Claim Management and Dispute Resolution in the Construction Industry: Current Research Trends Using Novel Technologies

1. Introduction

In every agreement where multiple parties are involved, disputes appear as a natural phenomenon, even if the surrounding conditions are perfect [1]. Accordingly, the case could not be any different in the construction industry, where an extremely complex and multidimensional environment is observed, and various professionals are involved during a construction project [1,2,3]. Cheung and Yiu [4] argue that dealing with disputes is part of an engineering manager’s portfolio. The stakeholders responsible for the emergence of conflicts, claims and disputes in the process of a construction project are the owner, the consultant engineer and the contractor or subcontractors [3]. As Naji et al. [5] observe, the terms conflict, claim or dispute are often mentioned in the relevant literature as synonyms, despite this not being entirely accurate. A conflict arises when the same situation is viewed differently according to each involved stakeholder’s perspective [5]. According to Mishmish and El-Sayegh [6], a claim can be defined as a request for compensation for damages incurred by any party to the contract and can refer to either a time extension or money reimbursement. In case a claim is made by one party and rejected by the other, then this situation results in a dispute [2,7], which needs to be resolved in order for the construction process to resume. Therefore, the submission and rejection of a claim can be seen as the start of dispute evolution [5].

Disputes arising in the construction industry induce negative impacts on a construction project since they require resources which could be spent more productively [2], lead to cost and time overruns [1,2,3,6,8], and could also generate problems in the involving parties’ working relations, which could even cause these relations to rupture [2,6]. The causes for such claims and disputes have been thoroughly investigated throughout the literature, and a variety of classifications and taxonomies exist. The categorization presented by Cakmak and Cakmak [9] revealed that there are seven main causes of claims related to the contracting authority (owner), the contractor, the design, the contract, human behaviour, the project, and external factors. Figure 1 presents a risk breakdown structure of 39 causes of claims (risk factors), which provides a comprehensive view of the hierarchy of the predominant causes of claims based on Cakmak and Cakmak’s categorization, as were studied in the research by Antoniou and Tsioulpa [10], resulting in a Causes of Claims Breakdown Structure (CCBS). Remarkably, the causes leading to construction claims and disputes have not changed significantly throughout the years [1]. According to the 2021 ARCADIS report [11], the overall dispute cause for the year 2021 was that the owner/contractor/subcontractor failed to understand and/or comply with its contractual obligations. This situation, along with the issue of poor claims documentation, are considered the two main reasons for construction disputes [1].

As stated before, whenever such disputes occur, the construction process inevitably pauses, and corresponding actions should be taken so that the disputes are resolved, and the process may resume. Disputes in the construction environment may be resolved by various methods, such as negotiation, litigation, arbitration, mediation, or any alternative dispute resolution method [2,8,11]. Litigation at courts, the traditional dispute resolution method used by public owners [8], is considered a time- and cost-consuming method [2], and private owners prefer the alternative dispute resolution methods (ADR) [8].

The purpose of this perspective paper is to explore the current research trends regarding claim management and dispute resolution in the construction industry, identify any research gaps and provide suggestions for future research directions in order to assist researchers and construction professionals in their efforts to address more efficiently construction disputes and their negative impacts on project performance.

Following this introductory section, Section 2 describes the approach used to conduct this research, and Section 3 presents the results with respect to the overall trend of research by publication year, journal, geographic location, co-authorship, and main research areas. Furthermore, a co-occurrence keyword analysis is conducted, revealing six main research themes, identifying the emergence of novel technologies such as BIM, Blockchain and Smart contract related to the investigation into claim management and dispute resolution in the construction industry, and, subsequently, a content analysis of the papers published during 2020-2022 is conveyed in Section 4. Finally, the main research trends and potential research directions for enhancing claim management and dispute resolution practices in the construction industry are discussed in section 5. In Section 6, the conclusions of this paper are presented, highlighting the most important findings of this research.

2. Methodology

This study adopts the science mapping technique in order to explore the existing literature regarding construction claims and dispute resolution methods employed in construction projects. The science mapping technique consists of bibliometric analysis, scientometrics and informatics; the bibliometric analysis focuses mainly on the literature per se, while scientometrics is used to measure and analyze the literature results, and, through informatics, these results can be visualized to detect not only the practices used by researchers, as well as the intellectual structure of a scientific field [12,13]. The publication and citation characteristics of construction claims and dispute resolution methods research were examined in terms of country, source, and author based on bibliographic coupling and citation analysis. Then, keyword co-occurrence analysis was conducted to detect the research topics and temporal trends, as well as the gap in research related to claims and dispute resolution methods in the construction industry. Finally, the authors performed a manual content analysis of the recently published studies related to this research field, allowing further analysis and classification of the current research trends regarding claim and dispute resolution methods in construction industry research.

Among the various existing science mapping tools, VOSviewer, BibExcel, CiteSpace, CoPalRed, Sci2, VantagePoint, and Gephi [12], VOSviewer was selected for this quantitative analysis as it is one of the most recommended mapping and visualization tools which can illustrate data obtained from bibliographic databases, such as Scopus or Web of Science, in a great visualized form and also has special features concerning text-mining [13]. Supplemental to VOSviewer, OpenRefine (version 3.5) software was also employed to improve the data obtained from the selected bibliographic database along with a thesaurus file. This procedure resulted in correcting errors and typos, as well as arranging similar terms into clusters regarding the co–occurrence author keyword analysis.

The Scopus (Elsevier) database was selected among the alternative available academic digital databases for scientometric analysis due to it being one of the most comprehensive ones, including a greater number and broader range of indexed publications in the engineering discipline and being more user-friendly [14] compared to the Web of Science database, without presenting double citation counting problems as is often the case with the Google Scholar database. The following statement was entered on the Advanced Search area in Scopus: TITLE-ABS-KEY (disput*) OR TITLE-ABS-KEY (“construction claim*”) AND ALL (“construction management”). The wildcard “*” denotes the fuzzy search strategy that is used to capture term variation [15]. After this initial search, the results were then filtered in order to select journal articles and papers published in conference proceedings written in English. Finally, this approach resulted in retrieving 791 documents, including 543 journal articles (69%) and 248 conference papers (31%), published between 1983 and 2022 (retrieved online on November 22, 2022), which were selected for this analysis.

The distribution of annual publications from 1983 to 2022 is shown in Figure 2, where it is easily observed that the number of annual publications started increasing after 2007 and, especially in the past five years, resulting in almost 43% of the entire relevant documents being published. The whole set of 791 publications received a total of 9,762 citations, an average of 12 citations per paper. The increasing number of published documents also indicates that claim management and dispute resolution in construction industry research has attracted extensive attention in the past fifteen years, indicating the importance of the impact claims possess in the construction industry.

Following the bibliometric analysis that was essential for determination, a content analysis of 27 research articles published in the past three years was conducted to determine the proposed future research directions. The widely accepted Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) method was followed for the selection of the studies for content analysis [16]. Figure 3 shows the adapted PRISMA flowchart of the process for the screening and selection of the relevant studies, which was conducted in four stages (identification, screening, eligibility, and inclusion).

3. Bibliometric Analysis

After selecting the data from the Scopus database, they were then exported in a .csv file (comma-separated values file) for further analysis through VOSviewer. This section presents the analyses carried out using VOSviewer to detect the most influential countries, the top highly cited publications sources (journals and conference proceedings), the most prominent researchers and authors and the main research areas.

The analyses carried out employing VOSviewer produce maps, which normally contain only one type of item (i.e., publications, researchers, countries, terms, or sources) and the potential relations or connections between any pair of items are called links, such as bibliographic coupling links between countries, or co-occurrence links between terms, etc. A map typically includes only one type of link. Any pair of items can be connected with only one link, which has a strength represented by a positive numerical value. The higher the value, the stronger the link. For instance, in the case of co-occurrence links between two terms, the strength of a link indicates the number of publications in which two terms occur together. Items and their links constitute a network. Items can have weight and score attributes, which are presented by numerical values. Weight attributes indicate the importance of an item, and there are two standard weight attributes· Links and Total link strength. The Links attribute shows the number of links of an item with other items, whereas the Total link strength indicates the total strength of the links of an item with other items. Presenting the abovementioned basic terms is essential to understand the following results produced via the VOSviewer software [17].

3.1. Country Analysis

All construction projects are prone to conflict [18]. The reasons for the claims occurring due to such conflicts, as well as the means of resolving these disputes, are researched throughout the world. In order to identify the most significant contributions of a country in this research field, the type of analysis was selected as bibliographing coupling, meaning the relatedness of countries is determined based on the number of references they share [17], with the limitation of at least five documents per country. As a result, of the 65 countries where at least one relevant study has been published, 31 met the threshold. The magnitudes concerning documents, citations, average citations per document and total link strength with respect to the five most influential countries, Australia, Hong Kong, USA, United Kingdom, and China, are illustrated in Table 1. At the same time, all 31 of them are shown in Figure 4, visualized in 5 groups (clusters).

3.2. Publication Sources Analysis

In total, 791 papers were published in 218 journals and conference proceedings according to the citation analysis, meaning the relatedness of the publication sources is determined based on the number of times they cite each other [17]. The limitations this time were that at least 1 document must have been published from each source, and also, this source must have been cited at least five times. Of the 218 sources, 106 met these thresholds. The latter’s top 5 according to Total Link Strength, which indicates the total strength of the links of the journals with other journals, are illustrated in Table 2, along with data concerning published documents, citations, total link strength and Scopus Quartile per source, according to November 2022 SCImago Journal Rank (SJR) statistics. “The Journal of Legal Affairs and Dispute Resolution in Engineering and Construction” has published the most documents (84 articles), and the journals “Journal of Construction Engineering and Management” and “Construction Management and Economics” contribute the most to this research field in terms of their total link strength.

3.3. Author Analysis

Over the investigative period, a total of 1512 authors have published at least one paper related to the examined research field. Attempting to detect the researchers who have contributed the most to the research regarding claim management and dispute resolution in the construction industry, citation analysis was conducted through VOSviewer software, selecting “Authors” as the unit of analysis, meaning the relatedness of the authors is determined based on the number of times they cite each other. The thresholds this time were that each author had at least five papers published and had been cited at least five times. These limitations resulted in detecting 38 authors, with 37 of them being connected, as illustrated in Figure 5.

VOSviewer software provides the tool to map the selected network of authors according to the average years concerning the papers they have published, translated in colour. In particular, the authors highlighted in yellow are the ones having published more recent publications (i.e., Gunduz M. and Abwunza A.A.). In contrast, the authors highlighted in green, blue, and purple are those having relatively earlier contributions to the examined field (i.e., Cheung S.O., Love P.E.D. and El-Adaway I.H.). Table 3 illustrates the number of the top 5 authors’ papers related to this research field and the number of citations, sorted as per total link strength. In Table 3, one can observe that Cheung S.O. has published the most papers related to the examined field (45), and Yiu T.W. and Fenn P. were the ones whose publications had the highest number of average citations.

3.4. Main Research Areas (Co-Occurrence of Keywords Analysis)

For the keyword analysis of this study, a co-occurrence network of author keywords was created using VOSviewer. Applying this type of analysis means that the relatedness between keywords is determined based on the number of publications in which they occur together [17]. Mapping a network of related keywords, through which the core content of published papers is represented, provides researchers with an accurate picture of scientific knowledge production in terms of patterns, relationships, and intellectual organization of the research themes covered [12]. VOSviewer created the network by setting the minimum number of occurrences of a keyword to 10 after supplementary data processing via OpenRefine, and a thesaurus file was created according to the initial results of the keyword analysis. The purpose of this data processing lies in merging similar terms, as well as correcting errors and typos of terms.

This process resulted in the network being visualized in two forms in Figure 6 and Figure 7. The network consists of 52 nodes (keywords) and 583 links organized in 5 clusters. The visualization in Figure 6 is per average publication year, whereas the one in Figure 7 is a density visualization map. The size of each point depends on the density of the number of items at that point, and the keywords in the different clusters are displayed in different background colours. Furthermore, keywords that are grouped into the same cluster may reflect more related research areas [19] and the keywords “construction disputes and conflicts” and “claims and disputes” are, as was expected, the most repeated ones, interconnecting all 5 clusters. Both visualizations reveal that the terms “blockchain”, “smart contracts”, “building information modelling (BIM),” and “claim management” appear only recently in the past three years in the literature with regards to construction claims and disputes research area. Attempting to shed light on the manner in which these concepts relate to construction claims and disputes, the recent documents published during the last three years were further investigated, leading to the content analysis described in the next section.

4. Content Analysis of the Most Recent Publications

As was revealed in Figure 2, a significant amount (341 documents) of the related literature was published during the last five years, indicating the researchers’ growth of interest in this research field. Conducting a preliminary screening of the 231 journal articles and conference papers published during 2020-2022 with regards to the research theme, 6 subcategories emerged, as listed below.

• Assessment of factors leading to claims/disputes
• The role of the human factor in construction conflicts
• Construction project performance
• Dispute resolution methods’ assessment
• Claims/Dispute management process models
• Methods for modelling and evaluating construction disputes.

The abovementioned 231 journal articles and conference papers were further shortlisted considering the publication and citation patterns revealed in section 3 as well, resulting in 27 journal articles for further investigation based on the following inclusion and exclusion criteria:

• The publication type must be a journal article (36 conference papers excluded).
• Studies focusing on novel technologies, such as BIM, blockchain and smart contracts (22 documents included)
• Journal articles cited at least five times except for those focusing on novel technologies (139 documents excluded)
• Journal articles being published in any of the top 5 journals presented in Table 2 and/or authored by any of the most prominent authors presented in Table 3 (51 documents excluded).

The first exclusion criterion was applied due to conference papers usually being less detailed than journal articles and therefore omitted in review papers [20]. The second inclusion criterion was chosen to investigate how these recently emerged terms are associated with construction claims and disputes, as was revealed in Section 3.4. The third exclusion criterion was applied following the publication and citation patterns and thresholds selected during the bibliometric analysis conducted in Section 3. In this step of the selection process, the threshold of 5 citations per paper was not applied for the studies focusing on novel technologies, as they have only recently emerged in the literature. The fourth and final exclusion criterion was selected to detect the main research trends, gaps, and future research directions based on the results of Section 3.2 and Section 3.3. Some of the most important findings of these 27 selected publications are presented per research theme in the following subsections in table form.

4.1. Assessment of Factors Leading to Claims/Disputes

Various studies have investigated the causes of construction disputes throughout the world, focusing either on specific construction projects (i.e., road projects [21,22] or on the construction sector in general [23], as well as investigating either all types of causes [23,24,25] or a particular type (i.e., variations [21,26]).

It is worth noting that while in the past relevant studies focused on identifying long lists of claim/dispute causes [27], the focus of recent studies lies on examining the interrelationships between various factors affecting the emergence of claims and disputes, aiming to discover possible patterns of claim occurrence and making suggestions to address such factors before evolving into disputes, thus enhancing claim management [21,22,26,27,28,29]. Further details to better comprehend this recent swift focus on construction claims research can be found in Table 4.

4.2. The Role of the Human Factor in Construction Conflicts

According to the CCBS shown in Figure 1, human factor-related disputes can emerge due to rivalry (adversarial or controversial), cultural differences, lack of communication or lack of team spirit between the CA and the Contractor. This situation is only natural since construction projects are complex not only because of specific technical project characteristics, but mainly because multiple stakeholders holding different perceptions and roles regarding the project must work together [1,2,3]. The human factor is also one of the deciding factors when it comes to dispute resolution, as it is not uncommon to find disputants missing the chance of capturing win-win options even when these are notable [30,31,32]. Additionally, as engineering professionals are involved in managing claims and disputes arising under construction contracts, it is vital to understand the spectrum of the enhanced claim administration roles that engineers are called to exercise and the necessary traits, practices, and requirements that are observed when these roles are fulfilled [33].

In the current subsection, recent studies attempting to explore in detail how the human factor affects construction conflicts are examined. Table 5 presents some of the most characteristic recent studies related to the domain of human factor in construction claims and their findings, revealing that the effects of the human factor can be observed early on during the procurement phase of a project [34], during other stages of the project life-cycle as far as building construction projects are concerned (design, construction, services installation, maintenance) [35], or at the early stages of the claim evolution process [33].

4.3. Construction Project Performance

The main effects of claims and disputes in construction projects are increased project costs and time. Thus, claims can have significant impacts on the project’s performance and the project’s success or failure. Therefore, it is imperative not only to identify the causes of claims but to resolve them efficiently as well as to improve the project performance so that the projects can be completed in the scheduled cost and time [7,23]. In fact, this research team has recently completed research that pioneers by simultaneously examining the views of experts on the frequency of occurrence of causes of contractual claims and their perceived impact on the time, total cost, and quality of the final project [10].To this end, the current part of this paper presents, in Table 6, the most recent studies investigating the factors that affect construction projects’ performance and could result in claims and, ultimately, disputes.

4.4. Dispute Resolution Methods’ Assessment

As stated previously, whenever a claim arises by one of the parties involved and is rejected by the other, a dispute arises, a situation quite common in the construction industry [23,44]. According to El-Sayegh et al. [23], the two most common ways to mitigate disputes are avoidance and resolution. Dispute avoidance methods include negotiation, risk allocation, early non-binding neutral evaluation, and partnering, and they are used to prevent disputes from occurring. Resolution methods are further categorized into early (negotiation, conciliation, and mini-trial/executive tribunal) and late methods (negotiation, arbitration, mediation, adjudication, dispute review boards (DRB), and litigation). Early and late dispute resolution methods, except for litigation, are considered alternative dispute resolution methods (ADR). Initially, in the dispute resolution process, ADR methods are employed, and if these fail, the involved parties resolve to litigation and courts as a last resort [44].

Recent studies on dispute resolution methods, as illustrated in Table 7, apart from assessing [23] and selecting the most appropriate dispute resolution methods with regards to the causes of claims [45], also review novel ones such as online dispute resolution (ODR) methods, which fall under the category of ADR. ODR services are provided by several start-ups, established companies, and even higher-level authorities, such as the European Commission [1].

4.5. Claims/Dispute Management Process Models

Claim management focuses on the identification, assessment and settlement of costs incurred over and above the amounts agreed upon in contracts due to additional work or damages [46]. This process is considered data-intensive and requires analysis of large amounts of diverse information, highlighting the importance of proper information and documentation management, which is essential in providing accurate data and proofs for claims, especially in the increasing complexity of architecture, engineering and construction (AEC) projects [47].

Recent studies attempt to address the problems observed in claim and dispute management by developing novel computer-aided claim management process models employing BIM [3,47] and Blockchain [48], as illustrated in Table 8. Fundamentally, claim management process models could either be utilized to provide data essential for proper and fast dispute resolution or to prevent even the occurrence of claims.

4.6. Methods for Modelling and Evaluating Construction Disputes

In this final subcategory, the most important findings of the recent publications regarding the methods for modelling and evaluating construction disputes are presented in Table 9. Recent studies have addressed the issue of modelling disputes either to predict the occurrence of disputes in construction [5,49,50] or to estimate the expected outcome of construction dispute resolutions, which can help professionals decide whether they should embark on dispute resolution or not [51,52]. Researchers also developed a methodology to model the disputes’ causes and interrelationships to identify the significant causal factors responsible for triggering other causal factors and ultimately assist in reducing construction disputes [53].

Table 8. Methods for modelling and evaluating construction disputes

Table 8. Methods for modelling and evaluating construction disputes

5. Current Research Trends

The content analysis carried out in the previous subsection sheds light on the manner in which novel technologies such as BIM, Blockchain, Smart contract, AI, ML, NN or fuzzy logic and SEM have recently been employed in the research field of claim management and dispute resolution in the construction industry, explaining why these pose as current research trends in this research field.

To better comprehend these terms, it is helpful to present their definitions. Fuzzy logic refers to fuzzy set theory (FST), which is a branch of modern mathematics, and fuzzy technique methodologies can provide a viable tool for modelling subjective information and handling uncertainty where comprehensive data sets are not available for modelling [5]. The term smart contract was first introduced in 1994 by Szabo, describing it as “a computerized transaction protocol that executes the terms of a contract”, suggesting the use of an automated protocol for satisfying contractual agreements, minimizing both malicious and unintentional errors, and eliminating the role of intermediaries in contract enforcement [54]. Structural equation modelling (SEM) is a class of multivariate techniques that combines the aspect of confirmatory factor analysis (CFA) in the form of a measurement model and regression or path analysis in the form of the structural model. SEM is one of the most useful advanced statistical analysis techniques that have emerged in the social sciences in recent decades, and the advantage of using SEM is that it can simultaneously examine the relationship between measured variables (independent variables) and constructs (dependent variables) [55]. Blockchain is the underlying distributed ledger technology (DLT) known primarily for underpinning the operation of the Bitcoin cryptocurrency network. A blockchain system can record transactions and validate digital events (e.g., information) conducted in the network in the form of encrypted “blocks” and can “chain” the entire recorded transactions chronology stored across multiple nodes. Blockchain operates on three core components: cryptography, consensus mechanisms, and decentralization [56]. Artificial Intelligence (AI), Machine Learning (ML) and Artificial Neural Networks (ANN) are AI technologies that can be employed, among other applications, in the construction industry to predict the occurrence of construction disputes or the outcome of construction litigation [2]. Building Information Modeling (BIM), as defined by the National Institute of Building [57], is “a digital representation of physical and functional characteristics of a facility… and a shared knowledge resource for information about a facility forming a reliable basis for decisions during its life-cycle; defined as existing from earliest conception to demolition”. BIM can represent elements such as walls, doors, and windows as 3D objects and provide other information, including manufacturers, fire ratings, schedules and cost estimates attached to these objects. Furthermore, one important advantage of BIM is the ease of inserting, extracting, updating or modifying digital data by the stakeholders involved in the project (owners, clients, engineers, architects, contractors, suppliers and building officials) [47].

After gaining the necessary insight into what exactly these novel technologies represent, it is now more easily understood how these methods are employed for the scope of the research of this current paper. In Table 10, the publications, which were analyzed during the content analysis, employing these methods for addressing construction disputes are presented per project-phase research theme and causes of claims addressed in each article.

BIM, blockchain, and Smart contracts are usually combined to assist researchers and professionals in coping with the issues arising regarding claims and disputes in the construction industry, either by preventing or resolving them more efficiently when they occur. Additionally, since BIM has already had practical implications in construction for many years now and has proven how useful it has been, it can be more easily combined with emerging technologies such as Blockchain and Smart contracts, rendering this combination more readily accepted and proving its applicability in real construction projects.

6. Conclusions

This paper explored the current state of research in the field of claim management and dispute resolution in the construction industry. This is a research area that has attracted extensive attention in the past 15 years. The bibliometric review conducted in this study through the VOSviewer software and the Scopus database recovered 791 documents published between 1983 and 2022, revealing that Australia, Hong Kong, and the United States of America are the countries contributing the most to this research field. Furthermore, the most influential scientific journals are “Journal of Legal Affairs and Dispute Resolution in Engineering and Construction”, “Journal of Construction Engineering and Management” and “Construction Management and Economics”, while Cheung S.O. along with Yiu T.W. and Fenn P. are the authors with the highest number of average citations. Conducting a co-occurrence author keywords analysis through VOSviewer, it was revealed that terms such as “blockchain”, “smart contracts”, “building information modelling (BIM)”, and “claim management” appear only recently (after 2020) in the literature with regards to the construction claims and disputes research area. Attempting to shed light on the manner in which these concepts relate to construction claims and disputes, the recent documents published between 2020-2022 were further investigated, revealing six research themes: “Assessment of factors leading to claims/disputes (Section 4.1)”, “The role of the human factor in construction conflicts (Section 4.2)”, “Construction project performance (Section 4.3)”, “Dispute resolution methods’ assessment (Section 4.4)”, “Claims/Dispute management process models (Section 4.2)”, and “Methods for modelling and evaluating construction disputes (Section 4.6)”, leading to a content analysis of 27 journal papers. Some of the most important findings and proposals for future research are presented per research theme.

Regarding the assessment of factors leading to claims and disputes related to modular construction projects [28], where construction disputes are triggered mainly by the occurrence of multiple causes rather than by just a single cause, future research could focus on the necessary, appropriate adjustments of the contractual aspects of modularization in construction. Furthermore, when examining the role of the human factor in construction conflicts, unethical practices of bid shopping and peddling during the subcontractor (Sub) procurement process can negatively affect construction conflicts. The blockchain-based framework proposed by Pishdad-Bozorgi and Yoon [34] can prevent these unethical practices and enable Subs to fairly compete for bid awards with proper budgets, enhancing the trust between the general contractor and Subs. As far as the construction project performance is concerned, the absence of a uniform and transparent system for managing quality information was found by Sheng et al. [39] to undermine the assurance process, which can lead to disputes among stakeholders. Future research in construction quality information management is proposed by highlighting that blockchain technology has the potential to co-evolution with BIM and IoT technologies, which could further promote industrial cooperation and improve productivity.

Moreover, when assessing the methods employed for resolving disputes, it was found that ADR methods are preferred over litigation and future research on integrating AI and blockchain is proposed so that potential disputes can be assessed based on the information of past projects in addition to reducing and resolving them [1]. BIM and blockchain were also found to enhance claim management during the design and construction phase of a project, which resulted in developing process models that could either be utilized to provide data essential for proper and fast dispute resolution or to prevent even the occurrence of claims. It is also proposed that Integrated Project Delivery (IPD) should be used as the project delivery system, since it provides the required platform for the necessary collaboration in a project [47]. Finally, regarding the research on the methods for modelling and evaluating disputes, some important findings were that there are complex interactions among the factors leading to claims and that “inconsistency between drawings and specification” was considered the most influential factor leading to claims, according to the developed artificial neural network (ANN)/decision tree-based model of claim tenability prediction [50].

The most important contribution of this perspective paper is that the content analysis revealed the current research trends using novel technologies such as BIM, blockchain, smart contracts, AI, ML, NN fuzzy logic and SEM. AI, ML, NN and, fuzzy logic & SEM are mainly employed during the pre-construction phase of a project or at the early stages of construction to model and evaluate construction disputes. The causes of claims addressed in these research endeavours include Change of scope (A1), Delays in work progress (B1), Inadequate/ incomplete specifications (C2), lack of communication between CA and Contractor (E2), or Project characteristics (F1, F2). In some cases, BIM, Blockchain and Smart contracts, either individually or combined, have been applied during the design, construction or post-construction phase of a project to address the construction disputes related to Change of scope (A1), Payment delays (A5), Quality of works (B10), Design errors (C1), Inadequate/ incomplete specifications (C2), Insufficient availability of information (C3), Ambiguity in contract documents (D1), Inadequate Document management (D5), or lack of communication between CA and Contractor (E2). Nevertheless, the literature revealed that there are still issues and limitations of these novel technologies to be addressed when it comes to applying them in actual construction projects, mainly due to the different levels of familiarity the parties involved in construction possess with these methods.

Furthermore, a research gap was observed regarding the combination of BIM, Blockchain and Smart contract applications in road projects. This could indicate a potential future research direction as to how and if this “partnership” can be employed for addressing disputes arising in road projects. Another direction for future research could be to explore the level of familiarity public road contracting authorities have with BIM, Blockchain and Smart contract applications in general and on specific project types. For example, road projects, as only three out of the 27 articles analyzed focused on this project type (in Sri Lanka [21], India [22], and Nepal [45]). To this end, attempting to facilitate the public sector into entering the era of Industry 4.0 in construction, future research could focus on developing a road map for the application of smart contracts for Road construction, operation, and maintenance to be tailored to the contracting road authorities’ needs.

Finally, although this study covered an extensive range of representative papers to reflect the status of claim management and dispute resolution in the AEC industry in its entirety, limitations exist due to the employment of the Scopus database and the VOSviewer software. Similar research could be conducted employing the CiteSpace software and the Web of Science database in an attempt to reveal more exciting findings with regard to bibliometrics since CiteSpace offers more possibilities in this field.