Identification of Contractual and Financial Dispute Causes in the Off-Site Construction Projects

Abstract

Off-site construction (OFC) is a hot topic to remedy the chronic issues of the construction industry, such as low levels of productivity, waste, safety risks, environmental pollution, poor quality, and time and cost issues. However, the lack of standards and knowledge about OFC projects hamper the adaptation process. Disputes are one of the most important hampering factors. Therefore, this study aims to identify contractual and financial disputes and to detect the importance level of disputes in OFC projects. In the study, the Focus Group Discussion (FGD) technique, Pythagorean fuzzy AHP, and fuzzy TOPSIS were employed. As a result of FGD, 42 dispute causes for off-site construction projects were found. The Pythagorean fuzzy AHP method was used to calculate the weights of the criteria (occurrences, severity, and detection) that were used in the evaluation of dispute causes. The Pythagorean fuzzy AHP analysis results indicated that “detection” is more important than other criteria in the evaluation of off-site construction dispute causes. After that, the fuzzy TOPSIS method was used to determine the importance level of off-site construction dispute causes. The analysis results showed that “Increase in contract value due to revision in scope of work” in the contractual factor group and “Extra money for the additional works” in the financial factor group are the most important dispute causes, respectively. The study findings can be used for the evaluation and analysis of OFC project contracts.

1. Introduction

The construction industry requires adaptation and optimization of various interdependent components such as construction equipment, materials, and labor workforce. However, these interdependent components belong to different stakeholders whose interests conflict. Therefore, disputes are very common in the construction industry [1]. With these chronic issues, the uptake of new technological advancements, such as off-site construction manufacturing, can induce new unexplored challenges and barriers in the construction industry.

According to the Arcadis report [2], the construction industry tries to be the impetus behind the development of the nations after COVID-19. However, inflation and supply chain-related issues cause construction disputes. Moreover, demand for critical global commodities, waning stockpiles, war between Ukraine and Russia, material and hydrocarbon shortages, and increase in energy prices exacerbate disputes. The Arcadis report also informs that the resolution time of disputes increased compared to previous years and the number of disputes is the highest value. The length of the disputes is another important criterion. Since companies lost business opportunities, it caused an increase in indirect costs and more tense relationships between stakeholders [1]. The root reasons for these disputes were summarized as the misunderstanding of the contractual terms and the breach of contractual terms, errors and omissions in contracts, and poor contract management [3]. Therefore, proper administration of the contract is required to enable early resolution of construction disputes and achieve project targets successfully [2]. Additionally, properly prepared construction contracts help to control and prevent disputes before they arise [3].

In practice, different construction contract drafts have been published by the American Institute of Architects, the International Federation of Consulting Engineers, the UK Institute of Civil Engineers, et cetera. These types of construction contract drafts help to eliminate and minimize misrepresentation and misunderstanding of contracts’ wordings, language, and terminology that lead to disputes by considering experiences. However, contract-related disputes are unavoidable since modification of contract templates based on owner requirements is not error-free [3]. Especially for off-site construction projects, the contract standardization process is relatively low, and the off-site construction practice is a new methodology for construction industry practitioners.

In the construction industry, contractual dispute causes are not only the source of disputes but also a change of the order, design problems, site conditions, delay problems, lack of communication, payment problems (financial), opportunistic behavior, and bid problem-related dispute causes are very common [4]. In construction projects, the owner cannot or will not pay due to the financial difficulties exacerbated by failure to seek funding, not having sufficient money, improper cash flow management, reduced overdraft facilities, or external factors such as COVID-19 [5]. Similar to conventional and on-site construction projects, Nabi and El-adaway [6] found that payment holds and delays are the most common dispute causes for modular construction (under off-site construction) projects. In other words, contractual and financial dispute causes require special focus on off-site construction projects.

Off-site construction is an umbrella term that includes pre-fabrication, industrialized construction, modular construction, and prebuilt construction. Off-site construction emerges as a methodology to resolve productivity issues in on-site construction projects, to eliminate the need for a skilled workforce, and to be more sustainable by reducing greenhouse gas emissions based on construction activities. The off-site construction method requires the production of building components in a factory, the transportation of the products to the construction site, and the installment of the products on the site. Therefore, it requires different management techniques and approaches compared to on-site construction activities [7]. While off-site construction helps to shorten the construction schedule and reduce health and safety-related issues, it requires timely delivery of the site and foundation of construction projects [3]. Sometimes, the production process and transportation of the products cannot be conducted as planned [7]. Additionally, the procurement process of off-site construction projects differs from on-site construction projects due to the excessive coordination and transition in off-site construction projects. Moreover, excessive costs could be incurred due to the materials, quantity, and distance between factory and construction sites. Furthermore, off-site construction requires the determination of a detailed scope and design before the production process begins [3,8].

In practice, construction contract templates designed for on-site construction projects are used in off-site construction by modifying them. Nonetheless, codes, risk insurance, delivery of products, schedule, and storage of materials on construction sites are different in off-site construction projects. This means that the root causes of disputes and the importance level of dispute causes can be variable [3]. Therefore, effective prevention mechanisms for off-site construction disputes require a proper understanding of the underlying conditions, risks, and causal factors in off-site construction projects. Thus, this study aims to identify contractual and financial disputes and to detect the importance level of disputes in evaluating risks and ambiguity in off-site construction projects.

To enable effective prevention mechanisms and management of financial and contractual dispute causes for off-site construction projects, the understanding of its theoretical and practical contributions is important. The theoretical contribution of this study is to increase the knowledge related to off-site construction projects. This study can also be used to identify contractual and financial risks in off-site construction projects. Moreover, the findings can be used as a checklist and to fill the gap in the development of off-site construction project contract templates. Finally, this study employs the first-time Pythagorean fuzzy AHP integrated Fuzzy TOPSIS Hybrid Approach to analyze dispute causes in the construction management literature. The results can be used by practitioners to analyze off-site construction project contracts. Moreover, the practitioners can use the results to choose the most convenient dispute resolution methods. Finally, it can guide the selection of the most convenient technologies for construction projects. Thus, the dispute causes can be prevented in off-site construction projects.

2. Literature Review

2.1. Existing Body of Knowledge for Dispute Causes in Off-Site Construction Projects

Off-site construction can also be referred to as pre-fabrication, industrialized construction, modular construction, or prebuilt construction. However, although these terms differ subtly [7], some researchers consider all terms and concepts interchangeably [9]. According to the explanation of the Off-site Construction Research Centre [10], off-site construction methods can involve both traditional and advanced industrial methods (including prefabricated and modular construction methods). In other words, the method does not need to consider prefabrication, standardization, or pre-assembly. Studies on dispute occurrences in construction projects often do not specialize in specific types of projects, such as off-site construction. Instead, they focus on the general context of the construction industry, which may not address the unique challenges of off-site construction [11].

Nabi and El-adaway [6] identified dispute causes for modular construction projects by analyzing dispute cases. After the analysis of 39 dispute cases obtained from the Case Law Google Scholar search engine (litigation cases), 40 dispute causes were identified. The authors also used the Social Network Analysis (SNA) method to discover both the most common causes of disputes and the dispute causation network. According to the findings of the study, “payment holds and delays”, “lack of collaboration between various project trades”, “delay in project completion” and “poor communication between project participants” are the most common disputes. In another study, Nabi and El-adaway [12] aimed to identify the dispute causes in modular construction projects. The authors used case studies and social network analysis methods to detect the causes of the dispute. The authors considered 28 common causes by considering both on-site projects and modular construction projects. After that, modular construction projects found in publicly open resources were analyzed. With the use of case study findings, the co-occurrence of dispute causes was found. The analysis results indicated that “delays in work progress”, “lack of communication”, and “lack of team spirit” were the main dispute causes in modular construction.

Chan et al. [13] investigated the contractual disputes for modular and off-site construction projects. In the study, the authors conducted a literature review for both conventional and on-site construction projects, and modular and off-site construction projects specific to construction contracts. After that, the Canadian Superior court cases during the past 20 years were analyzed to classify and quantify the causes of the dispute. Thus, the commonalities and differences between literature and real cases were identified. As a result of the literature review analysis, the contractual dispute causes are categorized under five categories (language, contract, design, stakeholders, and external factors). Additionally, the study contributed 14 new dispute causes for modular and off-site construction projects into the literature. According to the analysis of the litigation cases, the most common disputes related to the construction contracts were found as “unclear payment terms, procedure, certify”, “unclear terms for changes in work”, and “poorly defined general provisions”, respectively. However, the authors stated that “Not all literature-identified sources are found in cases of litigation”. Therefore, it can be inferred that the study findings can be misleading since the important dispute causes can be resolved before the litigation process. In the next section, the gap in knowledge is explained with the comparisons.

2.2. Gap in Knowledge

Off-site construction is a new method compared to on-site construction projects. Therefore, the components of the construction industry are not familiar with this production methodology and their knowledge is limited. Moreover, the standardization efforts on policies and guidelines for off-site construction are not at the intended level. Additionally, the flexibility offered by off-site construction causes to increase in risks [7]. For example, early or late delivery of building components to the construction site, additional workforce requirements due to business setbacks and increases in costs are supply chain-related issues due to the flexibility. Therefore, the authors stated that these flexibility conditions and project management practices should be managed and performed differently from on-site construction projects.

Moreover, the “off-site construction field remains underdeveloped, small, immature, and sluggish”. The underlying reason behind this situation is attributed to the lack of knowledge compared to conventional and on-site construction projects [14]. The lack of knowledge can also be observed in the identification of dispute causes for off-site construction projects. There are only three studies that analyze this [6,13]. The studies used litigation cases as a data source. However, the consideration of litigation cases can be misleading since some disputes could have been resolved before the litigation process initiates, or disputes can be resolved with the use of other dispute resolution methods. Therefore, the experiences of industrial practitioners gain importance in determining dispute causes that were resolved with dispute resolution methods. To identify all dispute causes depending on experts’ knowledge, this study included a questionnaire to collect data. Thus, all dispute causes related to contracts and finances in off-site construction projects were aimed to be revealed. Moreover, while Chan et al. [13] did not consider financial disputes, Nabi and El-Adaways’ studies [6,11] considered all dispute causes (including contractual, financial, stakeholder etc.) without categorization. Furthermore, Chan et al. [13] defined a higher number of dispute causes than our study since the researchers in that study considered “language”, “contract”, “design”, “stakeholder”, and “external” factors together under “contract source of ambiguity and disputes”. In other words, the authors associated all dispute causes with the contract. Compared to those studies, we categorized them differently.

As a consequence, the importance level of financial and contractual dispute causes could not be separately explored and ordered. The detailed comparisons are tabulated in

Table 1. The novelty of the proposed study.

	Chan et al. [13]	Nabi and El-adaway [12]	Nabi and El-adaway [6]	The Novelty of the Proposed Study
Identification of dispute causes (source)	Literature review + litigation cases	Literature review + litigation cases	Litigation cases	Literature review + Focus Group Discussion
Availability of dispute causes from on-site construction projects	Yes	Yes	No	Yes
Data collection source	Litigation cases	Litigation cases	Litigation cases	Questionnaire
Construction method	Off-site construction and modular construction	Modular construction	Modular construction	Off-site construction
The number of identified dispute causes	62	28	40	42
Focus	Contractual disputes	Mixed (without categorization)	Mixed (without categorization)	Contractual and financial disputes
Methodology	Fishbone method	SNA method	SNA method	Fuzzy Pythagorean AHP integrated Fuzzy TOPSIS methods

.

3. Methodology

This study employed three different methodologies to determine the importance levels of financial and contractual dispute causes for off-site construction projects. Figure 1 depicts the research flow and their interactions. According to the research methodology, the factors that need to be considered in the financial and contractual disputes for off-site construction projects were determined by a comprehensive literature review in the first step. Experts evaluated identified factors through a focus group session in the second step. The focus group discussion (FGD) session was extremely useful in discovering new dispute causes and eliminating and combining dispute causes that lead to incorrect calculations of importance levels. In the third step, the questionnaire was developed to collect data to analyze the weights of criteria (occurrences (O), severity (S), and Detection (D)) with the Pythagorean fuzzy AHP method and determine the importance level of “Organizational factors”, “External factors”, “Technical factors”, “Contractual factors”, and “Financial factors” depending on criteria (O, S, and D). Questionnaires were held face-to-face. It should be noted, this study only shares the results of financial and contractual dispute causes for off-site construction projects due to the page limit. However, “Organizational factors”, “External factors”, and “Technical factors” were considered to determine the general ranks of contractual and financial disputes. In the last step, sensitivity analysis was performed to assess the reliability of the results.

3.1. The Identification of Dispute Causes in Off-Site Construction

The existing knowledge about dispute causes for off-site construction projects is very narrow. As stated in the “Gap in Knowledge” section, the existing studies are not limited in terms of identification of dispute causes for off-site construction projects, but they also used the litigation cases as a data set. Therefore, on-site dispute causes related studies were investigated to identify additional factors. The Scopus search engine was selected to conduct the literature review due to its comprehensiveness and popularity [15,16]. As a result of the literature review, 46 factors were identified specific to contractual and financial factors. After conducting a comprehensive literature review, the identified dispute causes were investigated by experts in the FGD session. As a result of the expert evaluation in FGD, four factors were eliminated in the financial and contractual dispute causes.

Table 2. Financial and contractual dispute causes for off-site construction projects.

	Contractual Disputes	References
C1	Risk allocation	[6,17,18,19,20,21]
C2	Ambiguities in bidding	[12,19,22,23,24]
C3	Excessive changes in scope	[6,12,17,19,20,21,25,26,27,28]
C4	Poor contract documentation	[22,24,25,29,30]
C5	Misrepresentation of contract documents	[29]
C6	Noncompliance with the contract terms	[6,22,24]
C7	Ambiguities in contract (such as payment terms, scope description, and change orders)	[6,12,17,19,20,21,23,24,25,26,27,28,29,30,31]
C8	Poorly defined general provisions	[29]
C9	Mismatch contract type	[6,17,29,30]
C10	Contract wording and linguistic issues	[17,18,22,23,26,27,29]
C11	Increase in contract value due to revision in scope of work	[32]
C12	Excessive contractual variations	[29]
C13	Failure to examine contract conditions at the time of tender	[20,21]
C14	Errors and omissions of contract terms	[18,20,21,22,28,30]
C15	Legal text layout	[29]
C16	Problems in terminology	[26,29]
C17	Ineffective contract management and administration	[17,18,29]
C18	Unclear method to reduce the delay damages	[20]
C19	Unclear definition and types of defects	[20]
C20	Complexity in contract provisions	[6,12,17,18,19,20,22,23,26,28,29,31]
C21	Illegal and improper work suspension	[6,27,29]
C22	Opportunistic behavior of project parties	[6,18,27]
C23	Breach of warranty claims	[25,29]
C24	Non-practical conditions	[29]
	Financial Disputes	References
F1	Disagreement on payment methods caused by variations in quantities	[20,28]
F2	Financial failure or inadequacy of contractor	[6,12,17,19,20,21,24,26,30,32]
F3	Payment delays (owner based)	[6,12,17,19,21,22,24,26,27,28,31,32,33]
F4	Adamant nonpayment	[25]
F5	Disagreement of the compensation amount	[20]
F6	Deductions	[25]
F7	Delays in compensation	[25]
F8	Denial of compensation	[25]
F9	Insufficient financial planning	[23]
F10	Loss to the client	[32]
F11	Non-releasing of deposits	[25]
F12	Payment delays (contractor based such as delays in submitting progress payment claims, errors and insufficiency in submitted documents)	[6,34]
F13	Inadequate or delayed project funding	[6]
F14	Non-availability of spare money for additional work	[24]
F15	The low-profit margin	[31]
F16	Too much inference from the client	[22]
F17	Untimely contractual payment (payment made before the payment date for uncompleted works)	[27]
F18	Insufficient coverage of design liability insurance	[29]

includes the final dispute causes list.

3.2. Focus Group Discussion Technique

The focus group discussion (FGD) technique helps reveal the views and beliefs of the experienced professionals about the discussed topic. It is a qualitative research method. In FGD, the data is collected from the selected group of individuals. It facilitates data collection procedures instead of collecting data from a sample of a broader population [35]. This technique has increased in popularity and application areas across a wide range of disciplines (communication and media studies, sociology, health research, marketing research, engineering et cetera).

The FGD technique can be thought of as a series of profound interviews with experts. The researcher is a moderator and a peripheral actor in the FGD technique [35]. In the FGD technique, participants can affect each other so that innovative ideas are not only created, but also the discovery of practical knowledge can be facilitated. However, the size, composition, and execution process of the FGD are crucial to obtaining valuable results [36]. According to the flowchart of the steps of the FGD defined by Nyumba et al. [35], identification of the objectives for FGD, selection of experts, identification of suitable location, familiarization of the participants to the topic and each other, discussions according to questions and follow-up questions, analysis of the FGD findings and reporting should be performed respectively. The authors stated that the FGD session can be conducted with the participation of experts ranging from 3 to 21. Also, the median value was found as 10 participants. Mishra [36] stated that the size of the FGD session can show a variety of 10 to 12 experts. According to Mishra [36], the FGD technique can be used as a stand-alone method to support studies in which quantitative research methods are used before and after them.

3.3. FMEA Approach

The Failure Modes and Effects Analysis (FMEA) is a structured reliability analysis method to prevent issues with products and processes. The FMEA method helps to discover risk factors before the issue arises. Therefore, the practitioners can focus on eliminating or reducing the occurrence of risks and take precaution for the severity of risk impact [37]. In the FMEA analysis, occurrences (O), severity (S), and detection (D) of risks are the main components to evaluate risk factors [38]. Choi and Kim [37] stated that “the FMEA is an efficient tool to evaluate potential risk factors in the early stage of various construction management processes”. The authors expressed that the FMEA tool helps to enable resource allocation according to the important or high risks. Within this context, the authors proposed that the disputes and claims can be regarded as risks. Therefore, the authors employed the FMEA method to evaluate dispute causes.

In traditional FMEA analysis, each dispute cause is evaluated by using the 1–10 scale. However, Mohammadi and Tavakolan [38] stated that the use of conventional assessment methods (1–10 scale) is not convenient for obtaining reliable FMEA analysis results. In other words, they reported that probabilities of occurrences should not be evaluated with the use of precise numbers. Therefore, the use of fuzzy numbers is proposed to solve the vagueness of the traditional FMEA approach. Thus, the FMEA approach is combined with the Pythagorean fuzzy AHP method in this study.

3.4. Pythagorean Fuzzy AHP Integrated Fuzzy TOPSIS Hybrid Approach

The study aims to identify contractual and financial disputes and reveal the importance level of dispute causes to evaluate risks and ambiguity in off-site construction projects. Therefore, a novel approach (Pythagorean fuzzy AHP integrated Fuzzy TOPSIS method) is applied for the first time in the identification of dispute causes.

The steps of using the Pythagorean fuzzy AHP integrated Fuzzy TOPSIS Hybrid Approach and analysis results are given below.

3.4.1. Pythagorean Fuzzy AHP

The Analytical Hierarchy Process (AHP) is one of the most used MCDM methods. The AHP method aims to determine the weights of criteria and calculation of priorities of alternatives. It is commonly used thanks to its implementation easiness, systematic handling of problems, and easiness of analysis. In the method, the pair-wise comparison matrices are used to collect data. The experts are asked to either compare the criteria by considering the aim of the study or compare the alternatives by considering the criteria. However, in the evaluation process, precise numbers were used. This leads not to considering the uncertainty, vagueness, or imprecision of the experts [39,40]. The fuzzy AHP methodology was developed to overcome uncertainty, vagueness, or imprecise decisions. The development of fuzzy sets paves the way for other extensions such as neutrosophic sets, Pythagorean sets, and orthopair fuzzy sets [41]. Pythagorean fuzzy sets address uncertainty and indeterminacy and they reduce vagueness and impreciseness. Unlike the conventional AHP and FAHP, the P-FAHP allows for a more accurate representation of the decision-makers’ perceptions [41]. The Pythagorean fuzzy AHP steps are summarized below.

Step 1. Pair-wise comparison matrices are constructed to collect expert opinions. The scale used for data collection is taken from the study by Shete et al., 2020 [42]. The details of this study can be checked to access the linguistic terms for Pythagorean fuzzy AHP data.

Step 2. The consistency of expert responses should be evaluated to obtain reliable results in the AHP method. Therefore, the consistency ratio (CR) was calculated for each decision maker’s comparison matrix. The CR value must be less than 0.1 to achieve reliable results. If the CR values are lower than 0.1, the geometric mean of each decision maker’s responses is calculated to create a matrix that consensus has been formed [43].

Step 3. The differences matrix ($D={\left(d_{ik}\right)}_{mxn}$) is constructed by using the lower and upper values of membership and non-membership degrees. Equations (1) and (2) are employed to calculate lower and upper values.

$$d_{ikL}={\mu }_{ikL}^2-v_{ikU}^2$$

(1)

$$d_{ikU}={\mu }_{ikU}^2-v_{ikL}^2$$

(2)

Step 4. The interval multiplicative matrixes ($S={\left(S_{ik}\right)}_{mxn})$ are constructed by using Equations (3) and (4).

$$S_{ikL}=\sqrt{{1000}^{d_L}}$$

(3)

$$S_{ikU}=\sqrt{{1000}^{d_U}}$$

(4)

Step 5. The determinacy value ($\tau ={\left({\tau }_{ik}\right)}_{mxn}$) is calculated from the aggregated matrix by using Equation (5).

$${\tau }_{ik}=1-\left({\mu }_{ikU}^2-{\mu }_{ikL}^2\right)-v_{ikU}^2-v_{ikL}^2$$

(5)

Step 6. To calculate the weight matrix (Equation (6)), the arithmetic value of Equations (3) and (4) is calculated and multiplied by the result of Equation (5).

$$t_{ik}=\left({\displaystyle \frac{S_{ikL}+S_{ikU}}{2}}\right)\times {\tau }_{ik}$$

(6)

Step 7. The normalized priority weights are calculated by using Equation (7).

$$W_i=\left({\displaystyle \frac{{\sum }_{k=1}^m{t}_{ik}}{{\sum }_{i=1}^m{\sum }_{k=1}^m{t}_{ik}}}\right)$$

(7)

3.4.2. Fuzzy Techniques for Order Performance by Similarity to Ideal Solution (FTOPSIS)

The TOPSIS method is another useful MCDM method to deal with multi-attribute decision making problems. The classical form of the TOPSIS method was developed by Hwang and Yoon. In this method, the alternatives are evaluated with the consideration of conflicting criteria. The TOPSIS method aims to find “the shortest distance to the positive ideal solution and the farthest distance to the negative ideal solution” [44]. The difference between the FTOPSIS method from the classical TOPSIS is that the FTOPSIS method considers ambiguous and vague issues during the decision making process. Therefore, the FTOPSIS method employs linguistic values rather than numerical assessments. As in F-AHP, linguistic value takes into consideration ambiguities, uncertainties, and vagueness [45]. In other words, the use of numerical assessment will involve unclear judgment due to the uncertainty [44]. This enables us to better consider human thinking in real-world environments compared to the traditional TOPSIS method [46].

The linguistic variables are transformed into the triangular fuzzy numbers a (the smallest value), b (the peak value), and c (the largest value) for the analysis of the problem. If there is more than one data set, geometric mean can be used to create an aggregated matrix [43]. In this study, the linguistic variable scale explained in Chamoli [45] and Fu et al. [46] was used in the FTOPSIS analysis. The studies can be reviewed for the linguistic variable scale.

The FTOPSIS is one of the intensively used MCDM methods in the construction management literature. For example, the F-TOPSIS method was used in risk evaluation [47], risk allocation [48], the selection of dispute resolution method [49], et cetera. The FTOPSIS method steps are given below [50]:

Step 1: After aggregating expert judgments, Equations (8) and (9) are used to normalize the fuzzy decision matrix.

$$r_{ij}={\displaystyle \frac{a_{ij}}{c_j^{*}}},{\displaystyle \frac{b_{ij}}{c_j^{*}}},{\displaystyle \frac{c_{ij}}{c_j^{*}}}\mathrm{and}{c}_j^{*}={max}_i{c}_{ij}\left(benefitcriteria\right)$$

(8)

$$r_{ij}={\displaystyle \frac{a_j^{-}}{c_{ij}}},{\displaystyle \frac{a_j^{-}}{b_{ij}}},{\displaystyle \frac{a_j^{-}}{a_{ij}}}\mathrm{and}{a}_j^{-}={max}_i{a}_{ij}\left(costcriteria\right)$$

(9)

Step 2: The normalized matrix is multiplied by the criteria weights calculated as follows with the use of Pythagorean fuzzy AHP (See Equation (10)):

$$v_{ij}=w_j{r}_{ij}$$

(10)

where w_j corresponds to the weights of the jth criterion.

Step 3: Equations (11) and (12) are used to determine the positive and negative ideal solutions.

$$A^{*}=\left\{v_1^{*},\cdots ,v_n^{*}\right\}$$

(11)

$$A^{-}=\left\{v_1^{-},\cdots ,v_n^{-}\right\}$$

(12)

Step 4: The vertex method is used to calculate the separation measures of alternatives. For the negative ideal alternative separation.

$$S_i^{*}=\sum _{j=1}^{n}d\left(v_{ij},v_{ij}^{*}\right)$$

(13)

For the positive ideal alternative separation:

$$S_i^{-}=\sum _{j=1}^{n}d\left(v_{ij},v_{ij}^{-}\right)$$

(14)

The Euclidian distances between each of the alternatives were calculated with the use of Equation (15).

$$d\left(\tilde{m},\tilde{n}\right)=\sqrt{{\displaystyle \frac{1}{3}}\left[{\left(m_1-n_1\right)}^2+{\left(m_2-n_2\right)}^2+{\left(m_3-3\right)}^2\right]}$$

(15)

Step 5: The relative closeness index is calculated via Equation (16).

$$CCi={\displaystyle \frac{S_i^{*}}{S_i^{*}+S_i^{-}}}$$

(16)

3.4.3. Sensitivity Analysis

Sensitivity analysis is the key step to evaluate the robustness of preference decisions. The analysis is performed to observe how the ranks change when the weights of the criteria change. The sensitivity analysis is made by changing the weights of the main criteria calculated via the MCDM methods. Several combinations are generated according to the number of criteria [51].

4. Results

4.1. Results of Focus Group Discussion Technique

This study employed the FGD technique to identify disputes for off-site construction projects. In the FGD session, the execution process of FGD defined by Nyumba et al. [35] was followed. Experts were invited to the FGD according to the pre-qualifications (engineer/architect, MSc/PhD (to improve the understandability of the research), and experience in off-site construction) (see Figure 2). The FGD session was held face-to-face. The employment of face-to-face FGD helped to share the opinions of all participants equally [52]. The expert profile is presented in

Table 3. Expert profile (FGD session).

Expert ID	Personal Profession	Education	Years of Experience
E1	Purchasing Specialist	Civil Engineer (MSc degree)	CI: 7 years. O: 5 years.
E2	Contract Specialist	Civil Engineer (MSc degree)	CI: 17 years. O: 9 years.
E3	Tender Specialist	Civil Engineer (MSc degree)	CI: 10 years. O: 6 years.
E4	Purchasing and Contract Specialist	Civil Engineer (MSc degree)	CI: 10 years. O: 7 years.
E5	Tender Specialist	Civil Engineer (MSc degree)	CI: 8 years. O: 5 years.
E6	Technical Office Chief	Civil Engineer (MSc degree)	CI: 20 years. O: 7 years.
E7	Project Manager	Architect (MSc degree)	CI: 12 years. O: 5 years.
E8	Project Manager	Architect (MSc degree)	CI: 15 years. O: 6 years.
E9	Project Manager	Architect (MSc degree)	CI: 22 years. O: 12 years.
E10	Academician	Civil Engineer (PhD Degree)	CI: 11 years. O: 5 years.

CI: construction industry, O: off-site construction.

. A purposive sampling technique was employed to select experts for both FGD and questionnaires. In purposive sampling, the strategy of participant selection should align with the overall logic of the study. Also, the participants or experts who are most likely to yield helpful information about the topic are selected [53]. First, the aim of the study was explained to the experts. Second, the importance of the identification of a dispute list for off-site construction was asked. Third, experts with diverse experience in off-site construction projects reviewed the initial version of the dispute causes list. Thus, the experts were asked to eliminate, combine, or add new dispute causes for off-site construction projects.

In the first stage, participants were asked an open-ended question to learn the necessity of identifying dispute causes for off-site construction projects. According to expert responses, off-site construction projects show more variety than conventional and on-site projects. Therefore, the experts stated that they need to consider and give utmost importance to different activities, processes, and management areas in off-site construction projects.

In the second stage of the FGD session, the literature review results (off-site construction dispute causes list) were shown to the experts. The experts were asked to evaluate identified dispute causes in terms of off-site construction projects, and new dispute causes were requested if needed. However, the experts expressed that the identified dispute causes are satisfactory to reflect the seen dispute causes in the off-site construction. Moreover, the experts were requested to evaluate each dispute cause with the use of a 1–5 Likert scale (1—least importance, 5—the most importance). The collected data was analyzed with an arithmetic mean formula. As a result of the analysis, four factors were found under three scores for financial and contractual dispute causes. Therefore, these factors were eliminated. Thus, the dispute causes presented in Table 2 includes the final list.

4.2. Data Collection for Pythagorean Fuzzy AHP Integrated Fuzzy TOPSIS Hybrid Approach

After the conduction of FGD and determination of financial and contractual dispute causes for off-site construction projects, the questionnaire was prepared to collect data and analyze their importance levels. During the data collection process, data was collected from 17 experts who are experienced in off-site construction projects (See

Table 4. Expert profile (questionnaire).

Expert ID	Personal Profession	Education	Years of Experience
E1	Purchasing Specialist	Civil Engineer (MSc degree)	CI: 7 years. O: 5 years.
E2	Contract Specialist	Civil Engineer (MSc degree)	CI: 17 years. O: 9 years.
E3	Tender Specialist	Civil Engineer (MSc degree)	CI: 10 years. O: 6 years.
E4	Purchasing and Contract Specialist	Civil Engineer (MSc degree)	CI: 10 years. O: 7 years.
E5	Tender Specialist	Civil Engineer (MSc degree)	CI: 8 years. O: 5 years.
E6	Technical Office Chief	Civil Engineer (MSc degree)	CI: 20 years. O: 7 years.
E7	Project Manager	Architect (MSc degree)	CI: 12 years. O: 5 years.
E8	Project Manager	Architect (MSc degree)	CI: 15 years. O: 6 years.
E9	Project Manager	Architect (MSc degree)	CI: 22 years. O: 12 years.
E10	Board Member	Civil Engineer (MSc degree)	CI: 15 years. O: 8 years.
E11	Project Manager	Civil Engineer (MSc degree)	CI: 32 years. O: 14 years.
E12	Technical Office Chief	Civil Engineer (MSc degree)	CI: 13 years. O: 8 years.
E13	Project Manager	Civil Engineer (MSc degree)	CI: 11 years. O: 6 years.
E14	Technical Office Chief	Civil Engineer (MSc degree)	CI: 13 years. O: 6 years.
E15	Technical Office Engineer	Civil Engineer (MSc degree)	CI: 9 years. O: 5 years.
E16	Contract Specialist	Civil Engineer (MSc degree)	CI: 14 years. O: 7 years.
E17	Tender Specialist	Civil Engineer (PhD degree)	CI: 26 years. O: 10 years.

CI: construction industry, O: off-site construction.

).

Experts were selected based on the expert evaluation flowchart in Figure 2. Traditional AHP can be conducted with small sample sizes. Additionally, some researchers assert that AHP is a helpful method for analyzing subjective problems. Therefore, the authors expressed that a large data size is not needed to implement the method. Darko et al. [54] stated that the method can be conducted with a single qualified expert. In the literature, there are other examples regarding the sample size of the Pythagorean fuzzy AHP implementation, such as 5 experts [55].

A structured questionnaire type was implemented in this study and it consisted of six sections. In the first section, the study aim was explained to the participants. In the second section, questions helping to identify expert profiles were asked. For the filling questionnaire, examples were explained in the third section. The fourth section was designed to collect data with a pair-wise comparison matrix for the analysis of the importance level of criteria (O, C, and D). The fifth section was designed to collect judgments of experts related to main factor groups (“Organizational factors”, “External factors”, “Technical factors”, “Contractual factors”, and “Financial factors”) by considering criteria (O, C, and D). In the closing section, questions were designed to collect evaluations related to factors found under “Organizational factors”, “External factors”, “Technical factors”, “Contractual factors”, and “Financial factors” groups against criteria (O, C, and D). Data was collected with the face-to-face interviews.

4.3. Data Analysis with Pythagorean Fuzzy AHP

This study aimed to identify contractual and financial dispute causes and their priority orders by considering the FMEA framework. Multi-Criteria-Decision making (MCDM) methods are important to solve complex decision making problems. With the help of MCDM methods, the priority orders/the importance level of alternatives can be obtained by considering conflicting criteria (O, S, and D in the FMEA framework). After data collection from experts, the consistency index of each respondent was calculated. Analysis results for CI are represented in

Table 5. Consistency Index analysis results for pair-wise comparison matrix.

Expert ID	Consistency Index for FMEA Criteria
E1	0.02
E2	0.07
E3	0.004
E4	0.08
E5	0.03
E6	0.04
E7	0.02
E8	0.0
E9	0.08
E10	0.09
E11	0.08
E12	0.04
E13	0.01
E14	0.01
E15	0.02
E16	0.01
E17	0.02

. Analysis results showed that all pair-wise comparison matrixes are under 0.1. In other words, the matrixes are consistent.

Before fuzzy TOPSIS was used to obtain the weights of the main factors (financial and contractual), the criteria used in evaluating both main factors were calculated. Therefore, the aggregated matrix was calculated using the geometric mean method.

Table 6. Pythagorean fuzzy AHP analysis results for the calculation of weights of O, S, and D criteria.

	O				S				D				Result
	ml	mu	vl	vu	ml	mu	vl	vu	ml	mu	vl	vu	W
O	0.1965	0.1965	0.1965	0.1965	0.1	0.2	0.8	0.9	0	0	0.9	1	0.1233
S	0.8	0.9	0.1	0.2	0.1965	0.1965	0.1965	0.1965	0.1965	0.1965	0.1965	0.1965	0.3387
D	0.9	1	0	0	0.1965	0.1965	0.1965	0.1965	0.1965	0.1965	0.1965	0.1965	0.538

shows the aggregated matrix for O, S, and D criteria. The aggregated matrix was used and analyzed using Equations (1)–(7).

The findings showed that detection is the most important criterion for evaluating both the main factors and the factors of dispute causes in off-site construction projects. It is followed by severity and occurrences, respectively. The results of the Pythagorean fuzzy AHP (weights) will be used in the fuzzy TOPSIS analysis.

4.4. Data Analysis with Fuzzy TOPSIS Hybrid Approach

As stated above, even though this study aims to identify the causes of contractual and financial disputes for off-site construction projects, other factor groups that are important in disputes were considered together. Thus, the general ranks for the causes of contractual and financial disputes were calculated. The FTOPSIS analysis results for the calculation of factor groups were tabulated in

Table 7. FTOPSIS analysis results for the analysis of the importance level of factor groups.

	Normalized Weighted Matrix									Results
	O			S			D
	a	b	c	a	b	c	a	b	c	D+	d−	CCi	Rank
Organizational factors	0.05	0.08	0.10	0.13	0.20	0.27	0.28	0.39	0.49	2.35	0.68	0.225	4
External factors	0.04	0.07	0.10	0.15	0.23	0.29	0.13	0.24	0.36	2.47	0.57	0.186	5
Technical factors	0.07	0.10	0.12	0.16	0.23	0.30	0.31	0.43	0.54	2.25	0.78	0.257	3
Contractual factors	0.07	0.10	0.12	0.22	0.29	0.34	0.29	0.41	0.52	2.22	0.81	0.266	1
Financial factors	0.07	0.09	0.12	0.20	0.27	0.33	0.28	0.41	0.52	2.25	0.78	0.258	2

. Analysis results indicated that the most crucial factor groups for dispute causes are contractual, financial, and technical factors, respectively.

After calculating the importance level of the factor groups, contractual dispute causes were analyzed using the FTOPSIS method. The analysis results showed that C11 (Increase in contract value due to revision in scope of work) and C21 (Illegal work suspension) are the most important and common contractual causes of dispute for off-site construction projects. Moreover, these dispute causes are the most important dispute causes in the global ranking (See

Table 8. FTOPSIS analysis results for the analysis of the importance level of contractual dispute causes.

	Normalized Weighted Matrix									Results
	O			S			D
	a	b	c	a	b	c	a	b	c	D+	d−	CCi	Rank	Global Rank
C1	0.07	0.09	0.11	0.21	0.25	0.30	0.27	0.35	0.43	2.31	0.70	0.2335	16	51
C2	0.09	0.10	0.12	0.22	0.26	0.31	0.27	0.34	0.41	2.30	0.72	0.2378	13	40
C3	0.08	0.09	0.11	0.21	0.26	0.30	0.30	0.38	0.46	2.27	0.74	0.2462	8	32
C4	0.07	0.09	0.11	0.21	0.25	0.29	0.29	0.37	0.44	2.30	0.71	0.2372	14	44
C5	0.06	0.07	0.09	0.22	0.26	0.30	0.27	0.36	0.45	2.31	0.70	0.2333	17	52
C6	0.07	0.09	0.10	0.27	0.30	0.34	0.27	0.36	0.44	2.26	0.75	0.2505	5	25
C7	0.08	0.09	0.11	0.22	0.27	0.31	0.25	0.33	0.41	2.32	0.70	0.2320	18	55
C8	0.07	0.08	0.10	0.19	0.23	0.28	0.25	0.33	0.42	2.35	0.66	0.2202	20	66
C9	0.06	0.08	0.10	0.18	0.22	0.26	0.26	0.34	0.43	2.36	0.66	0.2178	22	71
C10	0.08	0.10	0.11	0.21	0.25	0.29	0.27	0.36	0.44	2.30	0.71	0.2364	15	45
C11	0.09	0.11	0.12	0.26	0.29	0.32	0.36	0.42	0.49	2.18	0.83	0.2749	1	19
C12	0.08	0.09	0.11	0.20	0.24	0.29	0.31	0.39	0.48	2.27	0.74	0.2455	9	33
C13	0.08	0.09	0.11	0.21	0.25	0.29	0.29	0.38	0.47	2.28	0.73	0.2429	10	34
C14	0.08	0.09	0.11	0.21	0.25	0.30	0.28	0.37	0.45	2.29	0.72	0.2395	12	38
C15	0.07	0.08	0.10	0.20	0.25	0.29	0.25	0.33	0.41	2.35	0.67	0.2220	19	62
C16	0.06	0.08	0.09	0.17	0.21	0.25	0.26	0.34	0.42	2.37	0.64	0.2120	24	78
C17	0.07	0.09	0.10	0.18	0.22	0.26	0.25	0.33	0.41	2.37	0.64	0.2130	23	77
C18	0.07	0.08	0.10	0.20	0.25	0.29	0.31	0.39	0.48	2.28	0.73	0.2429	11	35
C19	0.06	0.08	0.10	0.19	0.23	0.27	0.26	0.34	0.43	2.35	0.66	0.2200	21	67
C20	0.07	0.09	0.10	0.21	0.25	0.30	0.31	0.39	0.48	2.27	0.74	0.2463	7	31
C21	0.06	0.08	0.09	0.22	0.26	0.30	0.38	0.46	0.54	2.21	0.80	0.2668	2	20
C22	0.08	0.10	0.11	0.23	0.26	0.30	0.36	0.43	0.51	2.21	0.80	0.2659	3	21
C23	0.06	0.07	0.09	0.20	0.24	0.29	0.36	0.44	0.52	2.25	0.76	0.2537	4	24
C24	0.06	0.08	0.09	0.20	0.24	0.28	0.35	0.42	0.50	2.27	0.75	0.2477	6	28

).

The analysis of the causes of financial disputes was calculated using the FTOPSIS method. According to the results of the analysis, F17 (Non-availability of spare money for additional work) and F3 (delay in the payments—owner-based) are the most important and common causes of financial disputes for off-site construction projects. Moreover, the analysis results recommended that the utmost attention should be given to these dispute causes according to the global ranking results (See

Table 9. FTOPSIS analysis results for the analysis of the importance level of financial dispute causes.

	Normalized Weighted Matrix									Results
	O			S			D
	a	b	c	a	b	c	a	b	c	D+	d−	CCi	Rank	Global Rank
F1	0.10	0.11	0.12	0.26	0.28	0.31	0.31	0.36	0.42	2.25	0.76	0.2524	15	15
F2	0.09	0.10	0.12	0.29	0.31	0.34	0.31	0.36	0.42	2.22	0.79	0.2616	11	11
F3	0.10	0.11	0.12	0.28	0.31	0.34	0.33	0.39	0.46	2.19	0.82	0.2732	2	2
F4	0.08	0.10	0.11	0.26	0.28	0.31	0.34	0.40	0.46	2.22	0.78	0.2604	12	12
F5	0.08	0.10	0.11	0.26	0.28	0.31	0.37	0.43	0.49	2.19	0.82	0.2717	4	4
F6	0.09	0.10	0.11	0.24	0.27	0.30	0.33	0.39	0.46	2.24	0.77	0.2555	14	14
F7	0.09	0.10	0.12	0.24	0.27	0.30	0.36	0.42	0.48	2.21	0.80	0.2645	6	6
F8	0.08	0.10	0.11	0.25	0.28	0.31	0.38	0.44	0.50	2.19	0.82	0.2727	3	3
F9	0.09	0.10	0.12	0.26	0.29	0.32	0.31	0.38	0.45	2.23	0.78	0.2582	13	13
F10	0.08	0.09	0.11	0.24	0.28	0.32	0.30	0.36	0.43	2.27	0.74	0.2472	17	17
F11	0.08	0.09	0.11	0.25	0.28	0.32	0.35	0.41	0.47	2.22	0.79	0.2626	9	9
F12	0.09	0.11	0.12	0.27	0.30	0.33	0.34	0.38	0.43	2.21	0.79	0.264	7	7
F13	0.10	0.11	0.12	0.26	0.29	0.32	0.35	0.37	0.44	2.22	0.79	0.2620	10	10
F14	0.09	0.10	0.12	0.23	0.27	0.31	0.38	0.45	0.52	2.18	0.83	0.2748	1	1
F15	0.08	0.10	0.11	0.25	0.29	0.32	0.29	0.35	0.41	2.27	0.74	0.2459	18	18
F16	0.07	0.09	0.10	0.22	0.26	0.30	0.37	0.46	0.54	2.20	0.81	0.2695	5	5
F17	0.08	0.10	0.11	0.22	0.25	0.29	0.33	0.39	0.45	2.26	0.75	0.2477	16	16
F18	0.08	0.09	0.10	0.22	0.26	0.29	0.37	0.44	0.51	2.22	0.79	0.2631	8	8

).

4.5. Results of Sensitivity Analysis

In this study, three criteria (O, S and D) were considered to calculate the rank of the dispute causes for off-site construction projects. Within this context, six scenarios were available to test. In the scenarios, scenario 1 represents the main analysis results (see Table 8 and Table 9). The sensitivity analysis results for contractual dispute causes for off-site construction projects are presented in Figure 3. The analysis result indicated that C2, C6, C10, C20, C21, and C23 are sensitive and can show variety depending on the weights of the criteria.

The sensitivity analysis results for the financial dispute causes for off-site construction projects are presented in Figure 4. According to the sensitivity analysis results, F1, F2, F7, F8, F9, F12, F13, F14, F15, F16, F18, and F22 are sensitive dispute causes.

However, both of the financial and contractual dispute causes are sensitive depending on the value of criteria weights, the sensitivity of these dispute causes is clearly due to the increase in the weights of the lowest criteria, approximately three times (from 0.1233 to 0.3387) and four times (from 0.1233 to 0.538). Therefore, the analysis for the main results were more satisfactory.

5. Discussion

Off-site construction is one of the hot issues in the construction industry. It involves various innovations and benefits such as time, labor, cost, health and safety, waste reduction, less environmental pollution, and better life-cycle performance. However, there are some preventing factors for the development and adaptation of off-site construction practices in the construction industry. They lack standards and rely less on off-site construction products and quality issues. Moreover, communication and collaboration-related issues are important to enable a smooth process in off-site construction projects. They also lead to a reduction in the cost performance of off-site construction projects [56].

Furthermore, the integration and use of off-site construction products in construction projects is one solution regarding environmental sustainability in addition to issues seen in conventional construction methods. However, the adaptation and promotion of off-site construction methods is not an easy task due to the low trust level in technological innovation in the construction industry [57]. Therefore, this study aims not only to increase the body of knowledge but also to break prejudices regarding off-site construction by identifying possible dispute causes.

The analysis indicated that contractual and financial factor groups are the most significant dispute factor groups, respectively. The reason behind the results can be related to the importance and role of the contracts [58]. They help to regulate and organize the relationships between multiple parties by eliminating misunderstandings and misinterpretations. Moreover, off-site construction projects require different management approaches and risk allocation, since the activities in off-site construction projects can differentiate from on-site projects such as transportation, logistics, et cetera [59]. Additionally, building components produced with off-site construction methods require special technologies, equipment, and facilities. Therefore, the payment amount in advance is remarkably high compared to conventional practices. Thus, payment-related issues can jeopardize the process more severely.

The results also showed that C11 (Increase in contract value due to revision in scope of work) and C21 (Illegal and improper work suspension) are the most preeminent contractual dispute causes in off-site construction projects. In off-site construction projects, different stakeholders take part in building construction, such as manufacturers, suppliers, contractors, and assemblers [60]. Throughout the process of construction projects, changes in design and scope can occur. Consequently, the scope of work initially assigned to subcontractors may change. Due to these changes, it is possible for the contract value to increase. In off-site construction projects, where production and assembly occur in different locations, such disputes can significantly impact the cost and project timeline. Revisions in the scope of work for building elements manufactured with the off-site construction methods are more challenging once the manufacturing process is initiated. C21 (Illegal and improper work suspension) was found to be the most important second contractual dispute cause. The illegal suspension of work can jeopardize and deteriorate the relationship between parties [61]. In addition to tense relationships between stakeholders, it will induce project delays, cost overruns, and harmful impacts on the environment. Moreover, material procurement planned according to the contract can be affected severely. This will not only cause additional costs for materials but also hamper the relationship between producers and suppliers.

FTOPSIS analysis showed that F14 (Non-availability of spare money for additional work) and F3 (Payment delays-owner based) are the most important financial dispute causes in off-site construction projects. Off-site construction projects are constructed with the use of fabricated components. Changes or customization in the design and scope require an additional cost for materials, labor, and manufacturing processes [6]. Even though the changes are seen as unimportant, they can affect manufacturing processes negatively. Therefore, the scope of the work and compensation mechanism for changes should be addressed in the contracts. Furthermore, changing order management and approving procedures for the changes and their compensation is another principal factor in reducing financial disputes by considering unforeseen conditions in the projects. F3 (Payment delays-owner based) was found as the most important second dispute cause for off-site construction projects. As stated above, the production of off-site construction components requires upfront costs to procure materials, technologies, and other expenses. If the delays in the payments are realized in the process, it can affect the cash flow of the manufacturers and suppliers [62]. Additionally, it can activate the penalties in the contracts. Furthermore, if there are subsequent activities, it will also affect other parties. Therefore, the timeline for the payments should be negotiated and defined in the contracts.

Also, the studies using litigation cases as data sources were investigated and compared with the findings of this study. Nabi and El-adaway [6] found out that “payment holds and delays”, “lack of collaboration between various project trades”, “delay in project completion”, and “poor communication” are common causes of disputes. Within this context, even though the study results resemble each other in terms of the importance of “payment holds and delays”, the factor was not the most important factor in our study. According to the study results of Chan [13], ‘ambiguity in contract terms’, ‘poor contract draftsmanship’, ‘contract modification issues’, and ‘lack of industry readiness’ were found as the most important contractual dispute causes. However, the FTOPSIS analysis results presented in this study indicate completely different results. In other words, C11 (Increase in contract value due to revision in scope of work) and C21 (Illegal and improper work suspension) came into prominence. Additionally, the analysis results showed that C16 (Problems in terminology) is the least substantial dispute cause for off-site construction contracts, which parallels the findings of Chan [13] in his study.

Overall, our findings indicate the indispensable role of the contracts in the management of off-site construction disputes. Therefore, the study results presented in this study can be used to develop more balanced contracts for off-site construction projects.

6. Limitations and Recommendations

As a limitation, this study only reported the analysis of financial and contractual dispute causes for off-site construction projects. Since this study is ongoing, the analysis results for technical, operational, and external factor groups will be reported as a future study.

Also, the results of this study indicated that the importance levels of financial dispute causes are sensitive when the O, S, and D weights are changed critically. In other words, detectability is evaluated as less important than severity and occurrences; it will affect the importance levels of dispute causes. Therefore, this could be considered as a limitation.

Moreover, the data was collected from Türkiye (a developing country) in which the construction industry is a significant sector, contributing substantially to the national GDP. The country has seen a boom in construction projects, both in traditional and off-site construction methods. The use of off-site construction methods has accelerated, especially due to the economic crisis, earthquakes, and a population increase due to migration Therefore, the perception differences between developing and developed countries should be investigated so that potential discrepancies can be revealed. Moreover, the study does not consider the differences of stakeholders’ perspectives. It can be analyzed with another study.

Additionally, our findings can be used to create a contract guideline specific to off-site construction projects, which will help improve the use of off-site construction methodologies.

7. Conclusions

Off-site construction projects have gained importance due to their benefits, such as a safer environment, promotion of sustainability, fewer labor requirements, and less time to build a structure. However, the knowledge related to off-site construction is limited. Considering the low level of innovativeness of the construction industry, the use of off-site construction productions is limited compared to on-site construction productions.

Moreover, the literature review showed that using traditional project management practices and manufacturing processes is different in off-site construction projects. To increase the use of off-site construction productions, the issues that can be costly for stakeholders should be resolved and knowledge regarding off-site construction projects should be increased. Dispute causes are one of the issues that need to be addressed to increase awareness related to off-site construction projects. In the literature, three studies were conducted specifically on modular construction (that is under the off-site construction method), and the authors analyzed litigation cases to determine the dispute causes. However, the litigation case data set included events that were reflected in court. In other words, some dispute causes can be solved before the litigation process is initiated. Therefore, this study employs questionnaires to collect all dispute causes by considering the experience of experts.

In the study, FGD, Pythagorean fuzzy AHP, and the FTOPSIS methods were used to determine contractual and financial dispute causes, calculate the weights of criteria, calculate the weights of the factor groups, and calculate the weights of the factors, respectively. The results showed that contractual and financial factor groups are the most crucial factors. Moreover, the results showed that the detection of dispute causes has more importance than dispute occurrence and severity. By using the weights of the factor groups and criteria, the factors (under financial and contractual) were analyzed. According to the analysis results, C11 (Increase in contract value due to revision in scope of work) and C21 (Illegal and improper work suspension) in the contractual factor group, and F14 (non-availability of spare money for additional work) and F3 (Payment delays-owner based) in the financial factor group are the most important dispute causes. Moreover, the results regarding general ranks indicated that F14 (non-availability of spare money for additional work) and F3 (Payment delays-owner based) are the most important dispute causes for off-site construction projects. To overcome these dispute causes, the utmost attention should be paid to the preparation process of contracts. Moreover, the adaptation and implementation of blockchain and BIM technologies can be more convenient to solve these issues.

Theoretically, the root causes of dispute causes can be used for the implementation and facilitation of risk management. Practically, the awareness level of practitioners about the possible causes of off-site construction project disputes can be increased. Moreover, with the use of the study results, the ambiguities regarding the implementation of off-site construction projects can be reduced. Finally, the study results can be used to analyze the contracts of off-site construction projects to prevent and eliminate possible disputes.