Adoption of Building Information Modelling in the Saudi Construction Industry: An Interpretive Structural Modelling

Abstract

The Saudi Vision 2030 is a program of change management on a national level driven mostly by the use of digital technology. The implementation of building information modelling (BIM) is part of this change, and there is general agreement that its use improves the productivity and quality of the architecture, engineering, and construction (AEC) industries. Despite its extensive construction projects, Saudi Arabia has only recently planned for BIM. Several conditions must apply before it is successfully implemented. While the literature has identified the factors critical to its success and the barriers to its adoption, few studies have rated these factors in terms of their importance and their contingent impact. Furthermore, the interactional relationship between the factors has rarely been investigated. As a result, an interpretative structural model (ISM) was conducted to establish a hierarchy of variables, while accounting for the dynamic interaction between each. For factor selection, the matrix-based multiplication applied to a classification (MICMAC) method was utilized. Therefore, awareness of BIM and sustainability benefits are expected to be the most important variables in acceptance. Furthermore, the dynamic method is gradually shifting from bottom-down to a combined effect of top-down and bottom-up leadership.

1. Introduction

Building information modelling (BIM) is an interconnected workflow process based on 3D models, which are used for project planning, design, construction, and management. It utilizes shared data to generate coordinated digital design information and documentation, and anticipates performance aspects and prices. It is equally useful in completing a project in a faster, more cost-effective manner, and with much fewer ecological consequences. The technique is said to make project data easily accessible, accurate, and relevant to all stakeholders. Although some studies have claimed that BIM “remains at the development stage” [1], it is more appropriate to claim that it is being used at different dimensions on a variety of levels, and in a variety of geographic locations and industrial sectors. Certainly, the application of BIM technology is dependent on different critical factors that affect its implementation in various countries [2].

Countries and organizations are looking for new ways in which to establish physical and cultural infrastructure that can repay BIM investment. Multiple studies have examined the difficulty of establishing a standard evaluation model for measuring the success of BIM across a range of countries. A 2017 study identified some 27 countries with an early foothold in BIM development. From 2007 onwards, these countries have implemented government-mandated BIM regulations [3]. The study further shows a clear correlation between mandated government-backed BIM regulations (by or before 2016) and countries in which timely investment and specialization in BIM set the conditions for its success [3,4]. Additionally, the study confirms that early entry into the market, standardized work procedures, and government support are factors critical to the adoption and successful deployment of BIM [5].

For example, the Hong Kong government has enforced the use of BIM for all government projects costing more than HK$30 million, since 2018. Spain’s BIM commission has mandated it in buildings and infrastructural projects since 2018 and 2019, respectively [6]. Likewise, the UK government has mandated its use in all public high-rise projects since 2016 [7]. In 2016, the Saudi government’s 2030 Vision outlined its national forward plan for sustainable growth and diversified socio-economic development. The 2030 Vision aims to enact digital change from the bottom up, so that IT provides an attitudinal impetus for other sectors, and acts as a launch pad for entrepreneurial start-ups [8]. With the increased demand for sustainable “green” energy sources, the Saudi government has prioritized policies that will help to diversify its economy from natural resources, working towards a digitally enabled economy based on trade, tourism, and construction projects. This is expected to unlock the human potential of her predominantly young population. As a result of that, Saudi Arabia ranks top of the G20 countries in terms of digital competitiveness [9,10]. It is anticipated that this recalibration of the economic and digital model will help the construction industry prepare for the use of BIM.

Most studies investigating the adoption of BIM have identified some key factors required for its future development [11]. Past studies, however, have rarely focused on the interacting linkages between these components. This gap is partly explained by the challenge of mapping relationships when the key variables influencing a process or framework are subject to change. In this practical context, structural analysis may be a useful tool to guide managers on the application of BIM [12]. They can opt to deploy BIM either by a stepwise or company-wide approach, to coordinate data from multiple sources. The value, therefore, of identifying interactive relationships is that it informs choice and stimulates discussion within a changing environment [13]. On this basis, the fundamental factors and their relationship with secondary variables can be interpreted to develop a practical strategy.

Interpretive structural modelling (ISM) or structural analysis is a useful method for identifying the relationship between the fundamental and secondary factors that influence a process or framework [14]. Structural analysis lists the variables influencing BIM’s implementation, describes their interrelationship, and then identifies the critical ones [15]. It breaks down a complex process such as BIM implementation into multiple elements, informed by expert knowledge and opinions, and builds a layered or multi-level structural model which sets out the relationship between the factors that impact BIM. This interaction of variables will either be significant or dependent. Variables are classified into four types: independent, dependent, linked, and autonomous [16]. However, as well as representing the situation as it exists, structural analysis also recognizes and records trends, so it takes into account the dynamic process of changing factors. Indeed, changes in behaviors and processes are seen as a prerequisite for mastering a new technology.

In this work, we examined the application of BIM and identified the critical factors affecting its implementation in the Saudi construction industry. Additionally, we rated these factors in terms of their importance, and analyzed their interactional relationship. To realize this, we structured this paper by giving a general introduction (Section 1) to the topic of BIM, and reviewed some relevant literature (Section 2). Thereafter, we presented the research methodology adopted (Section 3). Section 4 and Section 5 contain the results and their discussion, respectively. In Section 6, we summarized the findings and derived some conclusions.

2. Literature Review

BIM is a relatively new technique in the Kingdom of Saudi Arabian (KSA) building sector [17]. The literature is ambiguous on the adoption and application of BIM in the Gulf Cooperation Country (GCC) countries. The methodologies used to implement it in the developed countries may not fit the characteristics of KSA’s Architecture, Engineering and Construction (AEC) industry [18]. The threat to the Saudi construction industry is that it will fall behind other countries that are benefitting from this technology and the associated updated work practices, which therefore places it at risk of being unable to compete in terms of efficiency. The adoption of BIM has seen a slow upward trend. The tactics proposed for its implementation in KSA include the establishment of enabling laws, a supportive legal framework, government financial assistance, and investment in education for the relevant stakeholders [19].

Saka and Chan [20] identify the high cost of implementation as a critical factor working against the adoption of BIM in developing countries. Although cost savings are cited as one of the chief reasons for BIM’s use [21], measuring its return on investment (ROI) is a work in progress, because it relies on assessing and apportioning multiple variables. The absence of instantaneous advantages from completed projects, according to [22], is one of the reasons for reluctance to deploy BIM. Besides, the complexity of identifying clear-cut corporate benefits adds significantly to other organizational hindrances affecting the deployment of BIM. Understandably, AEC managers wanting to benefit from the use of BIM should express a desire for a step-by-step learning process. However, implementing BIM is complex, because it must account for how professions and cultures interact, and how institutions make use of technology [23]. Complexity breeds regulations and protocols. The literature contains many vague and general statements, without reflecting the complexity and detail of BIM’s effect on organizational maturity.

Most studies investigating the conditions required for the successful adoption of BIM have isolated and graded some key success factors. Eadie et al. and Hetemi et al. [24,25] emphasize two major issues: standardization (i.e., the “functionality” and “design validation” of BIM tools), and another relating to top management’s institutional culture support and their involvement in the early determination of project goals. This is similar to the general classification into technological and institutional factors, as opined in [26]. Researchers in [27] also identify the difficulty of integrating suitably qualified project participants into the data-sharing processes, which reduces the availability of qualified staff [28]. Previous research studies have highlighted a shortage of experienced employees, as well as a lack of BIM expertise and training, as important barriers militating against BIM’s adoption in the AEC business [20]. Similarly, authors in Refs. [29,30] highlight three significant barriers: a lack of BIM research and expertise, absence or inadequacy of government policies, and high cost of implementation.

Industry reports and academic research have repeatedly cited certain universal conditions. One such condition is staff resistance to changing a well-established work technique [20]. Furthermore, the absence/inadequacy of IT infrastructure in AEC firms, insufficient computing competence levels among managers and workers, preference for familiar paper-based work, and scarcity of human resources and IT skills are factors specific to the Saudi context [31]. Other hinderances include a lack of consistent rules and standards and lack of support from the government [31]. A study by a Saudi national identifies the adoption of common standards and uniform specifications as essential to ensuring collaboration among AEC firms [32]. Protocols set out explicit contractual requirements to help establish common standards. Protocols enable BIM’s operation at defined stages or dimensions of a project by regulating working methods. The findings of a study on barriers to BIM implementation in Malaysia [33,34] and Nigeria [35] identify government’s limited involvement as a factor hindering increased BIM use [36]. Other obstacles to its adoption in Saudi Arabia, per the literature, include interoperability and functionality concerns caused by poor execution, the high cost of software, and a lack of national standardized specifications [36].

Just as the critical success factors of BIM’s implementation vary from country to country, studies also use a variety of classification methods. Ozorhon and Karahan [27] have classified them into human-related, industry-related, project-related, policy-related, and resource-related factors [37]. Furthermore, Amuda-Yusuf [38] uses factor analysis to categorize 28 critical success factors (CSFs) into five factors: dedication to and awareness of BIM among key stakeholders, capacity building for technology adoption, management’s commitment, cooperative harmony between experts in the field, and cultural perspectives. Additionally, Saka and Chan [20] review BIM success factors and the associated barriers within a socio-technical context, and classify them into three sub-groups: technology context, external environment, and internal or organizational factors. Another study in Ref. [39] identifies commonly shared universal CSFs relating to the most demanding aspect of BIM collaboration [40]. Implementation of the BIM process cannot be effective unless the design, engineering, and construction stakeholders collaborate. Nevertheless, the process of BIM implementation can be achieved if organizations limit their participation to non-integrated attributes, including producing accurate cost estimates from components, since this factor serves as an encumbrance to collaboration [41].

Most of the research literature agrees there is no simple introduction to the concept of BIM, although accounts describing the characteristics of this difficulty are hard to find. However, a few research findings refer to possible combinations for BIM applications in terms of levels and dimensions, which also help break its components into phases of collaboration [42]. The two broad issues emphasized by the authors in Ref. [25] relate to the standardization of BIM tools and institutional culture (management support) [28]. We must distinguish between its day-to-day commercial operation, and industry and government-backed efforts to embed BIM and facilitate its growth. The latter will only succeed if stakeholders share a joint vision and pursue a common plan. From the institutional perspective, companies in competition in the construction market must cooperate in industry-wide partnerships to win government backing to standardize protocols. Additionally, as study [4] makes clear, governments play a significant role in promoting BIM by mandating it in public projects, promoting training, and establishing financial and other incentives [3]. Organizations will determine how to utilize the potential of knowledge derived through data analysis and management. The vision of its users will determine how successful the technology is in altering companies and services, and how it interacts with them. BIM technology will have an immediate impact on institutional working relationships by reshaping them to encourage interpersonal cooperation [43].

Political, economic, social, and technological/technical (PEST) is a strategic tool for studying the prospective consequences of internal and external variables on enterprises and government policy. The PEST analytical framework is favored above other methodologies such as SWOT, in part because it can be used to unravel the interdependence of the different variables influencing BIM’s adoption, and how they function at various levels and sizes. PEST may take into consideration all these factors and explain how they may affect BIM’s implementation, perhaps increasing the popularity of BIM. Another justification for using PEST is that most BIM implementation studies have concentrated on architectural modelling, politics, and technology. These are significant, but they underestimate the social and economic factors that influence the need for long-term planning. This component classification reflects the goal of providing worldwide core classes for the data-sharing format [44]. The structure of the PEST analysis will be followed in the discussion. Each of these points will be covered in further details in the following sections (

Table 1. PEST Analysis.

Type	Factor	Definition/Description	References
Social	Awareness of BIM and sustainability benefits	BIM and sustainability success raises the awareness of their benefits among organizations.	[18,20,26,27,30,34,35,45]
	Knowledge and information ownership	Some management-level employees may believe that sharing knowledge weakens their ability to govern and instruct, which jeopardizes their position.	[46,47,48,49,50]
	Effective cooperation among project participants	A BIM deployment must be supported by the whole organization. It requires a well-articulated vision from top leadership outlining the benefits of adopting the BIM process for the company. Additionally, members and personnel should facilitate sharing of the model with other project participants.	[18,26,27,51,52]
	Top management support	It has long been recognized that top management support is critical to the success of information systems projects. Because of the hierarchical structure of organizations, interactions between nested levels are possible.	[25,51,53]
	Willingness to change ways of thinking and working	Traditionally management in construction has been remote, relying upon instructional methods and top-down information flows. BIM requires a strong organizational culture of collaboration and innovation, and benefits from internalized corporate attitudes that value critical thinking	[25,52,53,54,55]
	Trust and respect	A strong sense of trust among members, as well as mutual regard for both personality and career.	[18,25,26,51]
Economic	Cost viability	When regarded from the standpoint of society as a whole, a project is deemed economically feasible if the benefits outweigh the costs. The financial costs of the project are separate from the economic costs; externalities and environmental consequences must be considered.	[53,55,56,57]
	Demand	The amount of a product that customers are ready and able to buy at various prices during a specified period.	[57,58]
	Financial support	Running cost and constant investment in BIM.	[18,19,26,51,59]
	Early involvement	Construction trade organizations must lobby governments to mandate BIM’s use, and as soon as possible, provide financial incentives to invest in startups. Early entry into the market is linked to its successful application.	[4,25,26,53,54]
	BIM effectiveness evaluation criteria	Measuring BIM’s return on investment regarding assessments of its implementation efficacy.	[18,26,60]
	Formal incentive programs for using BIM	A motivation scheme for personnel and establishments who maintain and use BIM in practice.	[18,44,51,59,61]
Political/Legal	Government policies	Setting the terms, laws, and guidance that monitor establishments’ progression towards BIM.	[4,19,30,34,35]
	Employment policy	Demands and motive strategies for BIM skills when employing new personnel.	[26,27,59,62]
	New or edited templates of construction contracts	Setting a clear contractual relationship between partners, depending on BIM.	[47,53,63]
	Standardized work procedures for BIM	The adoption of common standards is a prerequisite for collaboration. The ownership and responsibility for managing building safety risks at different stages of the asset’s lifecycle must be set out in law.	[48,53,57,64,65]
	Standards to guide specific implementation	Protocols set out explicit contractual requirements which help to establish common standards. Protocols enable BIM’s operation at defined stages or dimensions of a project by regulating working methods. Protocols define tolerances for specific uses.	[26,35,66,67,68]
Technical/Technological	BIM training system	Pilot projects are one component of a well-thought-out BIM implementation plan. Vocational courses teaching lower-level digital skills can cooperate with universities teaching at a higher level.	[19,25,27,53,54,55,59,66]
	R&D plan	Continuous development of an R&D plan for BIM collaboration technology	[25,26,53,63]
	Simplicity	BIM technology is simple to understand and apply.	[25,26,59,69,70]
	Interoperability and compatibility	Collaboration requires interoperable software to provide an open workflow for data sharing. Interoperability is about the freedom to choose and mix the best tools, and those tools must use the same protocols.	[47,53,55,71]
	Cooperative management platform	Collaboration and values ensure team continuity. An integrated project is a significant change in culture for all team members at the organizational level, implemented by applying BIM to the integration of project information and processes.	[25,51,60]
	Functionality	Integrity, technological effectiveness, and customization necessitate BIM software functions’ fulfilment.	[19,25,26,51,60]
	Organizational innovation and learning	BIM cannot be successful as an isolated process. Collaboration is essential to its success. A strategic process should be designed to train and develop individual staff involved in its implementation.	[18,25,26]

).

The majority of studies investigating the factors influencing BIM adoption have relied on literature studies and surveys as the foundation for further analysis. However, the generalized assessments made in the literature are often not relevant to the Saudi context. So, the questionnaire method is used herein to explore the condition of BIM in Saudi Arabia. After that, unlike other methods of statistical analysis, which do not take full account of the changing relationships between variables, we used interpretive structural modelling, as it is well suited to representing the dynamic process of changing factors. Therefore, using the classification of PEST, this study exposes the dynamic relationships that make the factors critical rather than dormant or ineffectual.

3. Research Methodology

3.1. Hybrid Approach

This study employs a hybrid approach. First, a literature evaluation was used to identify the major parameters driving BIM’s adoption. Second, a questionnaire was developed to rank these variables. The reliability of the Likert scale was tested using the Cronbach’s α coefficient. According to Ref. [72], a coefficient > 0.7 should be considered a reliable scale. The Cronbach’s α was 0.917 on 24 items. Finally, to acquire expert comments on the contextual relationship between these features, an interpretive structural modelling (ISM) technique was employed. This study was carried out through focus groups by seven experts: two from the university, two contractors acting as project managers, an investor (owner), and two project managers from government agencies. By aggregating their perspectives, we believed we might be able to obtain an underlying attainable framework.

Authors in Ref. [73] created ISM to examine a complicated system by breaking it down into multiple subcategories, utilizing data acquired from professionals with expertise or experience in the issue [74]. The method concentrates on the quality of responses and places less emphasis on their quantity, making it possible to rely upon the participation of only a small number of knowledgeable and experienced interviewees for the survey [75]. This method is suited to the study of a nascent commercial domain when there is necessarily a shortage of experts in the research topic, as there is in the study of BIM in Saudi Arabia. Its clarity and accessibility have added to the technique’s widespread appeal for the study of complex systems in the AEC industry [76]. ISM is used because the data gathered from experienced experts are valid and reliable. It is particularly suited to the study of complex system dynamics such as innovation adoption. These issues make it a good fit for this study on BIM, which lacks experts with first-hand experience, in the Saudi context, thus ruling out a survey approach (Figure 1). In most circumstances, the following processes were used to determine how the different factors interact with one another:

(i)

Systematic meetings and a literature review assisted in defining the factors to be considered when evaluating the value.

(ii)

By comparing the detected elements, the conceptual link between them was established.

(iii)

A structural self-interaction matrix (SSIM) that may represent outcomes was built by accurately identifying the components.

(iv)

The SSIM was used to generate a reachability matrix (RM), which was used to assess a transition matrix. Using the integers 0 and 1, the RM was converted into a binary matrix. If factor S is linked to factor D and factor D is linked to factor F, then factor S relates to the essential tenet of ISM, which is linked to factor F, according to the transition rule of the factor’s conceptual relationship. If factor S is linked to factor D, and factor D is linked to factor F, then factor S is linked to an ISM basic notion.

(v)

The RM was categorized step-by-step, based on the findings of the fourth phase.

(vi)

Based on the staged matrices, a directed graph was created, which removed the transition connection from the RM. In addition, directed graphs were transformed into the ISM-based model to modify the nodes connecting each component.

3.2. Structural Analysis

Structural analysis is appealing because its application of common sense is simple. The matrix-based multiplication applied to a classification (MICMAC) approach was proposed by Xiao et al. [77]. It entails categorizing variables (or factors) based on a computation of driving power and reliance power. The approach clarifies and understands the interacting relationship between the variables. It displays the variables in four categories: independent, linked, autonomous, and dependent.

3.3. Analysis Based on the ISM

In several pieces of research, ISM has been utilized to analyze various aspects and their interactions [43,70,74,75,76,77,78]. Over the last 10 years, ISM technology, as discussed in the previous section, has been widely utilized in a range of research to understand the linkages between elements within a complete framework. Therefore, an ISM method was incorporated into the current research to analyze the factors and their interrelationships concerning BIM adoption.

3.4. Analysis of the Contextual Relationship and SSIM

The study initially developed a hierarchical structure between the identified components, and then analyzed their respective influence. Experts were asked to calculate the dynamic of the elements I and j using four symbols (V, A, X, and O), which are defined as follows:

(i)

V: i impacts j, but j does not influence i.

(ii)

A: barrier j impacts i but i does not influence barrier j.

(iii)

X: barrier i affects barrier j, and j influences barrier i.

(iv)

O: there are no relationships between components i and j.

To prevent subjectivity in the aggregate of replies, the “minority gives way to the majority” concept was used, as in previous research [79,80].

3.5. Analysis of RM

The initial reachable matrix (IRM) and final reachable matrix (FRM) were analyzed. The IRM was computed using binary matrices based on SSIM. The matrices i and j indicate the number of rows and columns, respectively.

(i)

“(i, j) = 1 and (j, i) = 0 in the initial RM if (i, j) is V in SSIM”

(ii)

“(i, j) = 0 and (j, i) = 1 in the initial RM if (i, j) is A in SSIM”

(iii)

“(i, j) = 1 and (j, i) = 1 in the initial RM if (i, j) is X in SSIM”

(iv)

“(i, j) = 0 and (j, i) = 0 in the initial RM if (i, j) is O in SSIM”

On the other hand, the FRM shows the influence or otherwise of one factor over the others. If a factor i influences another factor j, FRM can show the path linking them. The FRM was computed using Boolean rules, which are further expatiated in Section 4.

4. Results

4.1. Descriptive Analysis

The usage of BIM in the industry enhances quality service delivery and efficient execution of competitive projects.

Table 2. Ranking of variables.

Level	Rank	Factors	Factor Code
1	89	Top management support	16
2	87	Cost viability	14
2	87	Demand	15
3	86	Financial support	4
4	85	Government policies	1
4	85	Effective cooperation among project participants	13
5	82	BIM training system	3
5	82	New or edited templates of construction contracts	8
5	82	Functionality	24
5	82	Willingness to change ways of thinking and working	18
6	81	Standards to guide specific implementation	23
7	80	Early involvement of the sectors	17
7	80	BIM simplicity	20
8	79	Interoperability and compatibility	21
8	79	Standardized work procedures for BIM	5
9	78	Employment policy	2
9	78	Trust and respect	19
10	77	Awareness of BIM and sustainability benefits	10
11	76	Information and knowledge sharing and ownership	12
11	76	R&D plan	9
12	75	Cooperative management platform	22
12	75	BIM effectiveness evaluation criteria	6
12	75	Formal incentive programs for using BIM	7
13	74	Organizational innovation and learning	11

displays the total perceived effects of all the 24 factors. The severity index (SI) was used to rank the factors according to their significance. This ranking demonstrated that the top five factors in Table 2 had substantial influence on how BIM technologies were applied. The SI computation is shown by Equation (1) [81]:

$$\mathrm{SI}=\left({\displaystyle \sum }_{\mathrm{i}=1}^5{\mathrm{w}}_{\mathrm{i}}\times {\mathrm{f}}_{\mathrm{i}}\right)\times \frac{100\%}{\mathrm{n}}$$

(1)

Further discussions on these top five factors in Table 2 are given in Section 5.

4.2. Contextual Relationship and SSIM

Table 3. Structural self-intersection matrix (SSIM).

Factor Code	Factors	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24
1	Government policies		V	V	V	V	V	V	V	O	A	O	V	V	X	A	V	A	A	X	O	V	V	V	O
2	Employment policy			X	A	x	A	A	A	A	A	A	V	V	A	A	A	A	A	V	V	V	V	X	V
3	BIM training system				A	x	A	A	A	A	A	A	V	V	A	A	A	A	A	V	V	V	V	X	V
4	Financial support					V	V	V	V	V	A	V	O	V	A	A	A	X	A	X	V	V	V	V	V
5	Standardized work procedures for BIM						A	A	A	A	A	A	V	V	A	O	A	O	A	A	A	X	X	A	X
6	BIM effectiveness evaluation criteria							X	X	A	A	A	V	V	X	O	A	X	A	V	X	V	V	A	V
7	Formal incentive programs for using BIM								O	X	X	X	V	V	A	A	A	X	X	V	X	V	V	V	V
8	New or edited templates of construction contracts									A	A	A	V	V	A	A	A	A	A	V	X	X	V	A	X
9	R&D plan										A	X	V	V	X	O	A	A	A	O	V	V	V	V	V
10	Awareness of BIM and sustainability benefits											V	O	O	V	V	V	V	V	V	V	O	O	V	O
11	Organizational innovation and learning												V	V	A	A	A	X	X	O	V	V	V	V	V
12	Knowledge and information ownership													X	A	X	A	X	X	X	X	X	X	A	X
13	Effective cooperation among project participants														A	X	A	X	X	X	A	A	X	A	X
14	Cost viability															V	V	V	V	V	X	V	V	V	V
15	Demand																V	V	V	X	X	O	O	O	O
16	Top management support																	X	A	V	V	V	V	V	V
17	Early involvement																		A	O	O	V	V	V	V
18	Willingness to change ways of thinking and working																			X	X	V	V	V	V
19	Trust and respect																				X	O	V	A	V
20	Simplicity																					X	V	A	V
21	Interoperability and compatibility																						V	A	V
22	Cooperative management platform																							A	V
23	Standards to guide specific implementation																								V
24	Functionality

shows the SSIM for the aggregated responses of the experts. The table below shows the conceptual relationship, consisting of SSIM using the above-mentioned four symbols. Matrix i in the table is represented in the left column, while the top right row represents the matrix j.

4.3. Analysis of Initial Reachable Matrix (IRM)

For instance, the following may be used to evaluate the RM values of factors 1 (government policies) and 4 (financial support) in Table 3:

In Table 3, the SSIM value of (1, 4) is V, making the value of (1, 4) 1 and the

Table 4. Initial reachable matrix (IRM).

Factor Code	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	Driving Power
1	1	1	1	1	1	1	1	1	0	0	0	1	1	1	0	1	0	0	0	0	1	1	1	0	15
2	0	1	1	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	1	1	1	1	0	1	10
3	0	1	1	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	1	1	1	1	0	1	10
4	0	1	1	1	1	1	1	1	1	0	1	0	1	0	0	0	0	0	0	1	1	1	1	1	15
5	0	1	1	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	1	1	0	1	8
6	0	1	1	0	1	1	0	0	0	0	0	1	1	1	0	0	0	0	1	0	1	1	0	1	11
7	0	1	1	0	1	0	1	0	1	1	1	1	1	0	0	0	0	1	1	0	1	1	1	1	15
8	0	1	1	0	1	0	0	1	0	0	0	1	1	0	0	0	0	0	1	1	1	1	0	1	11
9	0	1	1	0	1	1	1	1	1	0	1	1	1	1	0	0	0	0	0	1	1	1	1	1	16
10	1	1	1	1	1	1	1	1	1	1	1	0	0	1	1	1	1	1	1	1	0	0	1	0	19
11	0	1	1	0	1	1	1	1	1	0	1	1	1	0	0	0	1	1	0	1	1	1	1	1	17
12	0	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0	1	1	1	1	1	1	0	1	10
13	0	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0	1	1	1	0	0	1	0	1	8
14	1	1	1	1	1	1	1	1	1	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	23
15	1	1	1	1	0	0	1	1	0	0	1	1	1	0	1	1	1	1	1	1	0	0	0	0	15
16	0	1	1	1	1	1	1	1	1	0	1	1	1	0	0	1	1	0	1	1	1	1	1	1	19
17	1	1	1	0	0	0	0	0	0	0	1	1	1	0	0	1	1	0	0	0	1	1	1	1	12
18	1	1	1	1	1	1	1	1	1	0	1	1	1	0	0	1	1	1	1	1	1	1	1	1	21
19	1	0	0	0	1	0	0	0	0	0	0	1	1	0	1	0	0	1	1	1	0	1	0	1	10
20	0	0	0	0	1	0	0	1	0	0	0	1	1	1	1	0	0	1	1	1	1	1	0	1	12
21	0	0	0	0	1	0	0	1	0	0	0	1	1	0	0	0	0	0	0	1	1	1	0	1	8
22	0	0	0	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	1	0	1	5
23	0	1	1	0	1	1	0	1	0	0	0	1	1	0	0	0	0	0	1	1	1	1	1	1	13
24	0	0	0	0	1	0	0	1	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	1	5
DEPENDENCE	7	17	17	7	20	10	10	14	8	2	10	22	23	6	7	7	9	10	15	16	18	21	11	21	616

values of (4, 1) 0, respectively (initial RM). The value of (1, 9) in Table 3 (SSIM) will be 0 if factor 1 (government policies) and factor 9 (R&D plan) are compared. In Table 4, the values of (1, 9) and (9, 1) are both zero (initial RM). Finally, the value of (11, 14) in Table 3 will change depending on how organizational innovation, learning factor 11 and cost viability factor 14 are compared (SSIM). Consequently, in Table 4, (11, 14) has a value of 0 but (14, 11) has a value of 1 in initial RM. In Table 4, this calculation yields a binary value that depicts the connection between each variable.

The transition rule serves as the foundation for the final RM in

Table 5. Final reachable matrix (FRM).

Factor Code	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	Driving Power
1	1	1	1	1	1	1	1	1	0	0	0	1	1	1	0	1	0	0	1	0	1	1	1	0	16
2	0	1	1	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	1	1	1	1	1	1	11
3	0	1	1	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	1	1	1	1	1	1	11
4	0	1	1	1	1	1	1	1	1	0	1	0	1	0	0	0	1	0	1	1	1	1	1	1	17
5	0	1	1	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	1	1	0	1	9
6	0	1	1	0	1	1	1	1	0	0	0	1	1	1	0	0	1	0	1	1	1	1	0	1	15
7	0	1	1	0	1	1	1	0	1	1	1	1	1	0	0	0	1	1	1	0	1	1	1	1	17
8	0	1	1	0	1	1	0	1	0	0	0	1	1	0	0	0	0	0	1	1	1	1	0	1	12
9	0	1	1	0	1	1	1	1	1	0	1	1	1	1	0	0	0	0	0	1	1	1	1	1	16
10	1	1	1	1	1	1	1	1	1	1	1	0	0	1	1	1	1	1	1	1	0	0	1	0	19
11	0	1	1	0	1	1	1	1	1	0	1	1	1	0	0	0	1	1	0	1	1	1	1	1	17
12	0	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0	1	1	1	1	1	1	0	1	10
13	0	0	0	0	0	0	0	0	0	0	0	1	1	0	1	0	1	1	1	0	0	1	0	1	8
14	1	1	1	1	1	1	1	1	1	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	23
15	1	1	1	1	0	0	1	1	0	0	1	1	1	0	1	1	1	1	1	1	0	0	0	0	15
16	0	1	1	1	1	1	1	1	1	0	1	1	1	0	0	1	1	0	1	1	1	1	1	1	19
17	1	1	1	1	0	1	1	1	1	0	1	1	1	0	0	1	1	0	0	0	1	1	1	1	17
18	1	1	1	1	1	1	1	1	1	0	1	1	1	0	0	1	1	1	1	1	1	1	1	1	21
19	1	0	0	1	1	0	0	0	0	0	0	1	1	0	1	0	0	1	1	1	0	1	0	1	11
20	0	0	0	0	1	1	1	1	0	0	0	1	1	1	1	0	0	1	1	1	1	1	0	1	14
21	0	0	0	0	1	0	0	1	0	0	0	1	1	0	0	0	0	0	0	1	1	1	0	1	8
22	0	0	0	0	1	0	0	0	0	0	0	1	1	0	0	0	0	0	0	0	0	1	0	1	5
23	0	1	1	0	1	1	0	1	0	0	0	1	1	0	0	0	0	0	1	1	1	1	1	1	13
24	0	0	0	0	1	0	0	1	0	0	0	1	1	0	0	0	0	0	0	0	0	0	0	1	5
DEPENDENCE	7	17	17	9	20	14	13	16	9	2	10	22	23	6	7	7	12	10	17	18	18	21	13	21	658

. For example, if factor S impacts factor D and factor D influences factor F, factor S effects factor F as well. The value of (1, 2) in Table 4 is 1, because “government policies” affects factor 2 (employment policy). The value of (2, 4) is 1, because factor 2 (employment policy) affects factor 4 (financial support) in Table 4. The transition rule may be used to alter the value of (1, 4) from 0 to 1 in Table 4. Furthermore, the value of (3, 2) in Table 4 is 1, since factor 2 (employment policy) has an influence on factor 3 (BIM training system). The value of (2, 1) in Table 4 is 1, because factor 2 (employment policy) influences factor 1, which is “government policies”. As a result, in Table 4, the value of (3, 1) may likewise be changed from 0 to 1. If the user’s IRM is utilized to validate the transition rule, all the binary values of the factors may be 1. Because there is no method to link the components in this scenario, the transition rule is ignored. As a result, the final reachability matrix (FRM) was used to define the initial reachable matrix (IRM) (see Table 5). The FRM contains both the driving power and the dependence power for the user. The total of the numbers in each row of the matrix represents the driving force, which might affect other variables. The fact that the matrix’s dependent power is summed up for each column implies that numerous elements can interact with one another. The user’s FRM reveals that the transition rule has no effect on the IRM.

4.4. Establishment of Final Reachable Matrix (FRM)

The key concept of the ISM technique is transitivity. If factor i influences factor j and factor j influences factor k, then factor i will influence k. If there is a path linking one element to another, the FRM can show it. If cell (i, j) in the final reachable matrix equals 0, there is no direct or indirect link between factor i and factor j. According to this concept, the FRM may be calculated using the following Boolean rules:

R = (A + I)^r = (A + I)^r−1 ≠ (A + I)^r−2 ≠ ⋯⋯ ≠ (A + I), r ≤ 20

(2)

where

A = initial reachable matrix

I = unit matrix

R = final reachable matrix

4.5. Hierarchical Analysis

To assist the reader in comprehending the hierarchical connection between each influencing factor (Fi), the reachable set R and the antecedent set A are presented. When the corresponding value is 1, the accessible set R indicates that Fi controls elements on line i. The antecedent set A is made up of the items in column i that have a value that is comparable to 1. There are parts in i that can both affect and be affected by Fi. If R is a complete subset of A, the element will be chosen and assigned a specific level. At the level of the first element, this study identified the elements for which I and R are equal. After the rows and columns of the first layer elements were removed, the remaining items were then used to create a new reachable matrix. The writers will then select the elements whose bottom layer has I equal to R. Additionally, the authors can learn about the stages’ components. The components’ hierarchical separation is shown in

Table 6. Hierarchical division of factors.

Factor	Factor Code	Reachability Set (I)	Antecedent Set (A)	Intersection Set (I)	Level
Knowledge and information ownership	12	12-13-15-17-18-19-20-21-22-24	1-2-3-5-6-7-8-9-11-12-13-14-15-16-17-18-19-20-21-22-23-24	12-13-15-17-18-19-20-21-22-24	1
Effective cooperation among project participants	13	12-13-15-17-18-21-22-24	1-2-3-4-5-6-7-8-9-11-12-13-14-15-16-17-18-19-20-21-22-23-24	12-13-15-17-18-21-22-24	1
Functionality	24	5-8-12-13-24	2-3-4-5-6-7-8-9-11-12-13-14-16-17-18-19-20-21-22-23-24	5-8-12-13-24	1
Standardized work Procedures for BIM	5	2-3-5-21-22	1-2-3-4-5-6-7-8-9-10-11-14-16-18-19-20-21-22-23	2-3-5-21-22	2
Cooperative management platform	22	5-22	1-2-3-4-5-6-7-8-9-11-14-16-17-18-19-20-21-22-23	5-22	2
Trust and respect	19	1-4-15-18-19-20	1-2-3-4-6-7-10-14-15-16-18-19-20-23	1-4-15-18-19-20	3
Simplicity	20	6-8-14-15-18-19-20-21	2-3-4-6-7-8-9-1-11-14-15-16-18-19-20-21-23	6-7-8-14-15-18-19-20-21	3
Interoperability and compatibility	21	8-20-21	1-2-3-4-5-6-7-8-11-14-16-17-18-20-21-23	8-20-21	3
Employment policy	2	2-3-23	1-2-3-4-6-7-8-9-10-11-14-15-16-17-18-23	2-3-23	4
BIM training system	3	2-3-23	1-2-3-4-6-7-8-9-10-11-14-15-16-17-18-23	2-3-23	4
BIM effectiveness evaluation criteria	6	6-7-8-14-17	1-4-6-7-8-9-10-11-14-16-17-18-23	6-7-8-14-17	5
New or edited templates of construction contracts	8	6-8	1-4-6-8-9-10-11-14-15-16-17-18-23	6-8	5
Standards to guide specific implementation	23	23	1-2-3-4-7-9-10-11-14-16-17-18-23	23	6
R& D plan	9	7-9-11-14	4-7-9-10-11-14-16-17-18	7-9-11-14	7
Organizational innovation and learning	11	7-9-11-17-18	4-7-9-10-11-14-15-16-17-18	7-9-11-17-18	7
Formal incentive programs for using BIM	7	7-10-17-18	1-4-7-10-14-15-16-17-18	7-10-17-18	8
Financial support	4	4-17	1-4-10-14-15-16-17-18	4-17	9
Top management support	16	16-17	1-10-14-15-16-17-18	16-17	10
Government policies	1	1-14	1-10-14-15-17-18	1-14	11
Early involvement	17	17	10-14-15-17-18	17	12
Willingness to change ways of thinking and working	18	18	10-14-15-18	18	13
Demand	15	15	10-14-15	15	14
Cost viability	14	14	10-14	14	15
Awareness of BIM and sustainability benefits	10	10	10	10	16

.

The interpretive structural model for AEC organizations’ BIM adoption is built to better depict the hierarchical structure from the bottom to the top. Figure 1 displays a layering of the same-level components from the prior investigation.

Based on FRM, the final ISM-based model for BIM factors was obtained. Figure 1 shows the final ISM-based model for BIM factors. It is observed that awareness of BIM and sustainability benefits (Level 16) is the fundamental factor affecting BIM’s adoption in AEC organizations. This BIM factor has the highest driving power, which implies that this was the key BIM factor influencing the entire project. It directly influences the other factors, such as “cost viability” (Level 15), “demand” (Level 14), “willingness to change ways of thinking and working” (Level 13), “early involvement” (Level 12), “government policies” (Level 11), “top management support” (Level 10), “financial support” (Level 9) and “formal incentive programs for using BIM” (Level 8).

The next level factors, in the order of reducing influence, are “R&D plan” and “organizational innovation and learning” (Level 7), which are influenced by “formal incentive programs for using BIM” directly, and at the same time are found to be interdependent. The “standards to guide specific implementation” (Level 6) is the next level BIM factor, which is influenced by the previously discussed factors of BIM; however, at the same time, it directly affects “BIM effectiveness evaluation criteria” and “new or edited templates of construction contracts” (Level 5). These two factors further influence “BIM training system and employment policy” (Level 4). Both levels are found to be interdependent. Furthermore, “trust and respect”, “simplicity and interoperability” and “compatibility” (all on Level 3) form the next level that is influenced by the former two factors; these are also interdependent. The “Cooperative management platform” and “standardized work procedures for BIM” (Level 2) are the factors which are affected by all three factors of the previous level. Other than these two factors being interdependent, the former factor and “interoperability and compatibility” are also found to be dependent on each other. “Knowledge and information ownership”, “effective cooperation among project participants” and “functionality” (Level 1) are found to be at the top of the hierarchy, reflecting the effectiveness of all the BIM factors. These are controlled by all the other BIM factors.

4.6. MICMAC Analysis

This paper employed MICMAC to enhance the interpretive structural model to highlight the strong link between the influencing factors, and further investigate the features of the influencing elements. The driving power of the final reachable matrix was derived by adding the rows of elements, whereas the dependence power was acquired by adding the columns of components. The influencing variables may be classified into four types, based on their dependency and driving force: independent, dependent, linked, and autonomous. Figure 2 depicts the final categorization.

5. Discussion

Little in-depth study has been conducted on the literature analysis and synthesis of the application of BIM in AEC businesses. This study covered research from 2004 to July 2019 to identify BIM adoption and implementation facilitators, and to present a thorough synthesis of the existing BIM literature, innovation management, and information technology domains. Out of the 80 studies chosen, 24 factors were discovered to assist BIM to be utilized more broadly throughout enterprises. IT adaptability, knowledge competency, strategic initiatives, network links, process and performance management strategies, cultural preparation, and learning capacity were among them. The influence of each implementation enabler on IT-enabled innovations in general and on BIM’s implementation in particular is underlined throughout. A brief insight into the top five factors is presented below.

5.1. Top Management Support

The process of guiding a group to effective project completion may be described as project leadership. The knowledge, skills, abilities, experience, and traits that a specific BIM leader requires to accept and implement BIM are referred to as BIM leadership competencies. The lack of a BIM specialist with the appropriate abilities, on the other hand, is a substantial impediment to the deployment of BIM [82]. Identifying and evaluating BIM skills offer several advantages, including increased performance, professional development support, certification, and accreditation [83]. Despite extensive study on leadership, little is known about the importance of leadership abilities and how they benefit the BIM profession. An incorrect allocation of skills and competences can lead to implementation failure [84], and many BIM-related occupations require specialist talents [85]. Leadership competencies and other BIM-related abilities deemed critical for BIM professionals may be included in the curriculum of BIM training facilities, since leadership skills are acquirable [84].

5.2. Financial Support

Financial support may have a substantial influence on the adoption of BIM technology. According to Ref. [86], there is a considerable association between the amount of acceptability of BIM and economic considerations. Benefits and financial help were recognized as significant success factors for the deployment of BIM in Singapore by the authors in Ref. [11]. Cao et al. [86] conducted another investigation that highlighted the importance of economic viability. Likewise, Lee and co-workers [87] investigated the economic feasibility of using structural building information modelling (S-BIM) for high-rise building structures. Saieg et al. [88] studied the economic benefits of implementing BIM in lean construction.

5.3. Government Policies

According to Herrera and Nieto [89], the effects of government policies on demand from industry, consumers, and public services may influence the process and direction of innovation. According to Lemola [90], governments typically play an important role in innovative procedures as information and technology suppliers. While certain restrictions may be useful in stimulating technological innovation, others may be ineffectual or even harmful. National leadership and coordination, which are essentially the responsibility of governments, are the most important factors in determining the success of BIM implementation [51]. For the effective development and deployment of advanced technical systems, a strong government backing is required [91].

5.4. Effective Cooperation among Project Participants

Member participation and communication serve as the foundation for information exchange and resolving issues [92]. Several professional designers must engage with one another in BIM-based collaborative design. To increase team efficiency, it is critical to control the team’s internal interaction process when the team’s external conditions are known [93]. Effective techniques and approaches for team interaction have been found in some studies to increase productivity and efficiency [94].

5.5. BIM Training System

Given that BIM is one of the most cutting-edge methodologies used in architecture and civil engineering recently, it is critical to assist its integration into university courses [95]. The construction sector has requested that universities reach an agreement that focuses on the building professions, which require various training approaches [96]. Engineers and architects are aware that using BIM platforms is required for competent and quality work in today’s worldwide economy [97]. The usage of BIM in the industry enhances quality service delivery and efficient execution of competitive projects.

Using Figure 1, the conclusions of this article are intended to help AEC firms determine the necessary interventions and competency development for overall effective BIM deployment, and to assess organizational preparedness for the implementation process.

Several initiatives have been launched in both public and commercial businesses to promote the use of BIM. These initiatives range from the development of guidelines to the regulations and tenders that demand the usage of BIM. Some of the leading nations that have released manuals on the recommendations for BIM implementation include the United States, the United Kingdom, Finland, Singapore, Norway, and Hong Kong. Typical examples of these manuals are “Getting Started with BIM (NATSPEC, 2014)”, “Building Information Modeling Roadmap (USACE and ERDC, 2006)”, “National Building Information Modeling Standard (NIBS)”, “National Building Information Modeling Guide 01–07 (GSA, 2006–2015)”, “BIM Guide for Germany (Federal Office for Building and Regional Planning, 2013)”, “CIC Building Information Modeling Standards (Construction Industry Council, Hong Kong, 2015)”, and “BIM Guideline Standard (Public Works Department)” [57].

6. Conclusions

Saudi Arabia’s economic thrust is shifting as a result of the recent drop in oil prices. Therefore, the construction industry is driven by competitive pressure to adapt to the demands of the current market and governmental regulations. Saudi Arabia’s construction sector is currently making these adjustments. The building industry in Saudi Arabia still faces significant obstacles and has significant market potential in the future. The government’s increased commitment to the private sector and its unwavering support for the privatization principle provides a ray of hope for the construction sector. It may be possible for the majority of construction companies to enter into a variety of rehabilitation, operation, and management contracts as well as smaller, contractor-conceived projects. To increase both quality and profitability, the construction industry is presently working on eliminating waste and inefficiency. However, because of its capacity to demonstrate expertise in this capacity, industrialized nations have recommended the adoption of BIM.

There are few examples of BIM applications in the Saudi AEC sector or education. This study developed a model for the deployment of BIM in KSA to prepare for its usage, which increases project quality and profitability, performance, and the possibility of creative solutions to AEC sector difficulties, as shown in Figure 1. By establishing a timetable for making BIM a requirement for all AEC projects, the KSA government may play a vital role in offering feasible and realistic strategic plans for execution. Furthermore, the government should support enterprises in reducing barriers to the implementation of BIM. For example, companies may be eligible for government aid to offset the early expenses of implementing BIM. To grow future generations who are entirely BIM-oriented (in the long run), it is recommended to include BIM in AEC undergraduate and graduate programs. Organizational decision-makers must assist staff in implementing BIM by, for example, providing short-term training and developing strategic goals. Everyone needs to develop their BIM skills. If the proposed technique is applied, the AEC industry’s performance and effectiveness might be enhanced, project-related concerns could be handled, creativity and innovation fostered, and a bright future for the sector ensured.