “inadequate planning (B1),” and “regulatory changes (C2).”

3.4. Expert Suggestions for Mitigation Measures

The survey comprised an open-ended question asking respondents for their views on how to reduce or manage claims in public construction contracts. One respondent proposed that improving communication about project details and site conditions during the financial proposal stage, along with cultivating a cooperative relationship between the contractor and the contracting authority, might be effective. Another respondent suggested the adoption of precise rules, detailed specifications, and comprehensive studies. Additionally, another participant stressed the importance of enhanced designs and more complete contract documents, and advocated for greater professionalism and proper training. Many respondents emphasized the need for robust design planning, timely acquisition of land, sustained financial flow throughout the project, and prompt, effective responses from the contracting authority. Moreover, one participant pointed out that improved designs should be supported by ongoing oversight from the designer during the construction phase.

Some participants emphasized the importance of bolstering preparations during the pre-contractual phase for all related issues. Meanwhile, others recommended adopting a design–build tendering approach. In contrast, drawing on their public works experience, some pointed out that the body formerly known as the Amicable Settlement Committee—now called Arbitration—could serve all parties well.

The participants offered these suggestions without knowing the risk assessment results, which were based on their own evaluations of how often and how severely various issues occur. Among all the proposals, only four participants presented mitigation strategies addressing four of the five highest-risk issues recognized in the study. Specifically, participants proposed measures to prevent claims related to “ambiguities in contract language (A1)” and “weather-related disruptions (C1)” by recommending the development of detailed rules and specifications, enhanced designs, and more comprehensive contract documentation. Additionally, they emphasized that maintaining a steady financial flow throughout the project is crucial for mitigating “regulatory changes (C2),” which could help prevent the “ineffective communication among stakeholders (B3).” However, none of the participants offered any suggestions specifically aimed at preventing “inadequate planning (B1).”

4. Conclusions

Drawing on RII values derived from specialist opinions, this study suggests specific probability and impact severity figures for 15 common claim causes in Kuwait’s public construction sector. These figures can be used to compute risk values (RVs), offering Kuwait stakeholders practical guidance when planning mitigation strategies to address the effects of contractual claims on project performance. By ranking these causes according to their total risk value (TRV), the study identifies which contractual claims most significantly affect construction project outcomes in Kuwait. In direct response to the research question, the analysis indicates that the five highest-risk causes of construction claims impacting overall project performance are “ambiguities in contract language (A1)” at the top, followed by “weather-related disruptions (C1),” “ineffective communication among stakeholders (B3),” “inadequate planning (B1),” and “regulatory changes (C2).”

This study contributes to both theory and practice in construction claim management. From a theoretical perspective, it advances existing research by developing a cause of claims breakdown structure (CCBS) that consolidates widely reported claim drivers from international literature and systematically categorizes them into a unified framework. Furthermore, the study applies a risk-based prioritization approach, combining frequency and severity through expert-informed indices, to evaluate claim drivers across their impact on cost, time, and quality. Moreover, the study significantly enhances the literature on the reasons for claims in the projects by being among the first to concurrently evaluate expert opinions on both the frequency of these claims and their perceived impacts on project schedules, overall costs, and quality. In doing so, it fills an important gap in current research. Furthermore, the study introduces a cause of claims breakdown structure (CCBS) that compiles the greatest common reasons for claims observed in real-world projects globally, as identified through the literature. This framework can aid international researchers in comparing findings and drawing more comprehensive conclusions.

From a practical standpoint, the findings provide contract administrators, project managers, and policymakers in Kuwait with an evidence-based tool to anticipate, rank, and mitigate the most critical claim causes, such as variations, delays in approvals, and design deficiencies. This will enable more proactive claim management, reducing disputes and enhancing project performance.

Despite its valuable contributions, the study has several limitations. It does not concentrate on specific types of construction and depends entirely on expert opinions. As a result, the research would be strengthened by validating its findings against current project claims and by administering a survey to a larger pool of construction industry stakeholders. Future investigations could also benefit from employing factor and variance analyses to determine the independence of the individual claim causes and to examine whether there are differing viewpoints among various groups, such as contracting authorities, contractors, and designers. Additionally, broadening the scope to contain expert opinions and data from projects could reveal whether important changes exist between public and private projects.

Despite these limitations, the paper’s findings provide a basis for developing an optimal and streamlined method for dispute prevention—an area notably underexplored in the literature. The study team expects to address the identified challenges by integrating advanced technologies. For instance, leveraging building information modeling (BIM) and smart contracts could automate processes like progress payments, thereby improving the management of work progress delays and associated extension of time (EOT) claims. Additionally, BIM features such as 3D conception, clash detection, organization, and quantity estimation would help reduce issues related to changes in quantities, or scope, as well as design quality deficiencies. Lastly, incorporating criteria into tender processes to avoid selecting contractors who exhibit signs of financial instability may help mitigate claims arising from a contractor’s financial failure.

Finally, the study addresses a significant gap in prior research, as few empirical investigations have been conducted in the Gulf and MENA region, and none comprehensively focused on Kuwait. By offering both a systematic classification and a contextualized assessment, the research provides novel insights and a transferable framework that can inform future studies and professional practice in similar regional settings.