Examining Green Building Practices: The Influence on Building Information Modeling Function Diffusion

Abstract

The construction sector plays a pivotal role in sustainability efforts, driving the need for innovative solutions like Building Information Modeling (BIM) to optimize green building design and performance. This study examines the diffusion of BIM functionalities that support sustainability, particularly in energy efficiency, water management, material selection, indoor environmental quality, and green building certification. Using the innovation diffusion theory, the research employs three mathematical models—internal, external, and mixed—to analyze the adoption patterns of BIM for green building applications. Empirical findings reveal that external factors, such as government regulations, financial incentives, and industry trends, significantly influence the diffusion of BIM functions related to environmental performance. The mixed diffusion model demonstrates the highest explanatory power, indicating that both external and internal drivers play a role, particularly in material selection and lifecycle assessment. This study highlights the growing integration of BIM in sustainable construction, reinforcing the need for regulatory support to accelerate adoption. These findings offer valuable insights for researchers, policymakers, and industry professionals, demonstrating how BIM can drive greener practices in the built environment. Policymakers should focus on developing policies and offering incentives such as feed-in tariffs, investment tax credits, and integrating Green BIM requirements into building codes to encourage sustainable construction practices. Also, curricula should be updated to include real-world projects and experiential learning to improve the adoption and efficiency of Green BIM practices. Future research should explore enhanced digital frameworks to further improve BIM’s impact on sustainability and lifecycle optimization.

1. Introduction

The increasing demand for sustainable development has pushed the construction sector towards inventive approaches that relieve natural effects while progressing proficiency. The architecture, engineering, and construction (AEC) industry essentially contributes to worldwide energy utilization and carbon emissions. According to the United Nations Environment Program [1], in 2021, the AEC segment accounted for around 37% of worldwide energy-related CO₂ emissions, with energy utilization coming to 132 exajoules, which is more than a third of the worldwide demand [2], and the World Green Building Council [3] emphasized that buildings are responsible for 39% of energy-related carbon outflows around the world, with 28% emerging from operational emissions, namely energy utilized for heating, cooling, and fueling buildings, and the remaining 11% from materials and development forms. For this reason, the shift towards green buildings has risen as a key objective for stakeholders in the AEC industry [4]. Among different innovative tools, Building Information Modeling (BIM) has developed as a key technology that enhances construction efficiency processes through the optimization of energy usage, material selection, and lifecycle assessments [5].

In any case, the application of BIM remains shy, especially in green building activities, due to challenges such as high adoption costs, a lack of skills, and issues related to interoperability [6]. Previous studies have explored the role of BIM in sustainable development, emphasizing its capabilities for energy simulations, the automation of green certification processes, and waste reduction procedures [7,8]. Researchers have acknowledged that BIM is a critical enabler for green building certification by integrating environmental performance analysis in the early stages of the design [9].

Later improvements in BIM’s functionalities advance and open its potential for sustainability, highlighting functions that encourage multi-objective optimization for accomplishing net-zero carbon targets [5]. Also, BIM’s association with material lifecycle assessments and digital twin integration provides a data-driven system for informed sustainable decision-making all through the extended lifecycle [10]. Despite these benefits, BIM diffusion for functions related to sustainability is hindered by financial and technological barriers [11].

Investigation shows that the complexities encompassing BIM adoption manifest in developing regions, where the lack of standardized policies, low awareness, and insufficient skilled labor impede broader utilization [12]. In addition, interoperability challenges between different BIM software and green certification systems remain a significant impediment that discourages its integration into sustainable construction practices [13,14].

Other studies examined small-scale green building projects and demonstrated that BIM applications could effectively promote sustainability [15]. The research addressed specific obstacles and opportunities encountered in these projects, highlighting that while BIM has been extensively examined in large-scale developments, its application in smaller projects also offers significant sustainability benefits. Similarly, Ref. [16] emphasized that while BIM offers valuable tools for certain assessments, it is essential to recognize its limitations in providing a comprehensive overview. Establishing a process is inherently dependent on prior knowledge, which is often lacking without a comprehensive understanding of the subject matter in KSA. In this context, Ref. [15] investigated BIM-based projects with a view to enhancing the widespread adoption of BIM for construction projects in Nigeria by the government and construction firms. The findings indicated that BIM has the potential to significantly improve design coordination and construction execution, suggesting that its integration can lead to more sustainable building practices. Despite the contribution of previous researchers in the field of BIM and green buildings, the existing literature often lacks empirical evidence on specific barriers and enablers influencing Green BIM diffusion, particularly in the Gulf region, where construction practices and policies differ from Western contexts. In addition, they have not sufficiently explored the role of external, internal, and mixed factors in the adoption of Green BIM, limiting the understanding of how different forces drive or hinder its implementation. This study is driven by the unique challenges and opportunities facing the Gulf region. These complexities have not been adequately addressed in the existing literature. These include the region’s rapid urban development, its reliance on conventional building techniques, and the emerging demand for sustainable practices amid regulatory and technological gaps. Despite the growing recognition of the benefits of BIM for sustainability purposes, there is a lack of comprehensive research into the patterns of Green BIM diffusion and the specific factors influencing the adoption of sustainability-related functions. These factors may include regulatory barriers, technological fragmentation, and limited stakeholder awareness or capacity in the construction sector.

Furthermore, traditional diffusion models often fail to capture the complexity of BIM adoption in the context of sustainable construction. This study employs innovative diffusion models, specifically internal, external, and mixed models, to provide a more nuanced understanding of how external regulations, market demands, and organizational readiness interact in shaping the adoption of Green BIM functions. The absence of empirical data on the factors influencing Green BIM diffusion in this region not only leaves a significant knowledge gap but also inhibits the development of tailored strategies to promote sustainability in construction practices.

Current research concentrates on technological problems [17] and sustainable practices in construction, emphasizing energy efficiency [18], waste reduction [15] and lifecycle assessments [19]. Also, scholars highlighted the associated benefits like cost savings, improved resource management, and reduced environmental impact through digital modeling and simulations [18,20,21]. Moreover, earlier studies concentrated on modeling capabilities and recent advancements that emphasize enhanced data integration and sustainability outcome analysis. Despite the importance of the above, there is still a lack of knowledge about the patterns of diffusion and whether external factors, including regulations, policies, and media, or internal factors, such as imitative behavior and bandwagon pressure, affect the diffusion of Green BIM functionalities in the Gulf area. The Gulf region has been rarely researched for Green BIM diffusion patterns, limiting insights into adoption trends and challenges.

The integration of BIM in complex construction projects, particularly high-risk environments like tunnel construction, has been explored in previous studies. Ref. [22] developed a BIM-based risk management system that enhances safety, efficiency, and decision-making in mountain tunnel construction. Their findings demonstrate how predictive modeling and real-time analytics can improve hazard assessments. These insights can be applied to Green BIM adoption in the Gulf region, where extreme climate conditions and rapid urbanization require advanced digital solutions for sustainability.

Similarly, Ref. [23] used finite element modeling (FEM) and numerical simulation models to predict tunnel stability, assess geological risks, and optimize construction sequencing in BIM-based tunnel engineering management. Song’s findings suggest that automated analysis, lifecycle assessment tools, and sustainability-driven workflows can support Green BIM adoption, enhancing decision-making in eco-friendly building practices.

Despite these advancements, research on Green BIM functionalities in the Gulf remains limited. Ref. [22] provides valuable insights into BIM adoption barriers and facilitators, particularly in risk-based digital modeling, predictive analytics, and sustainability assessments. This study addresses this gap by extending BIM risk management approaches to Green BIM adoption, offering a region-specific analysis of how digital tools can enhance sustainable construction in the Gulf region.

In addition, observational data are needed on how innovative diffusion models can illustrate the changing rates of decision-making to adopt specific Green BIM functions, especially in the Gulf area [24]. Addressing these gaps is imperative to develop strategies that encourage the widespread use of BIM for sustainability-enhancing applications.

This study is especially important for policymakers, construction companies, and analysts interested in the progress of the use of BIM in green building frameworks. By examining the variables that affect specific Green BIM function utilization, this research seeks to provide insights that will help industry experts overcome the adoption challenges. Moreover, this study contributes to the academic debate by analyzing the patterns of technological advancement diffusion, such as BIM, within the construction sector, giving visibility to a new viewpoint on how technological advances can drive economic change in the built environment.

The main objective of this research is to study the patterns affecting the diffusion of BIM in the Gulf region. Exploring this geographical area is vital because of its rapid urbanization, huge construction projects, and government-driven sustainability goals such as the (KSA) Vision 2030. Identifying the adoption patterns of BIM functions, especially tailored to green building applications, can improve efficiency, decrease the environmental impact (EI), and support policy development in the region.

Through a thorough research investigation of the green adoption rate and the barriers and enablers of adoption, this study seeks to fill the research gap encompassing BIM’s role in sustainability, ultimately supporting its ability to provide significant benefits to the AEC sector.

2. Literature Review

2.1. Building Information Modeling (BIM)

BIM is a digital process for creating, managing, and sharing construction project data throughout its lifecycle. Successful BIM adoption depends on the expertise of its users, particularly in integrating sustainability strategies such as lifecycle assessments (LCAs) and energy-efficient designs. Without trained professionals as implementation guides, the full potential of green construction remains unrealized.

BIM has arisen as a focal technological tool in the scope of green building design and construction, assisting in the incorporation of sustainability principles throughout the building lifecycle. BIM has several functions that can be used in sustainability and green building initiatives. The latest functions have rapidly progressed in the last decade all over the world [25].

Another critical aspect of BIM’s sustainability potential is its ability to facilitate eco-conscious procurement and material selection, ensuring that sustainable resources are incorporated while monitoring supply chain integrity [9]. As the demand for environmentally responsible buildings continues to rise, firms leveraging BIM gain a competitive advantage by delivering high-performance, sustainable solutions. This not only enhances their reputation but also increases their market share by aligning with industry-wide sustainability expectations [11]. Furthermore, BIM fosters improved collaboration by establishing a shared digital platform that streamlines coordination among multidisciplinary teams, a fundamental requirement for integrating sustainability principles throughout the project lifecycle [26,27].

Recent studies emphasize the pivotal role of Building Information Modeling (BIM) in evaluating environmental impacts and resource consumption through advanced data analytics [18].

As the literature increased, scholars started to discover the integration of BIM with building rating tools, such as LEED and BREEAM, which provided a structured approach to estimating sustainability metrics [4]. This scored a considerable step in lining up BIM functionalities with green building goals, as it enabled a systematic assessment of energy efficiency and resource utilization during the design phase [7]. With time, the use of BIM progressed to become a useful tool for performing complex energy modeling, lifecycle assessments, and real-time data analytics. For example, the employment of BIM with energy simulation tools, such as Green Building Studio and Ecotect, has permitted performing complete energy performance calculations and optimization strategies [28]. Furthermore, recent evidence suggests that BIM adoption significantly contributes to performance analysis, optimization strategies, and the development of structured frameworks for green building designs [4].

Adding to the above, the review of the literature revealed the role of BIM in providing informed material selection by offering detailed information on the EI, durability, and cost-effectiveness of materials, backing sustainable results [10]. Apart from the above, BIM has been recently deployed to design efficient water management systems and simulate water flow. This optimizes water usage and backs conservation strategies [7]. In the recent literature, many scholars emphasized the integration of BIM with digital twins which enables the real-time monitoring and management of building performance throughout its lifecycle. This allows for the tracking and optimization of resource allocation and utilization, resulting in sustainable and efficient building operations. Summarizing the literature review, the authors identified 11 key Green BIM functionalities that will be examined in this study, as presented in

Table 1. Green functionalities. Authors.

Green BIM Functionalities
1	Energy Efficiency and Performance	[7,18,28,29,30,31]
2	Water Efficiency and Management	[32,33,34,35,36,37]
3	Material Selection and LCA	[5,10,16,19,26,27,32,38]
4	Sustainable Site Design	[39,40,41,42,43]
5	Indoor Environmental Quality	[7,11,24,44,45]
6	Waste Reduction and Construction Optimization	[7,8,13,14,15,46,47]
7	Green Building Certification Assistance	[4,11,33,44,48,49,50]
8	Carbon Footprint and Emissions Analysis	[5,22,49,51,52]
9	Renewable Energy Integration	[53,54,55,56]
10	Data Management and Digital Twins	[10,20,21,23,57]
11	Facility Management Tools for Sustainability	[9,13,14,16,58]

.

2.2. Barriers to BIM Adoption

Despite its numerous benefits, the widespread implementation of BIM in green building projects is hindered by several constraints. The initial costs associated with acquiring software, training personnel, and integrating BIM into existing workflows present significant financial challenges, particularly for small and medium-sized enterprises [12,59]. Moreover, the scarcity of skilled BIM professionals limits its effective utilization, as the demand for trained experts surpasses the current supply [6,48]. Another major obstacle is interoperability, as inconsistencies in data exchange protocols among various BIM tools and platforms create difficulties in collaboration, particularly in multi-stakeholder projects [13,14]. Additionally, resistance to change remains a persistent challenge, as many firms remain reluctant to transition from traditional construction methodologies, perceiving BIM as a complex and costly shift [60,61]. The financial burden of acquiring BIM-compatible hardware and software further exacerbates adoption hesitancy, particularly for organizations operating with limited technological infrastructure [62]. Furthermore, a lack of commitment from clients and upper management often undermines BIM implementation, as project decision-makers prioritize short-term financial returns over the long-term sustainability benefits that BIM offers [63]. BIM adoption challenges are universal but vary based on regional construction practices, regulatory frameworks, and technological maturity. Developed markets like the UK and US benefit from strong digital infrastructure and regulations, whereas emerging markets face hurdles such as high costs and limited expertise. Effective BIM implementation also depends on a strong understanding of architectural principles, including materials, design, and management [14]. Without this knowledge, BIM tools may be underutilized, reducing their potential benefits. Interdisciplinary collaboration among architects, engineers, and project managers is essential for maximizing BIM’s impact across different contexts.

Table 2. BIM diffusion barriers.

Barrier	References
High Initial Costs	[6,39,62]
Lack of Skilled Workforce	[64,65]
Resistance to Change	[6,48,65]
Technological Complexity	[39,66,67]
Lack of Awareness and Knowledge	[62,68]
Interoperability Issues	[14,63]
Uncertain Return on Investment	[63,69]
Data Privacy and Security Concerns	[39,67]
Cultural and Organizational Barriers	[63,64,70]

summarizes all the barriers.

2.3. Innovative Diffusion Models

To better understand these barriers and drivers of Green BIM function adoption, innovation diffusion models (IDMs) can be used.

Innovation diffusion theory (IDT) presents a structured framework for understanding how new technologies, including BIM, are adopted within industries [58,71]. Prior research suggests that BIM adoption follows distinct diffusion patterns, with early adopters demonstrating its benefits before widespread industry acceptance occurs [72,73].

Innovative diffusion models aid in understanding the factors affecting Green BIM adoption like the patterns of adoption, peer influence, and market conditions. Scholars successfully used these models to assess the enablers of BIM adoption in green building projects, finding that organizational factors and technological readiness significantly impact its diffusion [72,74]. The authors used models to examine how various levels of awareness and knowledge across construction firms affect the implementation of sustainable practices. These models present a systematic approach to expecting and examining the factors that encourage or deter BIM’s use of sustainability features.

Mathematically, the internal diffusion model is represented as

$${\displaystyle \frac{\mathrm{d}\mathrm{N}\left(\mathrm{t}\right)}{\mathrm{d}\mathrm{t}}}=\mathrm{a}\mathrm{N}(\mathrm{t})[\mathrm{m}-\mathrm{N}(\mathrm{t})]$$

(1)

where

• N(t) is the cumulative number of adopters at time t;
• m represents the total number of potential adopters in the social system;
• a is the probability that each adopter will independently influence a non-user;
• dN(t)/dt represents the rate of diffusion at time t.

This equation suggests that as the number of adopters increases, the influence of social networks accelerates the diffusion process. In the case of BIM, this internal mechanism is evident in the construction industry’s gradual shift towards digital transformation, where early adopters promote technology diffusion through industry conferences, professional networks, and collaborative projects.

In contrast, the external diffusion model argues that technology adoption is influenced primarily by external sources of information, rather than social interactions within an industry. According to this model, firms adopt new technologies based on external forces such as government regulations, media influence, and client demands [75]. Unlike the internal model, this approach assumes that direct communication between early adopters and potential adopters is minimal.

The external diffusion model is expressed as

$${\displaystyle \frac{\mathrm{d}\mathrm{N}\left(\mathrm{t}\right)}{\mathrm{d}\mathrm{t}}}=\mathrm{b}[\mathrm{m}-\mathrm{N}(\mathrm{t})]$$

(2)

where

• b is the coefficient of an external influence per period (b ≥ 0).

This model indicates that as the number of adopters increases, the implication on social frameworks enlivens the spread. In the case of BIM, this internal component is clear as the advancement industry’s nonstop move towards progress alters, where early adopters progress advancements through industry conferences, capable frameworks, and collaborative wanders.

On the other hand, the exterior model contends that development allotment is affected fundamentally by exterior sources of information, rather than social interactions interior an industry. Concurrent to this show, firms grasp unused propels based on exterior powers such as government headings, media effects, and client demands [75]. Not at all like the inside show, this approach expects that coordinating communication between early adopters and potential adopters is negligible.

This show is especially pertinent for BIM selection in green buildings, where government commands approach motivating forces, and administrative conditions play a key part in quickening selection rates [68]. In this case, in districts where BIM compliance is legitimately required for open foundation ventures, selection rates tend to be essentially higher [48]. In addition, supportability certification frameworks such as LEED and BREEAM frequently empower BIM utilization to upgrade vitality proficiency and carbon following, fortifying the outside dissemination component.

Mixed dispersal appears for the planning of both inward social effects and exterior control weights, recognizing that the advancement choice is influenced by both peer pantomime and exterior drivers [75]. This is real and particularly profitable when analyzing BIM determination components, as firms routinely grasp advancements due to both competitive weights and regulatory prerequisites.

The mixed diffusion model integrates both internal social influence and external institutional pressures, recognizing that technology adoption is influenced by both peer imitation and external drivers. This model is particularly useful in analyzing BIM adoption dynamics, as firms often adopt the technology due to both competitive pressures and regulatory requirements.

The mixed influence model is defined as

$${\displaystyle \frac{dN\left(t\right)}{dt}}=[\mathrm{b}+\mathrm{a}\mathrm{N}(\mathrm{t})][\mathrm{m}-\mathrm{N}(\mathrm{t})]$$

(3)

This equation suggests that BIM adoption is accelerated by a combination of industry-wide best practices, regulatory frameworks, and social learning dynamics. For instance, firms operating in competitive markets may feel compelled to adopt BIM both to comply with government regulations and to maintain a competitive edge within the industry [76].

The integration of BIM in complex construction projects, particularly high-risk environments like tunnel construction, has been explored in previous studies. Liu Naifei et al. (2022) [22] developed a BIM-based risk management system that enhances safety, efficiency, and decision-making in mountain tunnel construction. Their findings demonstrate how predictive modeling and real-time analytics can improve hazard assessments. These insights can be applied to Green BIM adoption in the Gulf region, where extreme climate conditions and rapid urbanization require advanced digital solutions for sustainability.

Similarly, Song Zhanping et al. (2021) [22] used finite element modeling (FEM) and numerical simulation models to predict tunnel stability, assess geological risks, and optimize construction sequencing in BIM-based tunnel engineering management. Song’s findings suggest that automated analysis, lifecycle assessment tools, and sustainability-driven workflows can support Green BIM adoption, enhancing decision-making in eco-friendly building practices.

Despite these advancements, research on Green BIM functionalities in the Gulf region remains limited. Liu and Song’s methodologies provide valuable insights into BIM adoption barriers and facilitators, particularly in risk-based digital modeling, predictive analytics, and sustainability assessments. This study addresses this gap by extending BIM risk management approaches to Green BIM adoption, offering a region-specific analysis of how digital tools can enhance sustainable construction in the Gulf region.

Although extensive research has been conducted on BIM adoption in the construction industry, a critical gap remains in understanding how innovation diffusion models can enhance BIM integration in green building projects. While previous studies have identified general adoption drivers and barriers, they often lack a systematic approach to aligning BIM functionalities with sustainability objectives such as energy efficiency, water management, material selection, indoor environmental quality, and green building certifications. Current research predominantly examines the technical capabilities of BIM without sufficiently addressing the social and organizational factors influencing its diffusion within sustainable construction.

One key limitation in existing studies is the insufficient focus on practical frameworks that facilitate the seamless integration of BIM into established green certification systems such as LEED, BREEAM, and Green Star. Additionally, the absence of standardized methodologies for employing BIM in lifecycle sustainability assessments, particularly regarding energy modeling, resource conservation strategies, and the optimization of environmentally friendly materials, hinders its full potential. While BIM is recognized for enhancing collaboration, there is limited research on its effectiveness in fostering interdisciplinary teamwork aimed at achieving sustainability goals.

To bridge this gap, future research should develop comprehensive methodologies that integrate BIM with sustainability performance indicators and ensure that construction projects effectively align with green certification requirements. In addition, exploring the role of innovation diffusion models in shaping BIM adoption patterns for sustainable construction can offer deeper insights into overcoming existing barriers. Investigating digital workflows that optimize BIM’s role in lifecycle assessments, carbon footprint reduction, and sustainable material sourcing will further enhance its contribution to green building practices. Addressing these research gaps will not only advance BIM’s role in promoting sustainability but also support its widespread adoption as a fundamental tool for achieving global environmental objectives through technology-driven innovation.

Table 3. Key factors.

Model Type	Key Factors	Impact on Diffusion
Internal Factors	-Bandwagon pressure	Internal factors focus on the internal environment and resources necessary for successful adoption. Management commitment, leadership, organizational culture, and the ability to manage change are key factors as well.
	-Management commitment and leadership
	-Availability of skilled professionals
	-Word of mouth
	-Organizational culture (openness to innovation)
	-Organizational readiness for change
External Factors	-Regulatory frameworks (government mandates for BIM adoption)	External factors include legal requirements, governmental support, and market demand for sustainable building practices that drive adoption. These factors create external pressures for organizations to adopt new innovations
	-Economic incentives (tax breaks and subsidies for green buildings)
	-Societal demand for sustainable construction
	-Industry standards and norms
	-Environmental and sustainability policies
Mixed Factors	-Interaction between internal readiness and external regulatory pressures	Mixed factors consider the interplay between internal and external influences.
	-Collaboration between industry players
	-Knowledge transfer from industry leaders and pioneers

summarizes the main factors of the three diffusion models.

3. Methodology

Data-Collection Instrument and Process

The in-depth literature review discussed in the “Background” section revealed 11 main BIM functionalities for green building practices that were shortlisted according to the expert opinions of the researchers whose works were reviewed. A case study was integrated into this research. The Dubai Frame project is an 8000 m² project where BIM (Revit 19.2) was extensively used for material tracking. The project focused on minimizing construction waste and tracking materials from procurement to installation. Similarly, building energy modeling tools were integrated with BIM (Revit 2019.2) to conduct the energy analysis and modeling for the project aiming for an energy efficient project. The authors conducted report analysis and interviews with a project manager and a BIM specialist. The interview questions focused on their experiences with BIM adoption, the main enablers, and the barriers they encountered in integrating material tracking and energy simulation tools.

These formed the basis of the comprehensive questionnaire the authors used to collect data and seek answers to the research questions. A questionnaire with 18 questions was developed based on the literature review results, as this quantitative data collection method generates data that can be utilized for rigorous quantitative analysis and for high-quality research outcomes [77]. Questions included the size of the company, position, years of experience, and the type of system used.

Diffusion models predict adoption patterns and rates in the market, rather than specific factors that drive individual firms’ decisions. These models assume that once a firm is exposed to an innovation (via marketing or peer influence), adoption is based on general parameters like imitation and innovation. Economic variables such as ROI, cost–benefit analysis, and project size are more relevant to the firm’s decision-making process, which lies outside the scope of these models. The mixed model emphasizes social influence (internal) and external marketing efforts (external) but does not account for a company’s economic value or project scale when deciding to invest in BIM.

Before sending the questionnaire, and to avoid information distortion, the instrument was revised by two groups of specialists, including three academic faculty members and two industry professionals for the content validity process and to improve the solidity and practicability of the questionnaire.

There are different BIM functions being used for green buildings, and the companies that have been implementing BIM in the Gulf area have different technical skills, experience, and understanding of the functions; therefore, it was important to collect data from many organizations. To guarantee that the answers are collected from the correct sample population, the survey was sent only to firms listed either on the Institute of Architecture and Engineering register of the Gulf region’s countries or in the business directory under the Chamber of Commerce of Civil and Construction work, which resulted in a total of 1833 firms. As suggested in [78], three experts responded first to the questionnaire as part of a pilot study, and the questionnaire was reviewed according to their opinions and suggestions. Over 721 surveys were filled and submitted, indicating that the results portray the population accurately, with a confidence interval of 5% and a confidence level of 95%. Participants consisted of contractors, designers, construction engineers, construction managers, general managers, and owners working in the Gulf region, regardless of whether they were using BIM for specific green practices or not.

The questionnaire was headed by a brief description of the goals of the survey and the research paper, with an additional attestation from the authors to the respondents that total anonymity of their identity will be kept and that their response will be confidential and used solely for the paper’s objectives. Then, the responders were requested to answer questions presented in three sections. The first part was an obligatory part that focused on collecting data about the characteristics of the respondents and the company they worked with, including the company size, the respondent’s role, years of experience in the industry, expertise, mode of work, and educational level. The data collected are crucial to warrant that survey takers can procure data realistically [77] and to establish the credibility of the results [79,80]. The last question of this section is about whether they are using BIM functionalities in the projects or not. This final question was used as a directory for the subsequent part. The second section tackles only respondents who use BIM for green building practices. It starts with introducing only the 11 BIM functions related to sustainable and green building practices and thereafter asks participants if they are adopting any of them and the first year they have started adopting this function in their organization. The six-point Likert scale ranging from 1 (low) to 6 (High) was used, as per the recommendation by [81], to assess how frequently the BIM functions are used, the difficulty of adopting the functions, and the significance of its adoption. On the other hand, a third section of the questionnaire is developed especially for participants who answered that they are using BIM but not using any of the above functions, for example, if they use BIM for visualization, clash detection, cost estimation, and scheduling. This section is important to understand the barriers behind not using BIM features such as energy analysis, water conservation modeling, and lifecycle assessments for green building practices; specifically, for those people, the software and the skills are already there as they are using the BIM for other functions. The data collection process started in June 2024 and ended in January 2025.

To test whether the results are reliable or not, IBM SPSS Statistics version 30.00 was used to conduct a Cronbach alpha test. A reliability coefficient value of 0.802 was found, which is above the 0.7 threshold for reliable data, according to [82], which means that the results are reliable.

Data Analysis Using Diffusion Models

The time-series data retrieved from Section 2 of the questionnaire were examined using the three influence models presented above (internal, external, and mixed) to identify the decision-making patterns that affect the utilization of BIM features related to sustainable and green building practices in the specific context of the Gulf region. This step involves the estimation of the three parameters (a, b, and m) of the 10 BIM functionalities related to green building practices. To achieve this, the research employs the Levenberg–Marquardt algorithm within the Nonlinear Least Squares (NLS) framework for parameter estimation using SPSS. This method has proved its ability to correctly predict the diffusion of technological innovations in the built environment and presents reliable and more conservative results [79]. The three resulting influence models were then compared based on their goodness of fit to decide on the most powerful model in understanding why and how professionals adopt specific BIM functionalities that support sustainable and green building practices. To fulfill this objective, this study used the coefficient of determination, R2, and AIC. These methods basically measure and compare the amount of error in each model, which is defined as the sum of squares of the differences between the actual and predicted values for each observation. Complete descriptions of methods used to compare the models’ goodness of fit are provided in the Supplementary Materials. Figure 1 outlines the research methodology.

3.1. Case Study Analysis

The interviews and project report analysis of the case study highlighted critical insights concerning the encounters and opportunities in Green BIM adoption. For the Dubai Frame project, the use of BIM to monitor materials throughout the construction lifecycle allowed PMs to determine the excess materials ordered. According to the report, BIM enabled the accurate purchase of material quantities and reduced material wastage by 15% (Azhar et al., 2015) [39], resulting in lower carbon footprints. Notwithstanding the benefits of BIM, several challenges, specifically interoperability problems, were encountered during the integration of BIM (Revit) with energy simulation tools. Interviewees reported occasional issues with data synchronization and focused on how difficult it is to sustain accurate material specifications and energy performance data across different software platforms, which led to additional manual interventions to ensure compatibility. Data exchange between BIM and the IES-VE software was complex, leading to delays in energy performance analysis, specifically during the final phases of the project. Sometimes, energy simulation results were incompatible with the actual BIM model statistics.

Another insight from the interviews is that the company purchased BIM in 2010, but they were using it mainly for clash detection and scheduling rather than sustainability analysis. The year 2017 was the first year in which BIM was used for sustainability purposes, as most staff in the company were not aware of these capabilities earlier. The PM initiated five targeted training sessions per year with assessments, which led to a 30% increase in BIM-based energy efficiency assessments within a year. The PM established a system where whenever a new problem arises and is resolved, a meeting is held with the team to explain the issue and its solution, ensuring everyone knows how to handle it in the future. He indicated that the lack of skills and training is a barrier to adopting Green BIM functionalities.

When examining the effect of regulations on the adoption of BIM for sustainability practices, the PM highlighted the importance of recent green building regulations in Dubai (Al Sa’fat) and how they were both a push and an incentive to use BIM for energy and green certification. From their perspective, these policies provide a clear roadmap and act as a framework to integrate sustainability features. Similarly, the economic incentives for sustainable construction were key factors that influenced BIM adoption. The government provided tax exemptions and financial benefits to encourage investment in renewable energy technologies and sustainable practices in construction. The interviews imply that these incentives provided an added push for the integration.

3.2. Participants’ and Companies’ Characteristics

A total of 721 survey responses were collected from architecture, engineering, and construction (AEC) companies in the Gulf region, of which 709 were complete and were used in the analysis. Among the respondents, 374 were BIM users and 335 were non-BIM users. For the 374 BIM users’ respondents, the questionnaire assessed whether they are employing BIM for green and sustainable related practices (109 respondents) or structural design and other practices (265 respondents). Overall, the results show that 48% of the respondents are non-BIM users, and 52% of the respondents are BIM users of which 71% are using BIM functions for non-green/sustainability applications and 29% adopt specific BIM functionalities that support sustainable and green building practices. The distribution of participants fits the objective of the study as BIM users for non-green building/sustainability applications were asked to assess the significance of the barriers hindering the adoption of specific sustainability practices, while BIM users for green building applications were asked to determine the used functionalities and the year of adoption of each Green BIM function.

The answers show that construction professionals from different targeted divisions contributed to the survey. Among BIM users for green building practices, 52% have more than 10 years of experience and are using Green BIM functions for big projects; for BIM users for functions other than those related to green buildings, the results show that 72% have more than 5 years of experience and are also mainly using BIM for medium-sized and large projects.

Table 4. Participants and company characteristics.

		Respondents Percentage
Features	Subcategories	BIM Users for Green Building Practices	BIM Users for Other (Non-Green) Functions
Technology adoption status		29%	71%
Average work experience Experience	Less than 3 years	2%	5%
	3–5 years	7%	23%
	6–10 years	39%	37%
	More than 10 years	52%	35%
Role	Architect	25%	23%
	MEP Engineers	22%	16%
	Civil and Structural Engineers	16%	21%
	Sustainability Consultants	4%	1%
	Contractors and Construction Managers	20%	21%
	Project Managers	12%	15%
	Other	1%	3%
Project Size	Small	6%	12%
	Medium	29%	36%
	Big	65%	52%

displays the major characteristics of the respondents and their companies, while Figure 2 illustrates that respondents represented 6 different countries across the Gulf region, ensuring a geographically diverse sample.

3.3. Non-Green BIM Users’ Perception of Adoption Barriers

As mentioned earlier, 71% of the participants stated that they use BIM for standard applications such as visualization, clash detection, structural design, cost estimation, and scheduling but do not leverage its sustainability-related functionalities. The authors investigate the reasons why BIM users do not utilize BIM for green or sustainability applications, despite already possessing the necessary hardware, software, and skills.

BIM users for non-green functions rated the impact of various possible reasons for not adopting BIM for sustainability practices. Figure 3 illustrates the percentage of participants who rated each barrier as “Significant” or “Very Significant” on a 6-point Likert scale. The findings indicate the key challenges preventing BIM users from adopting sustainability-related functionalities, despite having the necessary software, hardware, and skills. The results reveal that although many adopters who are skilled in BIM and work in companies that have already made considerable financial investments in BIM, they continue to overlook its capability for green building applications. According to the graph, the lack of awareness and knowledge about how BIM can support green building initiatives tops the list, with 77% of the participants perceiving it as a significant barrier. This implies that although practitioners are well versed in utilizing BIM functions in their role, they are using it for conventional tasks such as visualization and clash detection but are unaware of the innovative capabilities BIM offers for energy efficiency, water management, material selection, and lifecycle analysis, among others. Without a solid understanding of these benefits, BIM remains underutilized in sustainable building practices [11].

Following these barriers, the absence of regulatory or client demand for green building practices is found. This shows that the utilization of BIM for green building practices is often not prioritized unless specifically required by a client or regulatory framework. This means that if the client does not ask for sustainability features, it makes it less urgent for the users to deploy these BIM functionalities. The third most significant barrier is the complexity and integration of challenges, which were perceived as a significant barrier by 54% of the respondents; this might be explained by the results of [83], where the tools for energy modeling, renewable energy integration, and carbon footprint analysis frequently necessitate particular software programs, advanced data inputs, and cross-disciplinary collaboration, which many gulf AEC companies might not be prepared to handle [83]. In this sense, workflow integration and interoperability might arise because, for example, combining energy simulation tools with BIM platforms like Revit or ArchiCAD forces harmonious data exchange among numerous software packages. Interoperability problems can restrain organizations from embracing BIM for green practices, as they would have to provide supplementary tools or workarounds to ensure compatibility which might also be costly [26]. Therefore, AEC companies in the Gulf area may not be convinced to invest more in BIM (30% of the respondents), especially since the return on investment for water saving and carbon footprint analysis is not apparent in the short term, especially when the project’s scope does not entail these features [7].

3.4. Perception of BIM Users for Green Building Practices

Table 5. Percent adoption of Green BIM functions.

Nb	Green BIM Functions	N	% of BIM Users
F1	Green Building Certification Assistance	77	71%
F2	Waste Reduction and Construction Optimization	73	67%
F3	Energy Efficiency and Performance	66	61%
F4	Facility Management Tools for Sustainability	59	54%
F5	Material Selection and Lifecycle Analysis (LCA)	45	41%
F6	Water Efficiency and Management	31	28%
F7	Indoor Environmental Quality	32	29%
F8	Sustainable Site Design	25	23%
F9	Carbon Footprint and Emissions Analysis	18	17%
F10	Renewable Energy Integration	7	6%
F11	Data Management and Digital Twins	5	5%

presents the adoption rates of different BIM functionalities for green building and sustainability practices. According to the results, the most frequently used Green BIM functionality in the Gulf region is energy efficiency and performance, which was used by 71% of Green BIM users. This tool is widely deployed in the Gulf region to examine and improve building energy performance for energy-saving purposes. The second most utilized Green BIM function in the Gulf area is waste reduction and construction optimization, which was employed by 67% of the practitioners to minimize material waste and plan/execute projects with reduced waste generation. Another commonly used feature was green building certification assistance, which was deployed by 61% of the respondents to automate and streamline the certification process for sustainable building standards. On the other hand, other BIM functions such as renewable energy integration, which includes the simulation of photovoltaic (PV) panels and geothermal modeling, have been rarely embraced in the Gulf area, possibly due to project-specific requirements and the need for specialized analysis tools to achieve accurate simulations. In addition, BIM employment for data management and digital twins was used by less than 5% of the participants.

3.5. Diffusion Models and Green BIM Functionality Diffusion

Participants were additionally inquired to indicate the year they started adopting Green BIM functions. As shown in Figure 4, the first recorded adoption of Green BIM functionalities among Gulf participants dates to 2013. Over time, Green BIM adoption has evolved significantly. This study allowed us to examine their chronological evolution in the Gulf area as follows:

Early adopted functions (2012–2016)

The first Green BIM functions adopted by respondents between 2012 and 2014 primarily focused on improving energy efficiency and performance, including energy modeling, and lighting analysis, indicating that in the early stage of BIM utilization for green building applications, the software was firstly used for energy efficiency assessments and basic sustainability evaluations. Similarly, the initial applications of Green BIM in the gulf area were in lifecycle assessments (LCAs) to evaluate sustainability and environmental performance. In the same sense, early BIM applications were tied to supporting green building certification systems like LEED and BREEAM, which were employed first in 2015. The graph shows the above three functions that were first used in the Gulf area.

Developed in the Mid-Stage functions (2016–2020)

From 2016 to 2021, we started to see a gradual increase in the number of practitioners who employ BIM tools for water usage analysis. This might be in line with the increasing focus on water conservation in building designs, yet none of the participants had used BIM for stormwater management.

In the same period, a rapid increase in the number of Gulf practitioners who were using BIM for waste reduction was observed. This includes modular designs and prefabrication practices. However, slower growth over time until 2020 was detected in using BIM to assess indoor environmental quality, such as thermal comfort and indoor air quality. In this period, BIM functionalities were also deployed for site-specific analysis tools, like environmental impact simulations for site design.

Recently Emerging and Trending (2021–2025)

The most recent and trending functionalities adopted in the Gulf area are carbon footprint and emissions analysis, data management and digital twins, and facility management tools for sustainability, with renewable energy integration also gaining importance. In 2021 and 2022, we began to witness a sudden and unprecedented adoption of BIM for carbon reduction. This indicates that in recent years, BIM has integrated new tools to analyze both embodied and operational carbon emissions, which are essential for meeting modern sustainability targets. Similarly, the embrace of digital twin technologies has increased in the last two years, indicating that they represent a more recent development in BIM. This technology can be used to manage real-time data and improve sustainable building management. It is also worth mentioning that practitioners increasingly employ BIM as a facility management tool to manage long-term performance and resource optimization.

The examination of the results also shows that some BIM features were not used in the Gulf area until the last couple of years. The results show that although BIM is still at its infant level, there is a recent trend in the Gulf area to use BIM in renewable energy integration, such as photovoltaic (PV) panels to optimize energy generation and consumption in buildings. This was observed in 2023 for the first time. The result of the analysis is shown in Figure 4.

The subsequent analysis will rely on the above results to compare the significance of the three diffusion models in explaining the dissemination of the 11 Green BIM functions and their goodness of fit.

The three models were examined for fitness. The results show that the internal influence model exhibited the worst fit, having a low coefficient of determination (R²) and the highest Akaike’s information criterion (AIC) value across all Green BIM functionalities. This means that the internal model fails to accurately approximate the m parameter (the total number of potential adopters in the social system), leading to an overestimation of adopters compared to the actual questionnaire results. Therefore, this model was excluded from the subsequent analysis. A low R² and high AIC for the internal diffusion model imply that it poorly explains the adoption trends of Green BIM in the Gulf region. This indicates that social influence alone (word of mouth and peer adoption) is not the leading driver. Instead, other factors, such as external factors, such as regulations, financial incentives, and project requirements, might play a key. To verify this, the mixed and external models were examined for their fitness. As opposed to the internal model alone, the external and mixed models accurately explained the observed adoption patterns in the real-world data with high R² and low AIC values. A high R² means that the model accurately explained much of the variation in the actual number of BIM adopters over time. Similarly, a low AIC value indicates that the model is an efficient or accurate representation of the adoption trend. The two models accurately estimated the key parameters (a, b, and m).

The external influence model effectively estimated parameters for 9 Green-BIM functions, and the mixed model realized accurate estimates for 9 functionalities. Nonetheless, both models were incapable of forecasting parameters for both the renewable energy integration and data management and digital twin functions, likely due to the limited number of practitioners using this feature.

The findings are presented in

Table 6. Parameters of Green BIM function diffusion in the Gulf region.

Nb	Green-BIM Functions	Model	N	m	a	b	R2 Adjusted	Adjusted AIC
F1	Green Building Certification Assistance	External	77	75	N.A.	0.602	0.987	77.23
		Mixed		69	0.131	0.421	0.902	135.45
F2	Waste Reduction and Construction Optimization	External	73	74	N.A.	0.519	0.978	84.65
		Mixed		66	0.009	0.312	0.894	236.9
F3	Energy Efficiency and Performance	External	66	59	N.A.	0.312	0.922	110.78
		Mixed		68	0.205	0.317	0.984	82.78
F4	Facility Management Tools for Sustainability	External	59	67	N.A.	0.216	0.977	85.89
		Mixed		59	0.303	0.323	0.994	37.33
F5	Material Selection and LCA	External	45	40	N.A.	0.107	0.972	89.32
		Mixed		46	0.114	0.219	0.981	332.5
F6	Water Efficiency and Management	External	32	30	N.A.	0.629	0.997	277.2
		Mixed		43	0.006	0.276	0.973	256.8
F7	Indoor Environmental Quality	External	31	38	N.A.	0.233	0.99	212.17
		Mixed		29	0.134	0.452	0.996	179.54
F8	Sustainable Site Design	External	25	27	N.A.	0.413	0.982	179.31
		Mixed		19	0.067	0.211	0.963	168.04
F9	Carbon Footprint and Emissions Analysis	External	18	15	N.A.	0.204	0.966	37.88
		Mixed		17	0.122	0.232	0.982	67.83

, which confirms that the external model has superior performance and better goodness for fit for 4 functions including (1) water efficiency, (2) site design, and (3) certification assistance, which are largely influenced by external factors like policies, regulations, and incentives. The results show that among these Green BIM functionalities, the most significant external influences are water efficiency and management (b = 0.629), green building certification assistance (b = 0.602), and waste reduction and construction optimization (b = 0.519).

While the mixed models outperform the remaining models for 5 Green BIM functions, namely (1) energy efficiency, (2) material selection, (3) air quality, (4) waste optimization, (5) carbon analysis, and (6) facility management, they are influenced by both external regulations and internal organizational priorities and indicate that balanced drivers, both external and internal, affect their adoption in the gulf region. This implies that both the internal dynamics of an organization and the external pressures from the market, government, and industry are critical for the successful integration of BIM with sustainability objectives. Therefore, organizations need to consider both sets of factors for effective BIM adoption in the green building industry. This suggests that the successful adoption of green building applications is not just about having the right tools or leadership in place but also understanding and responding to external pressures (like sustainability policies, industry collaborations, and global trends in green buildings).

Looking at the mixed model alone and examining the a and b values, the findings reveal that for most Green BIM functions, the influences of the external factors exceed those of the internal factors.

4. Discussion

Unlike previous studies that examined BIM adoption in general construction practices, this study isolates and quantifies the adoption of 11 key BIM functionalities directly linked to sustainability (e.g., energy analysis, water conservation modeling, lifecycle assessments). By distinguishing between firms using BIM for traditional functions (e.g., visualization and cost estimation) and those applying it to sustainability-driven practices, this study offers deeper insights into why Green BIM adoption lags despite the availability of BIM expertise and software. Adding to the above, this study introduces a novel quantitative approach by applying three influence models (internal, external, and mixed) to analyze decision-making patterns in Green BIM adoption. The estimation of adoption parameters (a, b, and m) using the Levenberg–Marquardt algorithm within the Nonlinear Least Squares (NLS) framework is an innovative application in construction research, providing a rigorous and predictive method for analyzing technology diffusion.

Another novelty of this study is that it is one of the first large-scale empirical studies on Green BIM in the Gulf region, surveying 721 industry professionals from 1833 firms registered in architecture and engineering institutes or business directories. This extensive dataset strengthens the statistical reliability of the findings and provides a high-confidence basis (95% confidence level and 5% confidence interval) for assessing Green BIM adoption patterns. The research uniquely segments respondents into two groups: (1) those using BIM for green building functionalities and (2) those using BIM for other purposes but not for sustainability applications. This distinction enables a deeper exploration of why firms with BIM capabilities still hesitate to implement sustainability-focused features, offering actionable insights for overcoming adoption barriers.

4.1. The Perspective of Non-Green BIM Users

The outcome of the survey emphasized the main barriers hindering BIM users in the Gulf region from leveraging their capability for sustainably related functions. It is evident from the perspectives of non-Green BIM users that lack awareness, and knowledge is a key barrier. This highlights the gap in both professional training and academic curricula in the higher education institutions of the Gulf region where sustainability is considered a secondary subject rather than an integrated aspect of BIM practices [84]. Previous studies focused on the importance of integrating sustainability topics in the curricula of civil engineering in the Arab world [6,52]. Although some countries in the Gulf such as KSA took initiatives to align BIM with sustainability concerns [44], this might still be insufficient. The finding aligns with technology acceptance model (TAM) theories, where perceived ease of use and perceived usefulness dictate adoption. In the Gulf context, BIM adoption has been driven by visualization and coordination efficiencies [67] rather than sustainability requirements, reflecting a wider regional trend where construction priorities have traditionally accentuated cost, schedule, and architecture over environmental performance.

The lack of regulatory mandates and client demand further exacerbates the issue, reinforcing the notion that sustainability remains a secondary priority in Gulf construction markets. Unlike regions such as the EU, where stringent regulations drive BIM-based energy modeling and lifecycle assessments, the Gulf’s regulatory landscape is still evolving. While green building codes like ESTIDAMA in the UAE and SASO in KSA exist, they often focus on material compliance rather than enforcing digital sustainability workflows. This aligns with institutional theory, which posits that market behavior is shaped by regulatory pressures, normative influences, and mimetic behaviors. In the Gulf region, there are several regional initiatives like KSA’s Vision 2030 and the UAE’s net-zero targets; in addition to making BIM mandatory for construction projects in Dubai, all these incentives increase the potential that the AEC industry takes initiatives toward sustainability, yet the regulations, which are the main driver of the Gulf AEC industry transformation, are not yet mandating BIM-based sustainable integration.

Despite regulatory efforts mandating BIM adoption in various regions, its widespread implementation remains inconsistent. This suggests that beyond legal requirements, factors such as cost, training, and industry readiness play crucial roles in determining the success of BIM integration in sustainable construction. High software costs remain a significant barrier to BIM adoption, particularly in regions with limited financial resources. However, affordability is only one of many challenges, and other factors such as training accessibility, regulatory enforcement, and industry readiness also influence adoption rates. For instance, a study on BIM adoption in the UK following the 2016 government mandate found that while compliance rates increased, many firms struggled with the financial and technical demands of full-scale implementation (Eadie et al., 2015) [66]. Similarly, in Saudi Arabia, despite Vision 2030 initiatives promoting digital transformation in construction, BIM adoption remains inconsistent, with projects facing difficulties in integrating BIM into existing workflows [85]. These findings highlight the need for continuous training, financial support, and clear implementation guidelines to bridge the gap between regulation and practical adoption.

Moreover, the results of the survey indicated that workflow complexity and inefficient challenges were key drivers. It is worth mentioning that some Green BIM functions, like carbon footprint analysis and renewable energy integration, necessitate integration with specific software like IES-VE or Open Studio, which augments complications to their current fragmented workflows. As is well known, the AEC industry in the Gulf region is characterized by a speedy execution schedule and numerous subcontractors, which means that it faces extra interoperability challenges due to the coexistence of various BIM standards (e.g., IFC vs. proprietary formats), which also discourages more function integrations and training and encourages reliance on traditional energy simulations separate from BIM workflows.

4.2. The Perspective of Green BIM Users

Regarding the perception of BIM sustainability functions users, this study involved the perception of 109 Green BIM users, and only two functions (F1: green building certification assistance, F2: waste reduction and construction optimization, and F3: energy efficiency and performance) were found to be used by more than 65% of the participants. In this case, the Pareto principle indicates that 65% of BIM users are using only 18% (2/11) of the functionalities. This might be explained using Rogers’s assumptions that any technology is composed of hardware, usually more visible to users, and software that need to be effective and accessible for users (Rogers, 1983) [58]. Yet, despite the presence of manuals that can help in conveying significant knowledge about Green BIM utilization, ease of use and user interaction/knowledge transfer are the most effective ways to understand the convenience and usefulness of any technology. To comprehend the relationship between the adoption rate of Green BIM functions and their ease of use, the authors will back on the results of [49] that integrating sustainability aspects, such as the carbon footprint and embodied renewable energy integration, into BIM workflows necessitates the use of particular software and tools such as IES-VE and requires specific knowledge and mature skilled practitioners to perform the analysis, thereby making these functions hard to use by new BIM adopters, as the above reasons add complications to the workflow. Adding to the above [53], in their study, the lack of seamless integration between BIM tools and specialized renewable energy integration and data management software led to more difficulties.

These conclusions might help in explaining the rationale behind having a low adoption rate for these functionalities (F9 with 17%, F10 with 6%, and F11 with 5%).

The results of Figure 4 demonstrate that users have passed through the use of most BIM sustainability-related functions before adopting the data management and digital twin function, which was the latest and the least function to be adopted; i.e., the data management and digital twin function was adopted for the first time in 2022 by only one participant, while in 2022, all the other functions were already adopted by a higher number of practitioners. This indicates that only mature users who are familiar and professional with the usage of a variety of Green BIM functions can start operating BIM for digital twin and data management.

Internal versus external factors

The results of the study highlight that the diffusion of all BIM sustainability-related functions in the AEC sector of the Gulf region is principally driven by mixed factors and more powerfully by the external components (the b parameter in Table 6) such as government regulations and policies, market conditions, and media rather than the imitative behaviors and the bandwagon pressure (internal factors).

The results reveal that the mixed model best describes the diffusion for five Green BIM functions (F3, F4, F5, F7, and F9), indicating that there is a combination or interaction between internal and external factors that affect the adoption of these five Green BIM functions. Examining the a, b, and m parameters for the functions where the mixed model outperforms the external model shows that for all functions, b > a indicates that the external factors have the biggest effect. In the practical world, this means that external marketing and regulatory incentives might play a vital role in proving Green BIM’s utility in realizing water efficiency, waste reduction, and compliance with green building certifications like LEED or BREEAM but also the internal skills of construction experts, comprising their awareness of sustainability paybacks and earlier exposure to Green BIM tools, which impact adoption but less significantly. For the remaining functions in the model (F1, F2, F6, and F8), the external model best describes their diffusion (R² is higher and AIC is lower for the external model than the mixed model), indicating that the presence of industry-wide standards and the requirement for BIM in government projects push adoption forward. Also, considering the external financial factors, the results imply that external factors, such as government incentives, subsidies for sustainable construction, and the decreasing cost of BIM software, encourage the wider diffusion of Green BIM. For the four functions that were best described by the external model, the results imply that legal frameworks, incentives, and restrictions are very important but are not alone affecting the diffusion. According to the theory of the external diffusion model, other factors such as (1) the existence of market competitors and economic trends which also profile the diffusion rate and (2) the media and mass communication which increase awareness and desirability also affect diffusion [24,86]. Also, adding to the above, the authors of [49] confirmed that the availability and expansion of complementary technologies stimulated diffusion.

These findings were not expected yet homogenous. The findings do not conform with the study of [24], who studied the diffusion of BIM in the MENA region and found that the mixed model, but mainly the internal factors (such as social influence and peer networks), play a more significant role than external factors (like government policies and market conditions) in driving BIM adoption in the MENA architectural, engineering, and construction (AEC) industry. These results are the same when compared to many studies in the same region [38,87].

Additionally, this study indicates that, according to non-Green BIM users, the main barriers were related to a (1) lack of BIM knowledge, which stems from within the organization, as professionals may lack the expertise, training, or awareness of BIM functionalities; (2) the complexity of BIM–Internal relations due to skill gaps, learning curves, or resistance to change; (3) workflow issues and organizational integration challenges; and (4) client demand. All the above, apart from client demand, are internal factors. Only one barrier, client demand, is perceived by non-users and is an impediment to the adoption of green practices on BIM. Internal organizational workflow adjustments must align with external software requirements and industry best practices.

The above two insights might lead to the conclusion that the adoption of BIM functionalities, in general, is led by mixed models but mainly internal factors, yet those specific functions related to green building and suitability practices are mainly driven by the mixed model but mostly by external factors.

In other words, an internal push is needed to induce non-users to adopt Green BIM functions; i.e., internal factors are mainly needed in the pre-adoption stage of Green BIM. Yet when the adoption occurs, the external factors are those affecting the utilization or the favoring of one functionality over the others.

Concerning F1 (green building certification assistance), the results for both external factors outperform the internal factors, indicating that although there is an internal preference for the prestige associated with certifications (internal factors), the demand for certified sustainable buildings in global markets and the stakeholder expectations and marketing potential for green labels dominate adoption patterns.

In the last decade, countries in the Gulf area including Bahrein, Qatar, KSA, and the UAE have been encouraged by global trends and are trying to obtain green certificates (LEED, WELL, and BREEAM) for most of their big project such as Expo Dubai 2020, which revealed a market demand for sustainability [33,44]. In this sense, the GCC Green Building Market study outlined how certifications, stainability accreditations, and environmental endorsements can enhance brand positioning and investor confidence [49]. BIM proved to be a tool that aids in obtaining a green certification, as it not only facilitates energy and water simulations but also helps in achieving and documenting the data that align with LEED and BREEAM, among other certification requirements.

Apart from this, the authors also examined the diffusion of waste reduction and construction optimization (F2). Table 6 shows that the external model best describes the diffusion, indicating that legislation on construction waste management (e.g., EU directives, Saudi Vision 2030 targets, and the media’s focus on sustainability in construction and the circular economy) is mainly affecting the use of this green function. Legislation on construction waste management in KSA, such as the Waste Management Law issued by Royal Decree No. M/3 in 2021, mandates strict regulations on waste handling and disposal. This forces the AEC sector to implement helpful waste reduction strategies such as BIM, as it enables precise material estimation and aligns project practices with legal requirements. The study of [16] underlines that adopting BIM helps in improving project efficiency and compliance with environmental regulations.

For F3, energy efficiency and performance, the mixed model best estimates the parameters, indicating that government policies on energy codes and efficiency standards and media highlighting energy crises and solutions (external), as well as organizational priority for energy savings (internal), affect the adoption of this function. Government incentives, such as renewable energy subsidies for solar and wind projects, play a crucial role in driving the early adoption of energy-efficient technologies [29]. Moreover, bandwagon effects, where establishments adopt sustainable innovations due to market trends and competitive pressure, further accelerate adoption [58]. In other words, as both the a and b parameters are significant for these functions, the incentives for renewable energy integration (e.g., subsidies for solar/wind) and the bandwagon pressure to adopt energy-saving technologies increase the chance of people adopting this specific function. Subsidies and tax benefits in the Gulf, such as the Shams Dubai Initiative (UAE) and KSA’s PPAs, decrease costs and incentivize renewable energy adoption. BIM optimizes project design, enhances financial planning, and ensures compliance with regulations to maximize incentives. By integrating subsidies into cost analysis, BIM drives efficient and profitable renewable energy installations.

Similarly, the diffusion of F4, facility management tools for sustainability, is also affected by both internal factors, including organizational readiness, such as staff skills and existing technology infrastructure, and external factors, including government regulations on sustainability and client demand for green buildings. These pressures can either push early adoption through external incentives (in this study, the first adoption was in 2017) or sustain it through internal operational needs [58], improving resource management and energy efficiency (as it continues to be used at an increasing rate till 2025).

Concerning material selection and LCA (F5), the mixed model also best fits the data, with both a and b parameters being significant. This indicates that embracing this function is related to both external certification demands and internal environmental goals. Recently, there has been a global push for sustainable construction materials and reporting (e.g., embodied carbon limits), and this seems to also affect the Gulf region [16], yet the results show that internal or in-house expertise for LCA integration needs to be available, especially as the green certificate also demands LCA compliance.

Internally, the lack of awareness about embodied carbon in materials in many countries might be a considerable challenge as it impends the smooth and successful integration of LCA into BIM workflows [88], because stakeholders may not totally grab the significance of evaluating the environmental impact of materials throughout their lifecycle. Apart from the internal pushes, governments in KSA, the UAE, Kuwait, and Qatar have introduced new material sustainability laws in the last decade [32]. In one way or another, these laws are pushing the AEC sector to perform more environmental assessments, such as LCA, for which BIM can be a convenient tool [59]. The results of Figure 4 show that more and more practitioners are utilizing BIM to assist in material analysis and LCA, as it delivers a complete platform for evaluating data throughout the lifespan of a building structure. This trend underlines the significance of tackling both internal and external factors to fully leverage BIM for LCA and to meet the evolving regulatory and environmental demands. Yet internal limitations such as the lack of knowledge and skills about embodied carbon and other sustainability metrics can hinder them from complying with the new requirements [51].

For F6, water efficiency and management, the external factors best describe their diffusion. This might be explained by the presence of regulatory frameworks and government policies such as sustainability mandates and water conservation laws, which are driving the adoption of BIM for water management in the Gulf area. Digging more into the mandates for water efficiency in the Gulf area, the review of the literature pointed out that mandates such as the ESTIDAMA Pearl Rating System in the UAE require water conservation for many projects which might be the reason why BIM adoption for this specific function has increased in the Gulf/UAE. Recently, Kuwait also has shown interest in reducing and managing water utilization in buildings to abide by the recent Kuwait Environment Public Authority (KEPA) 2024 environmental policies [32]. Likewise, Bahrain’s National Energy Efficiency Action Plan underscores water conservation as part of its sustainability goals, promoting BIM as a tool to achieve these objectives [33].

For F7, indoor environmental quality and BIM functionality, the results show that both the internal and external factors are important, though the external ones have more power. It is worth mentioning that health-focused policies and regulations in the Gulf region might be a key driver for adoption. For instance, Qatar’s Global Sustainability Assessment System (GSAS) and KSA’s Vision 2030 sustainability goals emphasize improving indoor environmental quality (IEQ) to improve occupant health and well-being; these policies in turn incentivize practitioners to implement BIM for a healthier design and monitor air quality. Similarly, Bahrain’s National Energy Efficiency Action Plan includes provisions for healthier indoor spaces, further encouraging the use of BIM. Concerning the internal factors, the mounting demand for high-performance structures with higher IEQ withstands the diffusion of BIM. The results in Figure 4 highlight that construction companies in the Gulf area are more and more spotting the worth of BIM in improving air quality, thermal comfort, and lighting, which supports both regulatory requirements and market expectations. In this sense, [39] examined the role of BIM in providing sustainable designs. Their case study, which focused on Gulf Organization for Research and Development (GORD), revealed the importance of BIM in accounting for health and environmental considerations in construction.

When examining the drivers of the sustainable site design functions, the results in Table 6 outline the external factors as the key drivers. According to the authors of [31], urban planning policies including zoning laws and sustainability mandates directly increase the rate of adopting various software to design sustainable sites. The authors of [31] examined the impact of urban mobility planning policies in Qatar and found that new laws include firm requirements related to sustainable site development. This results in a better diffusion of these specific BIM functionalities as BIM allows and facilitates meeting the requirements and aligning with the policies. Similarly, KSA’s Vision 2030 and Bahrain’s National Energy Efficiency Action Plan accentuate sustainable urban development. Furthermore, stakeholder pressure from clients, investors, and regulatory bodies to minimize environmental impacts is a critical factor. The authors of [39] underlined how BIM permits shareholders to picture and enhance site layouts, reduce environmental footprints, and comply with sustainability goals.

The results reveal that the mixed model is accurately estimating the parameters for F9, carbon footprint and emissions analysis, in the Gulf area. It is worth mentioning here that the external pressure from international agreements, such as the Paris Accord, has pushed Gulf countries to implement severe carbon reduction measures, thereby supporting the embracing of BIM for accurate emissions tracking and analysis. Internally, corporations are motivated by the necessity to improve their image and meet corporate commitments to carbon neutrality, which supports global sustainability trends. Moreover, client expectations for net-zero buildings are growing in the Gulf area [16], mostly in high-profile projects, further incentivizing the adoption of BIM to bring sustainable outcomes. GORD reports feature how BIM is a critical tool for achieving environmental targets in the Gulf area.

5. Conclusions

The diffusion of BIM sustainability-related functions in the Gulf area is continuing to rise in accordance with an increasing trend. BIM users’ awareness and understanding of non-environmentally friendly building-related functions in the Gulf region are limiting the realization of BIM’s full sustainability potential, primarily due to a combination of knowledge deficiencies, a lack of client demand, and technological fragmentation.

Concerning Green BIM users, this study showed that the Gulf area is missing BIM capability as a transformative tool for sustainable construction (a low percentage of adopters). A deeper examination suggests that while some BIM functions like energy modeling and waste reduction are frequently adopted, other functionalities like carbon footprint analysis and renewable energy simulations are barely used potentially due to their complexity or the need for specialized tools. Three diffusion models (internal, external, and mixed) were employed. The results show that the mixed model best fits the results and estimates perfectly the needed parameters for F3, F4, F5, F7, and F9, and the external model best fits F1, F2, F6, and F8. Yet the results of the mixed model outline that the external factors outperform the internal factors. This highlights the significance of rules, regulations, and the media in green buildings. The low number of people adopting green BIM functions highlighted the key role of both regulatory frameworks and awareness in determining the future of sustainable construction practices.

This study has significant research and practical implications, primarily by bridging the knowledge gap on the factors influencing the adoption patterns of Green BIM functions, providing a comprehensive understanding of the key drivers within the Gulf region’s construction industry, an area that has historically been under-explored and is currently at an early stage in adopting BIM. The author is aware that research is the initial study to investigate the influence of diffusion modes on the adoption of BIM sustainability-related functionalities. These results assist managers and professionals in enhancing their execution and provide guidance to policymakers regarding their involvement in encouraging the development of green buildings.

This study significantly contributed to the Gulf area by identifying the most used BIM functionalities that address sustainability issues such as green certification assistance, waste reduction, and energy efficiency. While BIM has been widely researched, there is a lack of region-specific studies focusing on its role in sustainable construction practices. This research addresses that gap and provides new information on the barriers, drivers, and patterns affecting the adoption of Green BIM functionalities in the Gulf region. Thus, it offers practical insights into how sustainability-focused BIM tools can be integrated into local construction practices, benefiting industry professionals in the region. Also, the findings are relevant for policymakers and regulators in the Gulf area, as they provide data that can inform the development of policies, incentives, and regulations to encourage the broader use of Green BIM tools. This is crucial for promoting sustainable construction practices in line with Saudi Vision 2030, which emphasizes the importance of sustainability and environmental conservation in the region’s development. The research also aids in aligning the construction industry with global best practices for sustainable building. By promoting the use of Green BIM tools, this study supports the nation’s transition to more sustainable construction practices, thereby helping to achieve the long-term sustainability objectives outlined in Vision 2030, particularly in the areas of environmental conservation and energy efficiency.

The results highlight the need for industry professionals to align their practices with both external regulations and internal efficiency measures. Contractors, engineers, and architects should invest in BIM training and collaborate with policymakers to ensure compliance with sustainability standards. But at the same time, managers should guarantee the availability of skills and resources needed, as well as infrastructure for the efficient adoption of green functions.

The research further shows that theoretical education in Gulf universities lays the essential groundwork; however, practical implementation proves crucial for mastering BIM and sustainability principles. To close this disparity, educational programs should include practical training sessions, partnerships with industries, and actual real-world projects. Integrating BIM into construction workflows through experiential learning is demonstrated to enhance both adoption and efficiency according to the results.

A limitation of this research is that it did not examine the reasoning behind the differences in the number of users adopting various features. Subsequent research can investigate this further. Presently, the models employed assume that the contributing factors remain unchanged over time; however, to enhance the models’ accuracy, future research could potentially evaluate the dynamic factors that influence the subjects, rather than the static factors, with the aim of refining the model.

The mathematical model offers a structured framework for evaluating the spread of Green BIM functions, but its limitations must be acknowledged. BIM adoption is significantly impacted by user expertise, an organization’s preparedness, and regulatory guidelines, which may be overlooked by quantitative analysis on its own. Integrating qualitative insights into mathematical modeling improves the comprehensiveness of assessments.