Barriers to Building Information Modeling (BIM) Implementation in Late-Adopting EU Countries: The Case of Portugal

Abstract

Adopting building information modeling (BIM) within the architecture, engineering, and construction (AEC) industry presents an opportunity to tackle persistent challenges, such as chronic productivity deficits and emerging imperatives like sustainability. However, BIM implementation (BIMI) across European Union (EU) countries diverges due to different contexts and the complexity of BIM. This study aims to identify the main barriers to BIMI and recommend effective mitigation measures in Portugal, a late-adopting EU country. Initially, 28 BIMI barriers were identified through a literature review. Experts in a Delphi survey then selected 15 critical barriers. An interpretive structural modeling (ISM) model was developed with input from a focus group to clarify the hierarchical relationships among barriers, and an impact matrix cross-reference multiplication applied to a classification (MICMAC) analysis was performed to evaluate the barriers’ driving and dependence powers. The resulting main barriers to BIMI include a lack of evaluation mechanisms, ignorance of BIM benefits, a shortage of skilled professionals, limited experience and cooperation, resistance to change, and inadequate top management support. Finally, experts in a second focus group developed mitigation measures to address the main barriers while ensuring the measures affect the entire barrier system. These findings will assist researchers, policymakers, and practitioners in late-adopter EU countries in addressing these barriers effectively.

1. Introduction

The construction industry is crucial for the global economy and has a significant role in the growth and development of countries. The European Union (EU) BIM Task Group [1] reports that the construction sector is responsible for about 9% of the European Union’s GDP (gross domestic product) and provides employment to 18 million individuals. In Portugal, the construction industry accounts for 6.2% of total jobs and approximately 5% of the country’s GDP [2]. Moreover, according to Eurostat [3], the construction sector share of GVA (gross value added) varied between 5 and 6% in the EU from 2010 to 2021. These statistics highlight the importance of the construction industry in promoting economic growth and providing employment opportunities. Despite its importance, the construction industry has suffered few changes. This lack of progress means that the age-old problems and challenges associated with the construction industry, such as project delays and cost overruns, are still present, and newer ones, such as cleaner production and sustainability [4], are emerging.

The Architecture, engineering, and construction industry (AEC) is remarked as slow and hesitant toward innovation and technology, remaining heavily reliant on manual labor and ancient techniques and processes, with minimal use of technology [5]. The lack of investment in innovation has been a persistent problem for the industry, with the authors reporting that increasing research and development (R&D) expenditure could help address the productivity deficit compared with other industries [6,7]. Investment in R&D is minimal compared to other industries, ranging from 0.01% to 0.4% of the construction value added, compared to 3–4% in manufacturing and 2–3% in general industries [8]. New technologies and practices, such as artificial intelligence, sustainability, Lean methodology, business process reengineering, total quality management, and building information modeling (BIM), are being considered and tested to address this gap.

BIM is a technology and process that provides a collaborative digital environment for facility design, planning, construction, and operation, incorporating all relevant information in a cloud-based model accessible to all entities involved [9]. This technology has recently gained significant attention for its potential to address key challenges in the AEC industry. BIM offers solutions to several issues, including improved clash detection, enhanced and streamlined communication, reduced costs, and higher quality, all while boosting productivity [10]. Consequently, BIM addresses modern challenges like sustainability, cleaner production, and safety issues, while also including cost estimation and facility management tools [11]. By converting fragmented, paper-based practices into a unified digital platform, BIM enhances coordination, automates clash detection, and clarifies costs and timelines, all while incorporating sustainability assessments during both the design and the construction stages [4,11]. BIM plays a crucial role in digitizing the built environment, positioning itself as a cornerstone in the construction industry’s shift towards Construction 4.0 [12].

Charef et al. [13] state that BIM adoption within the EU varies significantly. The economic, societal, cultural, and political factors impacting BIM implementation (BIMI) differ from one EU country to another, making a uniform approach unrealistic. Finland, Denmark, the Netherlands, the UK, and Lithuania are identified as early BIM adopters, while Germany, Italy, Poland, and Portugal are considered late adopters. Bulgaria, Greece, and Malta fall into the category of very late adopters. Rezahoseini et al. [14] also classify Portugal as a late adopter.

Mitera-Kiełbasa and Zima [15] found that 35% of European countries have and plan to introduce BIM mandates, emphasizing the decisive role of BIM in improving construction practices and promoting policy frameworks. Once the EU aims to achieve standardized and unified BIM practices across Europe, it is imperative to identify the barriers hindering BIM in late adopters and devise effective mitigation measures. Barriers to BIMI include technological, organizational, financial, legal, and cultural factors that obstruct or delay the adoption, integration, and effective use of BIM processes and tools within the AEC industry. In the literature, several studies deal with the barriers to BIMI; however, they are scarce in the European context.

This study aims to identify the main barriers to BIMI in Portugal, a late-adopting EU country; comprehend how they are interrelated; and design effective mitigation measures to lessen their impact and leverage BIMI. The main research questions are as follows: What are the main barriers to BIMI in the construction industry? What is the nature of these barriers? How are these barriers interrelated regarding hierarchy, driving, and dependence powers? What are the measures to mitigate these barriers?

This study makes two main contributions. First, it presents a new perspective on BIMI in Portugal, a late-adopting EU country, thereby expanding the literature. Second, it expands the application of combined interpretive structural modeling (ISM) and impact matrix cross-reference multiplication applied to a classification (MICMAC) analysis by developing measures to tackle the main barriers while considering their impacts on other hierarchically dependent barriers.

From a professional and practical standpoint, the findings of this research enable governments and the construction industry to identify and outline a roadmap of actions to address the main barriers, thereby improving the conditions for successful BIMI.

The paper organization is the following: after the introduction, Section 2 presents the literature review, Section 3 shows the research approach, Section 4 presents the findings, Section 5 discusses the findings and recommends mitigation measures, and Section 6 presents the main conclusions, implications, and limitations.

2. Literature Review of Barriers to BIM Implementation

In the short term, BIM involves significant technical knowledge and raises the costs of operations of companies due to the need for implementation and training [16]. These burdens, hampered by the traditional resistance to change in the construction industry, have generally stalled the BIMI rate. However, several studies have revealed that the benefits associated with BIM compensate for its drawbacks, hence the government’s push for adoption in developed countries [17], as is the case of the EU countries [13].

Several studies in the last decade and a half have tackled BIMI in different contexts and using various research methodologies. Most of these studies relied on literature reviews to identify BIMI barriers. In the present study, the same approach was adopted. To do so, the Web of Science and Scopus databases were searched with a combination of the following keywords: “BIM”, “building information modeling”, “implementation”, “adoption”, “barriers”, “critical success factors”, and “mitigation measures”. After title and abstract analysis, 27 articles were selected for review to determine barriers (

Table 1. Findings of studies on barriers to BIMI over the past decade and a half.

Author, Country	Main Aim	Methodologies	Main Barriers and Findings
Gu and London [18], Australia	Assess the role of BIM in the AEC industry and identify challenges to its adoption	Literature review and assessment of BIM in the industry	Issues with data organization, communication standards, security, a lack of clarity around roles and responsibilities, and a need for better training and support
Kassem, Brogden, and Dawood [19], UK	Analyze barriers and drivers for BIM and 4D technology adoption	Literature review and survey of AEC professionals	Unclear benefits, resistance to change, lack of experience, inconsistent adoption, contract limitations, and time and cost concerns. The paper highlights that overcoming non-technical barriers is crucial to bridging the gap between technology and end users.
C. W. Chan [20], Hong Kong	Examine BIM use among design companies for public housing projects and barriers to adoption thereof	Questionnaire survey	Lack of skilled staff, inadequate training, no standards, and low client demand. The study suggests that the government, industry, and educational bodies should collaborate to set clear BIM standards and offer targeted training to improve adoption.
Rogers, Chong, and Preece [21], Malaysia	Explore BIM adoption by consulting companies, focusing on perceptions and drivers for adoption	Focus group, surveys, Pearson analysis	Lack of well-trained personnel, lack of guidance and government support. Companies are willing to adopt BIM, driven primarily by market demand and the pursuit of competitive advantage.
M. R. Hosseini, Banihashemi, et al. [22], Australia	Examine BIMI in small and medium-sized enterprises (SMEs) using innovation diffusion theory	Questionnaire survey and partial least squares structural equation modeling (PLS-SEM)	Reluctance to implementation on account of uncertain return on investment (ROI) and low interest in BIM from supply chain entities
Bosch-Sijtsema et al. [23], Sweden	Explore constraints and driving forces of BIMI with respect to mid-sized contractors	Interview and questionnaire survey	Partners that do not use BIM, a lack of demand from clients, and an absence of internal demand in the company
Ayinla and Adamu [24], UK	Investigate BIM adoption in SMEs, mainly focusing on reasons for delays in adoption	Mixed-method approach with online questionnaires and expert interviews	Cost, organizational culture, lack of expertise, low client demand, and legal and technology challenges
Olawumi et al. [4], eight different countries	Explore barriers to BIM and sustainability integration across eight countries	Delphi survey, descriptive and inferential analysis, and interrater agreement	Resistance to change, lengthy adaptation period, lack of BIM and sustainability workflow understanding
Gamil and Rahman [25], Yemen	Investigate practitioners’ awareness of BIM and identify the main barriers of BIMI throughout the project’s life cycle	Literature review, questionnaire survey, and descriptive analysis	Financial restrictions, lack of BIM knowledge, improper introduction of BIM concepts, lack of awareness of BIM benefits, and no governmental enforcement
G. Ma et al. [26], China	Investigate institutional and technological factors affecting BIM adoption	Literature review, ISM, and MICMAC analysis	Insufficient corporate and project leadership, inadequate software functionality, limited financial support, lack of trust and respect, and challenges related to complexity, interoperability, and compatibility
D. W. M. Chan, Olawumi, and Ho [27], Hong Kong	Identify benefits and barriers to BIMI	Questionnaire survey and comparative analysis	Resistance to change, inadequate organizational support, and lack of industry-wide standards. Key benefits of BIM include improved cost estimation and control, more efficient construction planning and management, and enhanced design and project quality.
Zhou, Yang, and Yang [7], China	Recommend strategies for advancing BIM adoption based on international experiences	Literature review and mapping of barriers	Insufficient government leadership, organizational and legal challenges, high costs, resistance to changing traditional practices, and lack of external motivation
Olanrewaju et al. [16], Nigeria	Evaluate the perceptions of professionals regarding BIM barriers	Literature review, questionnaire, descriptive statistics, and factor analysis	Few studies available, lack of knowledge, an absence of government policies, and high cost of implementation
Ma et al. [28], China	Explore BIM barriers at the project level in the AEC industry	Questionnaire survey, descriptive statistics, and principal component analysis (PCA)	Lack of experience and capabilities, technical conditions, system inertia, additional input, changes in work routines, and implementation risks
Saka and Chan [29], Nigeria	To analyze BIMI barriers for SMEs in the construction industry	ISM and MICMAC analysis	Lack of implementation strategies, low awareness, unclear benefits, interoperability issues, and no government mandate
Sun, Xu, and Jiang [6], China	Identify and categorize BIM barriers and make recommendations for adoption	Literature review, ISM, questionnaire, and expert interviews	Data ownership issues, incomplete BIM system standardization, lack of industry insurance, shortage of skilled BIM technicians, limited project experience, inadequate BIM infrastructure, misalignment in stakeholders’ views on BIM, changes in delivery models, and software functionality issues
Farooq et al. [30], Pakistan	Assess the current state of BIMI, and identify barriers and potential	Questionnaire survey, ISM, and MICMAC analysis	High initial costs, dissatisfaction with existing practices, and communication gaps within entities. The study concluded that BIM is more economical and efficient than traditional management techniques.
Manzoor et al. [31], Malaysia	Develop strategies for overcoming BIM adoption barriers	Literature review and questionnaire survey	Lack of BIM training, standards, guidelines, expertise, high costs, and insufficient research on BIM. The study also identified strategies to mitigate these barriers and a research framework to guide effective BIMI and sustainability.
Siebelink et al. [32], nine Western European countries	Improve the understanding of the barriers to BIMI and the maturity levels of BIM within organizations.	Multiple case study	Motivation, competence, and time capacity barriers exist at all organizational levels. Middle management is key to overcoming these barriers. Low BIM maturity is hampered by insufficient top management support. High maturity deals with more external challenges to maximizing BIM benefits.
Olanrewaju et al. [33], Nigeria	Examine BIM barriers in building projects, focusing on awareness	Literature review, questionnaire survey, and PLS-SEM analysis	Cost and standards, processes and economics, technology and business, training and personnel
Durdyev et al. [34], New Zealand	Prioritize barriers to BIM adoption during the facility management phase	Parsimonious fuzzy analytic hierarchy process (AHP) and expert interviews	High cost of software, hardware, and training; lack of expertise; and unfamiliarity with BIM. The study concludes that additional resources are needed to overcome these challenges and expand BIM adoption in facility management.
Onososen and Musonda [11], South Africa	Analyze barriers to BIM integration in sustainability assessments	ISM and MICMAC analysis	Poor interoperability of BIM tools, high investment cost, and complexity
Alemayehu et al. [35], Ethiopia	Investigates perceived BIM barriers and their significance, focusing on respondents’ personal and professional attributes	Literature review, survey, Relative Importance Index (RII), exploratory factor analysis (EFA), and regression model	Project complexity, low BIM maturity, liability, licensing, and maintenance issues
Munianday, A. Rahman, and Esa [36], Malaysia	Explore challenges faced by BIM adopters	Case study approach, in-depth interviews, and NVivo software analysis	Time and financial investment, resistance to workflow, and approach changes. Human resources and capital are the most critical elements influencing the adoption of new technologies and innovations.

).

Several methodologies were employed in the cited studies. Based on experts’ and researchers’ opinions, focus groups were employed to filter and adapt the barriers found in the literature to the study context and decide on the importance of the barrier or the relationship between them [21]. Questionnaire surveys were used to rank the barriers [23,25,31,37,38] or to determine the relationships between barriers by applying statistical analysis such as the Pearson relationship analysis [21], PLS-SEM [22], factor analysis [16], or principal component analysis [28]. The case study approach was used to understand the barriers to BIMI in specific and natural contexts [32,36]. Finally, several authors have recently adopted a combined ISM-MICMAC analysis approach [6,26,29,30].

Context-wise, there are studies in Australia [39], the UK [19], the Netherlands [40], China [6,7,26,28,41], Hong Kong [42], Nigeria [16,29], Pakistan [30], Iran [38], Jordania [37], Yemen [25], and Malaysia [31]. Nevertheless, these studies are scarce in the EU context.

Lastly, most studies do not present measures to mitigate the barriers to BIMI or do not explicitly present them [6,16,19,21,22,26,28,37]. In studies where measures are presented, they are typically designed considering the highest-ranked barriers [7,31,41], and when the hierarchical relationships between the barriers and their respective driving and dependent powers are determined (ISM-MICMAC analysis), the proposed measures do not adequately take advantage of these results [30].

3. Research Methodology and Materials

This section outlines the research methodology and the data utilized in this study for clarity and convenience.

3.1. Research Methodology

Mixed-methods research (MMR) integrates qualitative and quantitative elements to answer the research questions [43]. The MMR adopted in this study includes a literature review, a Delphi survey, focus groups (FGs), and an ISM-MICMAC analysis. These research methods are well suited for studies involving human actions or behaviors in construction projects, such as BIMI [44]. The proposed research methodology has four stages (Figure 1): Stage I—determination of the critical barriers to BIMI; Stage II—ISM model; Stage III—MICMAC analysis; and Stage IV—development of mitigation measures.

The ISM model was introduced by Warfield [45]. It is a group learning procedure supported by a computer and employed to research the relationships between various variables regarding a specific topic of a particular dynamic, complex, and multifaceted system [46]. It decodes vague mental models into observable and well-defined systems, expanding the understanding of the system’s variables by defining their interrelationships and hierarchy. Moreover, ISM integrates experts’ opinions based on their experience and knowledge, permitting review opinions and change judgments. ISM considers that variables (barriers in this study) at the top of the hierarchy, designated root variables, largely control the system’s behavior, influencing other variables.

Duperrin and Godet [47] developed MICMAC analysis based on the multiplication properties of matrices to distribute and better comprehend a set of system variables according to their driving power (DVP) and dependence power (DEP). The DVP represents the variable’s capacity to influence others, and the DEP shows the level to which others influence it. The MICMAC analysis results in a DEP-DVP diagram with the variables placed in one of four clusters: independent (strong DVP and weak DEP), linkage (strong DVP and strong DEP), dependent (weak DVP and strong DEP), and autonomous (weak DVP and weak DEP). Variables in the independent cluster are considered the more influential ones. The MICMAC analysis complements the ISM model in determining the main barriers to BIMI, which include the barriers from the independent cluster (strong DVP and weak DEP), along with root barriers (the highest ISM level). Moreover, the MICMAC analysis also reveals barriers that are potentially not integrated into the system of barriers, specifically those in the autonomous cluster that present weak DVP and DEP.

A Delphi survey and two FGs (FG-1 and FG-2) were conducted to gather expert opinions. Through successive rounds, the Delphi survey produces and refines group judgments [48]. It is grounded on the premise that “pooled intelligence” enhances individual opinion and captures the collective opinion of a group of experts. It enables experts to anonymously share their knowledge and opinions on a complex subject, perceive how their opinions align with others, and revise them if desired after reviewing the group’s findings. The Delphi survey is an iterative, response-based method for achieving consensus among experts [49]. Although no clear rules specify the number of participants for a Delphi survey, Needham and de Loë [49] indicate a minimum sample size of 10, as a smaller size may not generate enough diversity.

The FG is a research approach, exploratory by nature, that gathers qualitative data on a subject through group interaction facilitated by a moderator [50]. FGs encourage discussion among experts about their perceptions, beliefs, opinions, and attitudes toward a product, concept, or theory. Kitzinger [51] suggested that an FG must include between 4 and 12 experts. The moderator of the FGs, one of the authors, facilitated consensus-building, encouraged open discussion, and ensured the progression of debate from general to specific topics to foster sincerity and minimize bias [50]. During the FGs, each expert’s input held equal importance in decision-making. However, whenever a consensus was not reached, “the minority gave way to the majority.”

3.2. Stage I: Determination of the Critical Barriers to BIMI

Stage I of the methodology encompasses two steps (Figure 1). First, three BIM experts—one academic in civil engineering with over 15 years of experience and two practitioners, each with over 10 years of experience in construction projects—assisted in consolidating similar barriers from the literature to eliminate redundancies and then adapted them to fit the Portuguese context. This process yielded 28 distinct barriers (

Table 2. List of barriers to BIMI from studies over the last decade and a half.

No.	Barrier	References
1	Lacking functionalities of BIM tools	[6,7,19,26,32]
2	Complexity of BIM tools	[4,11,19,25,31]
3	BIM-related project risks, and engineering and information defects	[4,18,25,29,35]
4	Immaturity of BIM technology	[23,28,34,52]
5	Interoperability difficulties of the software	[4,6,11,18,19,20,22,23,24,25,26,27,29,30,31,33]
6	Software acquisition cost	[4,6,7,19,20,21,22,23,24,25,26,29,30,31,33,53]
7	IT investment necessary for the transition to BIM	[4,6,20,23,25,26,27,29,30,31,33,34,36,54]
8	Time and capital investment in training	[4,22,23,25,26,28,33,34,52]
9	Change in work method required	[6,7,21,25,28,31,32]
10	Lack of BIM standards and implementation strategies	[4,7,21,22,25,26,27,28,29,31,33]
11	Lack of support and knowledge from top management	[4,6,23,24,25,26,28,29,30,32]
12	Need for corporate restructuring	[4,7,20,32]
13	Lack of internal communication protocols	[4,7,20,32]
14	Current methods provide satisfactory results	[4,28,29,30]
15	Weak cooperation in BIM adoption from other stakeholders	[4,20,23,25,26,27,28,31,32,33]
16	Lack of IT structure in the firm	[20,28]
17	Lack of experience within the firm for BIMI	[4,6,7,20,21,23,24,25,28,30,31,32,33]
18	Weak cooperation from other industry partners	[32,54]
19	Resistance to change	[6,7,22,23,24,27,29,30,31,32,33,55]
20	Lack of available BIM training	[18,20,25,27,28,30,31,33]
21	Scarcity of BIM-capable professionals	[4,6,22,27,28,30,33,52]
22	Lack of client demand	[4,7,20,22,23,24,25,28,29,31,32,33]
23	Ignorance of BIM capabilities/benefits	[22,24,25,26,29,31]
24	Lack of evaluation and feedback for successful BIMI	[4,6,7,23,26,27,28,31,33]
25	Fragmented nature of the construction industry	[4,32]
26	BIM data ownership and rights	[4,6,7,20,24,31,33]
27	Lack of government regulation	[4,7,20,21,22,24,25,26,28,29,30,31,32,33,35]
28	Concerns related to the safety and insurance framework of BIM	[6,7,20,27,31]

).

In the second, a panel of 12 Portuguese experts was selected to identify the critical barriers through a Delphi survey. Three of them were researchers in civil engineering from regulatory authorities such as LNEC (Portuguese National Civil Engineering Laboratory), the Portuguese Order of Engineers, and AECOPS (Portuguese Association of Construction, Public Works and Services Companies). The other nine were practitioners, including two contractors, two consultants, two clients, one designer, and two senior managers with a background in civil engineering. All these experts had over 10 years of experience each in the AEC field, with an average of 18 years. To improve the reliability and validity of the Delphi survey results, a non-probability sampling method was used to select experts, promoting diversity in professional skills, geographic distribution, and experience levels, thus capturing a broad range of informed perspectives and opinions.

The experts initially received an e-mail explaining the study’s objectives and presenting the list of BIMI barriers, inviting them to address any misunderstandings, ambiguities, or redundancies. Subsequently, the rounds of the Delphi survey commenced. At each round, the experts received an e-mail questionnaire comprising the 28 barriers. They were requested to score each barrier on a seven-point scale, where “7” designates that the barrier is highly critical, “4” critical, and “1” slightly or not critical to BIMI [48]. Following each round, the geometric mean of the scores was calculated to mitigate the impact of extreme scores. If the geometric mean of a particular barrier was greater than or equal to 5.0, that barrier was classified as critical [48].

In the first round of the Delphi survey, nine barriers were identified as critical. In the second round, the experts were informed of the results from the previous round and asked to score each barrier again, resulting in 15 critical barriers. To ensure anonymity and thus minimize bias, between rounds, the experts only had access to the global score (geometric mean) of the barriers. In the third round, using the same procedure, the experts confirmed the same 15 critical barriers identified previously. Thus, following the recommendation from Ma et al. [26] to limit the number of barriers to 15 or fewer to reduce the effort required to develop the ISM model, the Delphi survey was concluded after the third round. Figure 2 displays the geometric mean of the barrier scores, with those above 5.0 being deemed critical. These critical barriers are presented in

Table 3. List and description of critical barriers to BIMI.

Code	Barrier—Description
B1	Software acquisition cost—Decision-makers may lack awareness of the long-term benefits of BIM [16], and high initial software procurement costs may contribute to a perceived negative ROI [4].
B2	IT investment necessary for the transition to BIM—Given the significant computing power required by the BIM process, most businesses must upgrade their existing hardware, network, and other inadequate infrastructure components [4].
B3	Time and capital investment in training—Successful BIMI requires companies to offer comprehensive training to their employees, as BIM tools, workflows, and protocols diverge from traditional practices. Early-stage training poses the most significant challenge to BIM success [10].
B4	Change in working methods required—BIM procedures differ from traditional practices [6]; inadequate BIMI strategies exacerbate the challenges associated with adapting to new work methods.
B5	Lack of BIM standards and implementation strategies—Lack of BIM standards and information on BIMI strategies poses great obstacles for companies transitioning to BIM [27,31].
B6	Lack of support and knowledge from top management—Top management is accountable for strategic decisions impacting the company’s success. Having years of experience and knowledge of traditional methods, they often tend to be risk-averse when it comes to engaging in BIM [24].
B7	Need for company restructuring—According to Ossick and Neff [56], project managers play a crucial role in BIMI. However, traditionally, projects have operated as separate entities within companies. Therefore, it is essential to restructure and clearly define the organizational framework of companies to facilitate cooperation and collaboration between projects for the success of BIMI.
B8	Weak cooperation in BIM adoption from other entities involved—Construction projects involve multiple entities with specific interests in successful project development. While BIM is intended to increase collaboration and communication, it demands the active participation of all entities [7].
B9	Lack of experience within the company for BIMI—Kassem et al. [19] argue that successful technology implementation relies on an adequately trained and experienced workforce to avoid increased costs and delays motivated by corrections and adjustments [6].
B10	Resistance to change—Resistance to change undermines change objectives, potentially leading to procedural failure. However, technological advancements and innovative methods offer a competitive edge to adopters. Chan et al. [27] have identified cultural resistance to change as a significant barrier.
B11	Scarcity of BIM professionals—Professionals with BIM skills are rare, primarily because of the industry’s failure to provide adequate training and development opportunities, particularly for recent graduates. This also stems from the lack of BIM in the curricula offered by universities, as Rogers et al. [21] identified.
B12	Ignorance of BIM capabilities/benefits—A lack of understanding of the benefits of BIM undermines its success potential, as companies and their employees fail to recognize the need for change and the advantages it could offer them [37].
B13	Lack of evaluation and feedback on successful BIMIs—BIM promotes new and improved working and relationship processes compared to traditional ones; therefore, further evaluation and feedback on successful implementation is needed [28].
B14	Fragmented nature of the construction industry—The construction industry is often fragmented, with knowledge from projects not consistently shared across teams or companies. This hinders collaboration, an essential element of successful BIMI [6].
B15	Lack of government regulation—The absence of mature regulations and contractual legislation for BIM and a lack of government incentives such as subsidies or tax reductions represent a major barrier to its widespread adoption [6].

. Notably, none of the barriers identified as critical for BIMI in Portugal are related to technology, which aligns with the findings of Kassem et al. [19]. From now on, the “critical barriers” will be referred to as only “barriers” for simplification.

3.3. Stage II: ISM Model

The development of the ISM model (Stage II, Figure 1) followed six steps (Figure 1) that are well established in the literature [57]. In Step 1, eight experts from FG-1—three researchers and five practitioners who had already participated in the Delphi survey—expressed the contextual relationships between pairs (i,j) of barriers. The following symbology was used: V—barrier i influences or leads to achieving barrier j; A—barrier j influences or leads to achieving barrier i; X—barriers i and j influence or lead to achieving each other; O—barriers i and j do not influence each other. The results were placed in the structural self-intersection matrix (SSIM) (

Table 4. Structural self-intersection matrix.

B(i/j)	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1		V	O	O	O	A	O	O	O	O	O	O	O	O	O
2			O	O	O	A	O	A	O	O	O	A	O	O	O
3				A	A	A	O	O	A	O	A	O	O	O	O
4					A	A	X	O	A	A	O	O	O	A	O
5						O	V	A	O	O	A	O	A	A	A
6							V	O	O	V	O	A	A	O	O
7								A	A	A	O	O	A	A	O
8									A	A	A	O	O	A	O
9										O	A	O	O	O	O
10											O	A	A	O	O
11												O	O	O	O
12													A	O	O
13														O	O
14															O
15

Note: B(i/j)—barrier in row i or column j.

).

The SSIM was transformed into the initial reachability matrix (IRM) in Step 2, a binary matrix representing the direct relationships between barriers, by replacing the letters with 1s and 0s: If SSIM(a,b) = V, then IRM(a,b) = 1 and IRM(b,a) = 0; if SSIM(a,b) = A, then IRM(a,b) = 0 and IRM(b,a) = 1; if SSIM(a,b) = X, then IRM(a,b) = IRM(b,a) = 1; if SSIM(a,b) = O, then IRM(a,b) = IRM(b,a) = 0. IRM(i,j) = 1 means that barrier i influences or leads to achieving barrier j; IRM(i,j) = 0 means that barriers i and j do not influence each other. The IRM is presented in

Table 5. Initial reachability matrix.

B(i/j)	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15
1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0
2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0
3	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0
4	0	0	1	1	0	0	1	0	0	0	0	0	0	0	0
5	0	0	1	1	1	0	1	0	0	0	0	0	0	0	0
6	1	1	1	1	0	1	1	0	0	1	0	0	0	0	0
7	0	0	0	1	0	0	1	0	0	0	0	0	0	0	0
8	0	1	0	0	1	0	1	1	0	0	0	0	0	0	0
9	0	0	1	1	0	0	1	1	1	0	0	0	0	0	0
10	0	0	0	1	0	0	1	1	0	1	0	0	0	0	0
11	0	0	1	0	1	0	0	1	1	0	1	0	0	0	0
12	0	1	0	0	0	1	0	0	0	1	0	1	0	0	0
13	0	0	0	0	1	1	1	0	0	1	0	1	1	0	0
14	0	0	0	1	1	0	1	1	0	0	0	0	0	1	0
15	0	0	0	0	1	0	0	0	0	0	0	0	0	0	1

Note: B(i/j)—barrier in row i or column j.

.

In Step 3, the transitivity check converted the IRM into the final reachability matrix (FRM). If barrier i influences barrier j, and j influences k, then barrier i indirectly influences k through j, and if IRM(i,k) = 0, then FRM(i,k) = 1*. The FRM was obtained through a Boolean operation [58], which involved self-multiplication of the IRM until it reached a stable result, as shown in Equation (1) (

Table 6. Final reachability matrix.

B(i/j)	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	DVP
1	1	1	0	0	0	0	0	0	0	0	0	0	0	0	0	2
2	0	1	0	0	0	0	0	0	0	0	0	0	0	0	0	1
3	0	0	1	0	0	0	0	0	0	0	0	0	0	0	0	1
4	0	0	1	1	0	0	1	0	0	0	0	0	0	0	0	3
5	0	0	1	1	1	0	1	0	0	0	0	0	0	0	0	4
6	1	1	1	1	1*	1	1	1*	0	1	0	0	0	0	0	9
7	0	0	1*	1	0	0	1	0	0	0	0	0	0	0	0	3
8	0	1	1*	1*	1	0	1	1	0	0	0	0	0	0	0	6
9	0	1*	1	1	1*	0	1	1	1	0	0	0	0	0	0	7
10	0	1*	1*	1	1*	0	1	1	0	1	0	0	0	0	0	7
11	0	1*	1	1*	1	0	1*	1	1	0	1	0	0	0	0	8
12	1*	1	1*	1*	1*	1	1*	1*	0	1	0	1	0	0	0	10
13	1*	1*	1*	1*	1	1	1	1*	0	1	0	1	1	0	0	11
14	0	1*	1*	1	1	0	1	1	0	0	0	0	0	1	0	7
15	0	0	1*	1*	1	0	1 *	0	0	0	0	0	0	0	1	5
DEP	4	10	13	12	10	3	12	8	2	4	1	2	1	1	1

Notes: B(i/j)—barrier in line i or column j; 1*—transitive linkage; DVP—driving power; DEP—dependence power.

).

$$\mathrm{I}\mathrm{R}\mathrm{M}\ne {\mathrm{I}\mathrm{R}\mathrm{M}}^2\ne \dots \ne {\mathrm{I}\mathrm{R}\mathrm{M}}^{n-1}\ne {\mathrm{I}\mathrm{R}\mathrm{M}}^n={\mathrm{I}\mathrm{R}\mathrm{M}}^{n+1}=\mathrm{F}\mathrm{R}\mathrm{M}$$

(1)

Next, in Step 4, the level partitioning of the FRM was performed to delineate the hierarchy among barriers. This process is iterative, starting with the creation of the reachability set (RS), the antecedent set (AS), and the intersection set (IS) for each barrier. The RS of barrier i comprises all barriers influenced by it (“1s” and “1*s” in row i of the FRM), while the AS comprises all barriers that influence it (“1s” and “1*s” in column i of the FRM). The IS contains common barriers to the RS and AS. When a barrier’s IS and RS are equal, the barrier is assigned to the current iteration (hierarchical level) and removed from the RS, AS, and IS for the next iteration. Essentially, if barrier B1 affects barriers B2, B3, and B4 (its RS), and B2, B3, and B4 (along with others in B1s AS) also influence B1, then B1 is regarded as being at its hierarchical level alongside B2, B3, and B4. This process continues until all barriers are partitioned into their respective hierarchical levels. In the present study, the FRM was partitioned into eight hierarchical levels (

Table 7. Level partitioning of the FRM.

Barrier	Reachability Set	Antecedent Set	Intersection Set	Level
B2	B2	B: 1, 2, 6, 8, 9, 10, 11, 12, 13, 14	B2	I
B3	B3	B: 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15	B3	I
B1	B1	B: 1, 6, 12, 13	B1	II
B4	B: 4, 7	B: 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15	B: 4, 7	II
B7	B: 4, 7	B: 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15	B: 4, 7	II
B5	B5	B: 5, 6, 8, 9, 10, 11, 12, 13, 14, 15	B5	III
B8	B8	B: 6, 8, 9, 10, 11, 12, 13, 14	B8	IV
B15	B15	B15	B15	IV
B9	B9	B: 9, 11	B9	V
B10	B10	B: 6, 10, 12, 13	B10	V
B14	B14	B14	B14	V
B6	B6	B: 6, 12, 13	B6	VI
B11	B11	B11	B11	VI
B12	B12	B: 12, 13	B12	VII
B13	B13	B13	B13	VIII

).

In Section 5, the ISM model was developed in Step 5, and lastly, in Step 6, FG-1 experts checked the ISM model for conceptual consistency, making necessary corrections.

3.4. Stage III: MICMAC Analysis

The MICMAC analysis development followed two steps (Stage III, Figure 1). First, for each barrier i, the DVP and DEP were calculated as the sum of 1s in row i and 1s in column i of the FRM, respectively (Table 5). Next, a DEP-DVP diagram was created, and the barriers were located in one of the four clusters, given their DVP and DEP.

3.5. Stage IV: Development of Mitigation Measures

In this stage, the FG-2 experts (the same ones that participated in FG-1) developed mitigation measures (MMs) for the main barriers to BIMI—barriers from the independent cluster (strong DVP and weak DEP) along with root barriers (the highest ISM hierarchical level). First, the experts interpreted and discussed the ISM model and the MICMAC diagram results. Then, they were requested to propose measures to act on and mitigate the main barriers, but considering that these measures should be capable of reaching and impacting the remaining barriers based on the hierarchy between them and their DVPs and DEPs. To ensure the MMs’ effectiveness, the experts were instructed to follow the hierarchy present in the ISM model, beginning with the highest-level barriers. Nevertheless, experts verified whether there was a need for dedicated MMs to address the barriers in the autonomous cluster, due to their reduced DEP.

These MMs were designed to address the main barriers that control the behavior of the barrier system towards BIMI. They operate through the hierarchical relationships among barriers, considering their DVP and DEP, and are supported by experts. Therefore, these measures are expected to be more effective than the MMs targeting individual barriers. MMs focusing solely on individual barriers may not address hierarchically dependent barriers, thereby failing to provide a systemic impact on barriers to BIMI.

4. Results

This section presents the ISM model and the MICMAC diagram.

4.1. ISM Model

To develop the ISM model, Step 5 of Stage II of the research methodology (Figure 1), first, the FRM canonic matrix was created by grouping barriers by hierarchical level to aid in structuring the ISM model (

Table 8. The canonical form of the FRM.

B(i,j)	B2	B3	B1	B4	B7	B5	B8	B15	B9	B10	B14	B6	B11	B12	B13
B2	I	0	0	0	0	0	0	0	0	0	0	0	0	0	0
B3	0	I	0	0	0	0	0	0	0	0	0	0	0	0	0
B1	1	0	II	0	0	0	0	0	0	0	0	0	0	0	0
B4	0	1	0	II	1	0	0	0	0	0	0	0	0	0	0
B7	0	1	0	1	II	0	0	0	0	0	0	0	0	0	0
B5	0	1	0	1	1	III	0	0	0	0	0	0	0	0	0
B8	1	1	0	1	1	1	IV	0	0	0	0	0	0	0	0
B15	0	1	0	1	1	1	0	IV	0	0	0	0	0	0	0
B9	1	1	0	1	1	1	1	0	V	0	0	0	0	0	0
B10	1	1	0	1	1	1	1	0	0	V	0	0	0	0	0
B14	1	1	0	1	1	1	1	0	0	0	V	0	0	0	0
B6	1	1	1	1	1	1	1	0	0	1	0	VI	0	0	0
B11	1	1	0	1	1	1	1	0	1	0	0	0	VI	0	0
B12	1	1	1	1	1	1	1	0	0	1	0	1	0	VII	0
B13	1	1	1	1	1	1	1	0	0	1	0	1	0	1	VIII

Notes: B(i/j)—barrier in row i or column j; levels are displayed diagonally, and the shadow demarcates the barriers at each level.

). Then, an initial digraph was prepared by placing the barriers vertically by partition levels and linking them with arrows. Finally, indirect links between barriers at different levels were eliminated to obtain the ISM model. The model illustrates the hierarchical levels and relationships among the barriers.

Finally, in Step 6, the FG-1 experts validated the ISM model and confirmed its consistency with their mental model of the system of barriers to BIMI. As a result, the ISM model was deemed adequate for representing the hierarchical relationships between the barriers (Figure 3).

4.2. MICMAC Diagram

The development of the MICMAC diagram followed Stage III of the research methodology (Figure 1). The barriers were placed into clusters within the diagram based on their DVP and DEP scores presented in Table 6 (Figure 4).

5. Discussion and Mitigation Measures

With the help of experts in the FG-2 (the same ones who participated in FG-1), this section discusses the results of the ISM model and MICMAC analysis and recommends MMs for the barriers to BIMI (Stage IV of the research methodology).

5.1. Discussion

5.1.1. ISM Model

B3 and B2 are at the top of the ISM model (Figure 3), at level I, the lowest hierarchical level. Although these barriers may significantly affect BIMI [29], they are greatly influenced by other barriers and will likely have little or no influence on others.

Level II comprises B7, B4, and B1. B7 and B4 influence each other and B3 directly, which is expected once corporate restructuring and changes in the work methods aggravate the need for time and capital to invest in training [29]. B1 is isolated at this level and directly influences B2; the higher the software acquisition cost, the higher the impact of B2.

B5, at level III, directly influences B7 and B4. Changing the corporate structure and working methods is more difficult without BIM standards and implementation strategies [59].

B8 and B15 are at level IV. These barriers are not interconnected, and both directly influence B5 [7]. Note that no barriers influence B15.

B9, B10, and B14 are at level V. They are not interconnected and directly influence B8 [4], and no barriers influence B14.

At level VI are B11 and B6, which are not interrelated. B11 understandably worsens the impact of B9, and, according to the experts, B6 aggravates the impacts of B10 and B1 (at level II).

B12 is at level VII and directly influences B6. Reducing the ignorance of BIM capabilities/benefits (B12) drives managers to support BIMI (B6) [37].

Finally, B13, the lack of evaluation and feedback on successful BIMIs, is at the bottom of the ISM model at the highest hierarchy level, which is level VIII. B13 directly influences B12 [60]; indirectly influences the other barriers at lower hierarchical levels, except B11, B14, and B15; and is not influenced by any barrier. In conclusion, B13, concerning the ISM model, is considered the root barrier to BIMI in Portugal.

5.1.2. MICMAC Analysis

Regarding the MICMAC diagram (Figure 4), B8 (weak cooperation in BIM adoption from other entities involved) is at the boundary between the linkage and dependent clusters. However, in the ISM model, B8 transmits the influence of higher-level barriers to lower-level barriers within the hierarchy, thus acting as a linkage barrier. A barrier in this category presents strong DEP and DVP; it acts as a transmission belt between independent and dependent barriers.

The autonomous cluster comprises two barriers, B1 and B15. They have weak DVP and weak DEP, meaning they are, to some extent, detached from the remaining system of barriers to BIMI. Thus, specific MMs may be required for these barriers.

The dependent cluster comprises five barriers: B2, B3, B4, B5, and B7. Weak DVP and strong DEP characterize these barriers. Thus, they are strongly influenced, but their influence on others is negligible. Therefore, if appropriate MMs are developed for the barriers in the independent cluster, in principle, additional specific measures for these barriers may not be necessary.

Lastly, the independent cluster includes seven barriers: B6, B9, B10, B11, B12, B13 and B14. These barriers have a strong DVP and a weak DEP, influencing most others but being barely affected by them. Therefore, they should be the primary target of the MMs.

5.1.3. Category of the Barriers

Lastly, aside from the process-related barrier (B13), which occupies the highest level (level VIII) in the ISM model hierarchy, levels VII and VI are dominated by cultural and industry (B12, B11, and B14) and organization-related barriers (B6, B9, and B10). Moreover, all these barriers fall within the independent cluster of MICMAC analysis. This highlights the significant role these categories of barriers play in influencing the overall system of barriers to BIMI. These findings align with those of Saka et al. [29]. Furthermore, the MICMAC analysis classifies the regulatory and legal-related barrier (B15) as autonomous, indicating that it lies outside the system of barriers; the other barriers do not influence the impact of the lack of government regulation (DEP = 1, it is only influenced by itself). However, B15 demonstrates some capacity to influence other barriers (DVP = 5), which is reflected in the ISM model, where it still influences some lower-level barriers: B5 directly, and B5, B7, B4, and B3 indirectly.

5.2. Mitigation Measures

After identifying the main barriers to BIMI in Portugal—both the root barriers from the ISM model and the barriers in the independent cluster of the MICMAC analysis, namely, B6 and B9 to B14—the experts from FG-2 (the same ones who participated in FG-1) were tasked with developing MMs to target these main barriers and simultaneously reach and mitigate the remaining ones. The main barriers are central to the dynamic behavior of the barrier system. The experts were also advised that the MMs could be tailored to lessen the barrier’s severity, reduce its impact on BIMI, or both. Lastly, they were informed that if the proposed measures did not effectively address the barriers in the autonomous cluster, additional measures needed to be established to tackle those barriers directly. A total of 14 MMs were proposed.

The lack of evaluation and feedback on successful BIMIs (B13) in Portugal means that the success of BIMI in the construction industry remains speculative, relying on comparisons to studies in other contexts that may not be applicable to Portugal. The experts ended up suggesting five MMs. Government funding of research studies to evaluate and collect feedback on BIMI (MM1) would enable the collection of valuable data and feedback on BIMI cases in Portugal and the effectiveness of their implementation process. Encouraging professional associations to work with industry leaders to establish the necessary support and knowledge base for BIM (MM2) would enhance collaboration and knowledge of BIMI, which could help future implementations avoid common mistakes and highlight key challenges encountered by prior implementation attempts [7]. Advocacy for adopting integrated project delivery (IPD) by the industry (MM3) would promote the involvement of entities early in the project and fortify trust among them. IPD implies that all entities collaborate, share information and risks, and make collective decisions to achieve project goals [61]. Encouraging BIMI pilot projects through the consortium participation of multiple companies (MM4) would facilitate resource pooling, enabling the development of practical experience and exploration of BIMI initiatives. These consortia should consist of companies of various sizes, project functions, and geographical areas to enhance the pilot and ensure that the insights gained can be broadly utilized across the construction industry.

Moreover, it would help companies gain practical experience with BIMI and could serve as a stepping stone for employees’ training [31]. Lastly, promoting collaboration between industry and experts to evaluate existing processes and frameworks for a phased BIMI (MM5) would create a continuous feedback loop among companies and experts, enabling progress to be tracked and essential information to be collected to guide future BIMI initiatives.

The experts suggested five more MMs concerning the ignorance of BIM capabilities/benefits (B12). Introducing BIM in university curricula and promoting research on this topic (MM6) would result in graduates better equipped to handle BIM-related decisions and increased BIM awareness within companies in the future [25]. The organization of BIM training seminars and workshops to raise awareness and encourage professional development (MM7) would provide participants with hands-on experience with BIM tools while explaining its fundamentals. This measure would help demystify BIM, increase awareness of its benefits, and create a continuous growth and learning culture, enabling companies to keep up with BIM practices [31]. The organization of BIM awareness seminars and conferences aimed at top management (MM8) would address their concerns, who may lack technical expertise but have key decision-making power, [24]). It should focus on BIM’s benefits for their organization and provide a roadmap for BIMI. Developing government-led legislation and guides to BIMI and subsidizing BIM-related costs (MM9) would guarantee companies a stable and transversal BIM environment and guide them through the necessary steps for a successful BIMI. Moreover, by subsidizing BIM-related costs, companies could reduce the financial burden of BIMI [4]. Lastly, the development of awareness campaigns aimed at all construction industry entities (MM10) would help address the general lack of BIM knowledge and help them understand the benefits of cooperation in BIM. MM6 to MM10 would benefit from specific BIM applications that showcase the usefulness and advantages of BIM, such as the bridge information model (BrIM) [62,63] or heritage building information modeling (HBIM) [64,65].

To overcome the lack of support and knowledge from top management (B6), the experts also suggested the creation of incentives in the form of prizes for companies that implement BIM effectively (MM11). This measure would reduce the financial costs of BIMI, like MM9, but in particular, the prize competition would further contribute to the promotion and visibility of BIM.

The scarcity of BIM professionals (B11) makes it difficult for companies to hire and retain them. To address this barrier, the experts added two more measures. Prioritizing BIM-capable professionals when hiring (MM12) might not be effective immediately due to their scarcity. However, it would highlight their importance and signal the market to encourage more training and certification in BIM. The involvement of employees in the BIMI process from the outset (MM13) would encourage them to give feedback and voice their concerns. This measure would allow companies to gain valuable insights into specific skills gaps and workforce training needs, thus adapting their training and development programs accordingly [4].

Concerning the last three main barriers—resistance to change (B10), lack of experience within the company for BIMI (B9), and ignorance of BIM capabilities/benefits (B14)—the experts considered that some of the MMs designed for the previous barriers already targeted them and that no further measures were necessary.

Regarding the two barriers of the autonomous cluster, the experts considered that the previously proposed measures were enough to address the lack of government regulation (B15). However, they suggested an additional measure for software acquisition cost (B1), which may be instrumental in addressing the financial burden of BIMI on SMEs. Sharing BIM-related expenses among entities involved in construction projects (MM14) would minimize costs and risk, leading to more coordinated and integrated BIMI processes [40]. This measure would improve communication and collaboration by providing a platform for all entities involved. Moreover, it would create a level playing field, as SMEs may not be able to afford the high upfront costs of BIMI and its associated risks [66].

Finally, experts reviewed and confirmed that the proposed measures effectively addressed all remaining barriers (B2 to B5, B7, and B8). Therefore, no additional measures were proposed.

6. Conclusions and Implications

This study focuses on the Portuguese case to understand the barriers to BIMI in late-adopting EU countries and proposes mitigation measures to overcome them. Of the 28 barriers identified in the literature, 15 were deemed critical. It is worth noting that technology-related barriers were not considered critical.

Seven of the critical barriers were identified as the main barriers. These barriers are foundational to the dynamics of the barrier system and, therefore, require priority attention. These barriers are cultural and industry-related: ignorance of BIM capabilities and benefits, scarcity of BIM professionals, and fragmented nature of the construction industry; organization-related: lack of experience within the company for BIMI, resistance to change, and lack of support and knowledge from top management; and process-related: lack of feedback on successful BIMIs. These barriers have a significant influence on others. It should be highlighted that although cost-related barriers affect BIMI, these are largely influenced by other barriers.

Finally, two sets of mitigation measures, totaling 14, are proposed to promote effective BIMI in the construction industry in Portugal. The first set consists of government-led or government-influenced initiatives, such as funding BIM research, encouraging collaboration on pilot projects and knowledge sharing, and integrating BIM into university curricula. The second set includes industry-oriented initiatives, such as adopting IPD and fostering collaboration among stakeholders to develop an effective phased approach to BIM. Moreover, some measures require active participation from government, universities, and research centers, while others necessitate collaboration across entities in the construction industry. The implementation of MMs in Portugal faces several challenges, particularly those requiring industry-wide collaboration and government support. These challenges arise from a fragmented industry, a weak regulatory framework for BIM, delays in governmental actions, traditional inertia within the industry, managerial resistance, limited institutional BIM capacity and knowledge, resource shortages, and a lack of trust essential for promoting joint ventures and cost-sharing models. A phased implementation, highlighting early wins, showcasing pilot examples, and securing support from professional organizations and academic institutions, is essential for building momentum and confidence in the industry.

This study makes two key contributions. First, it introduces a novel perspective on BIMI in Portugal, a late-adopting EU country, thereby expanding the literature. Second, it extends the applicability of the combined ISM-MICMAC analysis by deliberately developing mitigation measures to address the main barriers while potentially impacting other hierarchically dependent barriers.

Regarding policy implications, the government has a crucial role in advancing BIM adoption by financing research studies, developing relevant legislation and regulations, providing incentives, and encouraging BIM adoption through public procurement. Moreover, by acting as a client, the government can be among the first to implement BIM, allowing companies to identify market trends before they become widespread.

There are also practical implications. Companies should promote BIM skills through conferences, seminars, awareness-raising sessions, and training courses aimed at workers, management (all levels), and other entities involved in construction projects to promote rapid and sustained adoption of BIM. Furthermore, companies should enhance coordination and cooperation in implementing BIM both internally and among all entities involved in the construction project. This would lead to a more robust BIMI process and leverage its benefits.

Professional and industry associations should establish and document appropriate performance measurement mechanisms to improve BIMI and promote best practices by organizing training sessions, awareness seminars, and workshops. They should reward companies that effectively adopt BIM and reward their management. Additionally, they should promote collaboration with universities and research centers to integrate BIM topics into university curricula and encourage further research on BIM-related issues.

Finally, managers should embrace a holistic approach when crafting mitigation measures to address BIMI barriers, leveraging individual expertise and group interactions to determine the criticality of the barriers. Additionally, employing methodologies like ISM and MICMAC analysis helps identify the main barriers and develop mitigation measures accordingly. By integrating these approaches, managers can devise comprehensive and actionable measures to mitigate BIMI barriers.

Although this study offers valuable insights, it is not without limitations. Firstly, the FGs that developed the ISM model and the MICMAC analysis examined only 15 of the 28 barriers identified in the initial ranking questionnaire. However, the rankings of these barriers do not always align with their hierarchical positions in the ISM model or their power scores in the MICMAC analysis. Including additional barriers in the FGs could have revealed other lower-ranking barriers that might have been considered main ones. Secondly, the development of mitigation measures for BIMI barriers relied on subjective input from experts, which may introduce biases. Thirdly, while it is possible to generalize the findings from the Portuguese context to other late-adopting EU countries, this should be approached with caution. On one hand, the economic, social, cultural, and political factors impacting BIMI vary across EU countries. On the other hand, EU BIM directives are applied throughout European countries, which share a common economic space, favoring the generalization of findings. However, the proposed methodology can be adapted and applied in various contexts.

Nevertheless, the limitations present opportunities for future research. A comprehensive plan needs to be developed to implement the recommended MMs and evaluate their effectiveness in addressing barriers to BIMI. Additionally, relationships between barriers can be quantitatively assessed using appropriate statistical analysis tools such as PLS-SEM. Moreover, the proposed methodology can be replicated in different European contexts and other contexts.