A Systematic Review on the Organizational Learning Potential of Building Information Modelling: Theoretical Foundations and Future Directions

Abstract

Organizational learning refers to the systematic development, exchange and dissemination of knowledge throughout the organization. Organizational learning processes in construction are disrupted by the decentralized flow of information and the temporary, short-term nature of project teams. The emergence of Building Information Modelling (BIM) has significantly enhanced the ability to capture and disseminate construction project knowledge within the architecture, engineering, construction, and facilities management (AEC-FM) sector. Despite this progress, existing research has predominantly focused on the technical aspects of BIM, with limited evidence on its effects on organizational learning capabilities. This study addresses this gap by examining how BIM shapes organizational learning mechanisms within AEC-FM contexts. Employing a systematic literature review (SLR) approach, 104 articles from the Scopus database were analyzed using scientometric and thematic analyses. The systematic review of the literature was carried out following the PRISMA guidelines. The SLR provided a comprehensive examination of BIM’s contribution to strengthening the three core organizational learning mechanisms: experience accumulation, knowledge articulation, and knowledge codification. The thematic analysis revealed seven BIM-enabled organizational learning factors that are expected to strengthen learning mechanisms in AEC-FM organizations: agility of thinking and reasoning skills; enhanced decision-making; interconnected stakeholders’ relationships; integrated business processes; BIM-facilitated project knowledge sharing; BIM-supported project knowledge retention; and BIM-supported project knowledge extraction. Findings suggest that BIM significantly facilitates learning mechanisms within AEC-FM firms. A conceptual model of BIM-supported learning mechanisms was developed to highlight opportunities for enhancing organizational learning capabilities in the BIM environment.

1. Introduction

Innovation is an essential element for Architecture, Engineering, Construction, and Facility Management (AEC-FM) businesses if they wish to remain competitive in the construction industry. Construction activities are knowledge-intensive activities [1], and each construction project is a unique project. The knowledge gained in previous projects can be used as a source of knowledge in subsequent construction projects [2]. Knowledge as a valuable asset has an underlying impact on creating core competencies and innovation [3]. AEC-FM organizations should constantly seek to update their technical skills and knowledge if they want to generate innovative outcomes [4].

Previous research has shown that organizational learning processes enable organizations to manage and exploit the acquired knowledge [5]. Organizations utilize various learning mechanisms to acquire knowledge from the inner and outside environment. However, geographical dispersion of AEC-FM companies and the temporary nature of construction projects create barriers to manage lessons learned in construction projects [6]. Bartsch, et al. [7] argue that the depletion of the three main factors of knowledge management (opportunity, motivation, and capacity) is due to the discontinuous nature of projects.

Building information modelling (BIM), as a collaborative working methodology, can be used to support organizational learning processes [8]. BIM enables a continuous learning process by collecting, transferring, and retrieving project knowledge at different stages of a project lifecycle [9,10]. The unique features of BIM, including parametric modelling, automation, virtual visualization, and centralized knowledge repository present opportunities for more effective learning within AEC-FM organizations. BIM’s role as a centralized knowledge repository reinforces its socio-technical dimension by promoting interdependent communication and fostering collaborative working relationships [11]. Through this integration of technology and social interaction, BIM enhances decision-making and cultivates a shared understanding among project stakeholders. Despite these advantages, there remains a lack of comprehensive analysis on how these BIM features actively support and shape learning mechanisms within AEC–FM organizations [12]. Although great progress has been made in BIM-based knowledge management (BIM-KM) domain, the organizational learning literature has eminent gaps in this area, and little is known about the fundamental role of BIM in supporting organizational learning mechanisms. The literature has given limited attention to how BIM capabilities are situated within organizational learning processes. This limitation stems largely from the frequent conflation of knowledge management and organizational learning. Knowledge management primarily concerns the handling of knowledge artefacts and tasks, such as codification, storage, retrieval, and sharing. In contrast, organizational learning refers to the dynamic and iterative processes through which organizations interpret experience, adapt routines, and modify collective practices to enable improvement and innovation. Current BIM–KM research predominantly adopts a functional or technical perspective, emphasizing information exchange, 4D sequencing and project scheduling, and construction safety knowledge management, etc., while offering limited insight into how BIM supports learning mechanisms such as experience accumulation, knowledge articulation, reflection, and the institutionalization of lessons into organizational routines. Accordingly, numerous studies have examined BIM’s technical capabilities; however, there has been less comprehensive synthesis of its impact on organizational learning mechanisms. This gap is particularly significant given that BIM represents not just a technological tool, but a socio-technical system that fundamentally alters how project stakeholders interact, communicate, and share knowledge. The ability of BIM to serve as a centralized knowledge repository while facilitating real-time collaboration suggests its potential to overcome traditional barriers to learning in the AEC-FM sector [13]. Also, the majority of research has focused on the values of BIM at project level, but this research focuses on the level of AEC-FM organizations. The fragmented nature of existing research on BIM’s organizational impacts necessitates systematic approach to identify patterns and relationships across diverse studies. Addressing these limitations, a systematic literature review (SLR) was deemed necessary for this research due to the rapid evolution of BIM implementation practices and given the strong emphasis on the literature to consider BIM as a socio-technical approach rather than merely a technical tool. Therefore, this paper addresses these gaps by investigating how BIM helps AEC-FM organizations foster their learning mechanisms in a project environment. This SLR study aims to address the following research questions: RQ1. How does BIM facilitate the learning mechanisms within organizations in the AEC-FM sector? and RQ2. What are the limitations in extant research regarding the use of BIM to enhance organizational learning mechanisms?

The remainder of this paper unfolds as follows: the literature review on organizational learning and BIM as a learning platform are explained in Section 2, followed by an explanation of the employed methodology in Section 3. In Section 4, the result and discussion, including seven BIM-enabled organizational learning factors are presented. Finally, a conceptual model is developed in Section 5 before conclusions are presented in Section 6.

2. Literature Review

2.1. Organizational Learning

The significance of organizational learning has been underlined by many scholars from different perspectives including continuous improvement and organizational competencies [14,15], innovation [16], and knowledge management [17]. In knowledge management literature, there is a distinctive difference between information, knowledge, and organizational learning. Information represents data that have been processed to become meaningful and useful; knowledge emerges from the thoughtful application and interpretation of that information [18,19]; and organizational learning is conceptualized as the process through which knowledge is embedded into organizational routines, decision-making practices, and behaviors, resulting in cognitive development over time [20]. In this regard, Argote [21] considers organizational learning as a change in an organization’s knowledge arising from experience. Similarly, Levitt and March [22] believe that organizations learn through encoding historical information into routines that guide their behavior [23]. They further explain that organization’s behavior is based on routines, and routines are generated by interpretations of the past events rather than anticipations of future events. Levitt and March [22] define the term routines as “the forms, rules, procedures, conventions, strategies, and technologies around which organizations are constructed and through which they operate.” In a similar vein, Zollo and Winter [24] focus on the role of (1) experience accumulation, (2) knowledge articulation, and (3) Knowledge codification processes as the key learning mechanisms through which organizations develop their operational routines. Learning mechanisms have been systematically used by organizations to eliminate barriers in a dynamic business environment. The term experience accumulation refers to the central learning process in which operating routines are usually developed [24]. There is a pressing need for experience accumulation where technology and competing conditions are rapidly changing. Levitt and March [22] argue that organizational search and trial-and-error experimentation are two essential mechanisms to alter operating routines in response to direct organizational experience. Knowledge articulation refers to the process by which tacit or implicit knowledge is understood and shared between individuals such as debriefing session and collective discussions [24]. Interaction with colleagues, collaboration, socialization and communication are the ways to share tacit knowledge [9]. Knowledge codification refers to the process of codifying knowledge through using tools such as manuals, project management software, etc., to develop guidelines for the implementation of future tasks [24]. Codification of knowledge enables the dissemination of lessons learned.

In the construction context, AEC-FM organizations can learn through various sources such as direct experience in the project environment (e.g., in-house research activities), and from sharing experiences with other project stakeholders or peers. According to Lin [25], architects, engineers, contactors, and suppliers involved in construction projects act as knowledge workers, aiding in the collection and management of knowledge across current and previous projects. Therefore, the increased integration and interaction between AEC-FM will facilitate tacit knowledge sharing in construction projects. In this regard, Anderson, et al. [26] observed that cooperative learning was a significant factor in transferring knowledge in joint ventures. Similarly, Holt, et al. [27] argue that construction businesses can benefit from strategic construction alliances to achieve competitive advantage through knowledge transfer with their project partners.

Given the significance of organizational learning, the fragmented nature of construction projects hinders knowledge collaboration among AEC-FM organizations. Organizational learning mechanisms are disturbed by information decentralization and transient nature of construction projects [28]. Fragmented construction processes have always made effective communication and efficient information management difficult [29].

In addition, research on innovation has found that there is a link between learning from experience and the speed of project termination. Rapid termination of projects and allocation of resources to new projects create barriers for organizational members to codify lessons learned at the end of a project [30]. Even the codified knowledge, in some cases, is temporary due to the lack of long-term relationships between AEC-FM organizations. In the event of rapid project termination, resources are immediately allocated to new projects with a low chance for reflection on failures in previous projects. In this case, effective information and project knowledge will be lost if they are not captured on time by the teams that possess them [29]. Therefore, the AEC-FM industry runs into many challenges when it comes to integrating its knowledge in conventional project delivery processes.

2.2. BIM as a Socio-Technical Learning Platform

BIM has emerged as a significant innovation within the AEC–FM industry, largely due to its recognized business value in managing and sharing project information. Beyond its technical utility, BIM also plays a pivotal role in reinforcing organizational learning mechanisms, particularly when AEC–FM firms engage in collaborative project environments. BIM facilitates easy updating and transfer of information through virtual visualization and keeping information digitally [31]. The business values of BIM such as enhanced stakeholder collaboration, information management, and decision-making across the facility lifecycle [32] are achieved through data-rich models and data-driven collaboration. BIM as a new paradigm shift from traditional document-based practices to integrated digital environment, enabling the creation, management, and exchanges of information through parametric and data-rich models [33].

Literature increasingly recognizes BIM as a socio-technical platform, emphasizing that its value extends beyond technical functionalities. While BIM offers advanced data-rich models, visualization, and parametric design, its successful implementation also depends on the alignment of social factors [34]. The socio-technical perspective positions BIM not merely as a software tool, but as an integrated system in which technology, people (actors), tasks, and organizational structures are deeply interconnected. The concept of socio-technical systems (STS) emerged to characterize work environments shaped by the intricate interplay between human actors, technological tools, and the broader organizational and environmental context in which they operate [35]. Within intraorganizational construction settings, the STS model conceptualizes organizational functioning as the interplay of four interdependent components: tasks, structure, actors, and technology [11]. These elements maintain a balanced socio-technical environment, where the effectiveness of one component is inherently linked to the performance of the others [36]. In BIM projects, a set of policies, processes, and technologies are integrated to produce a digital model of managing the design and project data throughout a facility’s lifecycle [37]. Data rich BIM model produced by BIM tools (technology) facilitates sharing and exchanging project information. This digital model serves as a repository of information and can be used throughout the entire life cycle of a facility. There are AEC-FM stakeholders involved in the BIM process (actors). BIM also changes traditional design and construction work practices (tasks) requiring 3D coordination and design reviews, developing BIM execution plans (BEP), etc. The organizational structure factor requires changes in organizational structure to support collaborative work (structure).

Several studies have examined the business values of BIM adoption. For example, the seminal work of [37] highlighted the business values of BIM in terms of model-based collaboration, information repository and stakeholder integration. BIM-enabled information repositories support improved traceability, data reliability, and decision-making throughout a facility’s lifecycle, reinforcing cross-organizational collaboration and long-term asset management efficiency. Aranda-Mena, et al. [38] analyzed the business factors driving BIM adoption in five Australian architecture and engineering firms. In four of the five case studies, improved information flow was identified as one of the top benefits of BIM. Similarly, Ref. [39] emphasized BIM’s role in improving process integration and collaborative workflows across project teams. Čuš-Babič, et al. [40] examined how BIM can be used for integrating information flow in industrialized construction projects, including design, prefabrication, and on-site construction tasks. They observed that use of BIM led to a more transparent stakeholder relationship than paper-based communication due to the more reliable information exchange in BIM compared to 2D drawings. The AEC-FM organizational tie and collaboration can be strengthened due to this transparent relationship in BIM projects.

Certainly, the role of BIM as a learning platform can be seen as a key factor driving the widespread adoption of BIM. Scholarly research has demonstrated that employing knowledge-based techniques can enhance BIM capabilities, facilitating the sharing of knowledge, ultimately benefiting stakeholders [41]. A wide range of analytical applications can be created by using BIM, including energy efficiency analysis, automated clash detection, structural analysis, cost estimation etc. As discussed by Charlesraj [42] the information stored in BIM models is primarily driven by knowledge rather than reliant solely on information. These characteristics of BIM elevate it as a sophisticated learning platform. Despite extensive research on BIM-enabled information integration and collaboration, limited studies have examined the learning capacities of BIM in existing literature, which was the primary aim of this study: to investigate the learning potential of BIM.

3. Methodology

3.1. Review Design and Protocol

This study reports the outcomes of a systematic literature review (SLR) conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement [43] (Supplementary Materials). An SLR was conducted to gain a comprehensive overview of BIM’s potential role in enhancing AEC-FM organizations learning mechanisms. Systematic reviews synthesize current knowledge to highlight future research directions, address complex questions, identify primary research gaps, and theories about phenomena. Authors should clearly detail the review’s purpose, methods, and findings to ensure its usefulness [44]. The aim of SLR was to explore and consolidate evidence regarding the impact of BIM on organizational learning processes. The systematic review was implemented in four key stages: identification, screening, eligibility assessment and synthesis. It followed the SLR methodology proposed by Kitchenham, et al. [45], encompassing sub-stages such as ‘Research Questions’, ‘Search process’, ‘Selection criteria’, ‘Quality Assessment’, ‘Data Collection’, and ‘Data Analysis’, which are discussed in detail in the following sections.

During the identification stage, Author 1 conducted the database searches, while Author 2 verified the search strategy and keywords. In the screening stage, both authors reviewed the titles and abstracts, and disagreements regarding the manuscripts’ appropriateness were resolved through discussion. Data extraction and thematic synthesis were conducted collaboratively. The SLR process is shown in detail in Figure 1.

3.2. Research Question

This study seeks to address the following research questions:

RQ1. How does BIM facilitate the learning mechanisms within organizations in the AEC-FM sector?

RQ2. What are the limitations in extant research regarding the use of BIM to enhance organizational learning mechanisms?

To address RQ1, we conducted a search using keywords aligned with Zollo and Winter [24] organizational learning theory and employing NVivo for thematic analysis. Zollo and Winter [24] framework of organizational learning was used in this study as it is widely used in research on organizational routines and knowledge management literature. The choice of this framework was theoretically motivated by its explicit focus on learning as an organizationally embedded process that operates through routines and structured mechanisms, which aligns closely with the nature of BIM-enabled practices. Zollo and Winter describe organizational learning as an intentional process in which organizations build experience, articulate insights, and codify knowledge, gradually shaping and stabilizing their routines. This process-based, routine-focused perspective aligns well with the study of BIM-enabled learning, since BIM practices are largely carried out through structured workflows and formal organizational procedures rather than relying solely on individual cognitive reflection. Alternative organizational learning models, while influential, were less appropriate for the specific analytical focus of this study. For example, Nonaka’s SECI model centres on the conversion of tacit and explicit knowledge, making it more relevant to knowledge creation and sharing than to the institutionalization of learning within organizational routines [46].

The construct of organizational learning in Zollo and Winter’s framework aligned well with the purpose of this study, enabling the authors to contextualize BIM technical features within organizational learning functions.

We explored how BIM facilitates learning mechanisms within AEC-FM sector organizations, identifying themes and subthemes that illustrate its impact. With respect to RQ2, we methodically identify and analyze existing research on the impact of BIM on organizational learning in the AEC industry, leveraging the thematic codes established in RQ1.

3.3. Search Process

The search process of this study unfolded in three primary phases. Initially, a search string was crafted to identify scholarly works pertinent to the study’s scope, goals, and objectives, focusing specifically on “organizational learning” and “BIM”. For the selection of keywords related to organizational learning, the authors utilized the keywords from the literature on organizational learning mechanisms. The authors developed and applied the following search syntax to gather relevant publications: ((“building information modelling*”) AND (“knowledge sharing” OR “sharing experiences” OR “knowledge articulation” OR “meetings”) AND (“knowledge management” OR “managing knowledge” OR “organizational learning”) AND (“knowledge codification” OR “knowledge retrieval” OR “manual recording” OR “documenting” OR “knowledge capture” OR “as-built BIM”) AND (“record lessons learned” OR “practice-based learning” OR “trial-and-error” OR “research and development”)).

The search, conducted within the “Scopus” database, retrieved 825 materials in August 2025. Different databases, such as Web of Science, Scopus, and ProQuest can be used to search articles. However, Scopus stands out for its comprehensive coverage of journals in construction project management and construction IT, surpassing other databases in terms of both the breadth of journals and the inclusion of more current publications [47]. Given the focus of this study on BIM, a field that is both emerging and rapidly expanding, the selection of Scopus as the primary data source was deemed appropriate.

Following an initial search, after removing duplicates and not in English sources 709 remained for the first run of screening which focused on title and abstract review based on the established selection criteria, including specific inclusion and exclusion parameters, to refine this pool. The selection was conducted by two researchers who reviewed the titles, abstracts. In the second run of screening the authors reviewed the full texts of these studies. To ensure consistency in the screening process, two researchers independently reviewed all titles, abstracts and full text. Any discrepancies were resolved through discussion until consensus was reached, resulting in an agreement level of 94%. This rigorous selection procedure resulted in 104 studies being earmarked for further analysis, chosen in accordance with the predefined inclusion and exclusion criteria detailed subsequently (Appendix A).

3.4. Selection Process

To ensure the integrity and relevance of our systematic review, the following inclusion and exclusion criteria were established. Figure 1 illustrates in detail the selection criteria adopted in this research. These criteria were meticulously designed to provide transparency and rationale behind each decision, ensuring that the studies included had logical and valid motives that contribute to the research objectives.

3.4.1. Inclusion Criteria

Project/Industry-Based Research: Study must be validated within an industry setting, reflecting real-world applications and outcomes. This criterion ensured that the findings were grounded in practical experience rather than purely theoretical constructs.

Related Disciplines: Included studies should specifically pertain to the disciplines of design, construction, and operation within the project context. This specification aimed to capture a comprehensive view of the entire lifecycle of industry projects and their relationship with knowledge and experience sharing workflows.

Empirical Application of Managing Project Knowledge/Experience Workflow: The article must clearly articulate the empirical application of managing project knowledge or experience workflows. The rationale behind this criterion is to ensure that the studies provide actionable insights into the effective management and dissemination of knowledge within industry contexts.

3.4.2. Exclusion Criteria

Irrelevance and Language: Studies not directly related to the research scope or not in English.

Peer-reviewed sources: White papers are excluded to maintain a focus on peer-reviewed academic research.

Academic Focus: Conceptual or academia-only research without project-based validation.

Secondary Research: Review papers and meta-analyses were excluded to avoid double-counting findings and to focus on original, industry-validated evidence.

Duplicates: Only the most comprehensive report of a study is included if duplicates exist.

3.5. Quality Assessment

Our review paper employs a streamlined quality assessment (QA) procedure focusing on three key questions to ensure methodological soundness:

QA1: Criteria Appropriateness

Are the inclusion and exclusion criteria clearly and consistently applied in all papers reviewed?

QA2: Quality Evaluation of Studies

Are the included studies’ quality and validity systematically assessed to identify any biases or methodological issues?

This criterion was assessed through a careful review of the paper to ensure that the research was implemented and validated through an empirical BIM case study or project.

QA3: Study Descriptions Adequacy

Are the selected studies described with sufficient detail to understand their relevance and contributions?

For this quality assessment criterion, the research methods, results, and discussion sections of the studies were reviewed to ensure that the authors provided sufficient information on how BIM was applied in that project, as well as the outcomes and benefits achieved in relation to project knowledge management and organizational learning mechanisms. To implement these evaluation criteria, we conducted a dual reviewer assessment for each QA question, ensuring a thorough and unbiased review. In cases of disagreement, a third-party resolution was sought to maintain objectivity. This approach aims to underscore the reliability and credibility of the included studies, reinforcing the review’s overall integrity. Risk of bias due to missing results was assessed by examining whether expected outcomes were consistently reported across studies addressing similar research questions.

3.6. Data Collection

The extracted data from each study included:

• The publication source (journal or conference).
• Publication years.
• The principal subject area, focusing on BIM’s role in organizational learning and knowledge management.
• An assessment of the study’s quality.
• Confirmation of the study’s validation within an industry context and its application in real-world scenarios.

In the next step, to facilitate the collection of this information from the primary studies, we developed a data collection form in Excel™. In this form, title, authors, publication date, type of article, contribution, area of focus, and name of publication, conference, or book were all listed.

3.7. Data Analysis

The literature review included both bibliometric analysis such as publication years and sources (conference or journal articles) and analytical insights derived from thematic analysis. Thematic analysis of the studies highlighted the focal areas, key achievements, disciplines involved, and significant findings.

3.8. Bibliometric Analysis

Given the exponential growth of academic literature in the digital age, this study employed bibliometric analysis using VOSviewer version 1.6.20 to systematically map and visualize complex patterns within scholarly discourse [48]. VOSviewer was selected for its sophisticated capabilities in cluster analysis and network visualization based on co-citation and co-occurrence relationships, enabling identification of distinct research streams while maintaining methodological rigor [49]. Scopus served as the primary data source due to its superior coverage of construction-specific journals in project management and construction IT, with its frequent update cycles and robust indexing of conference proceedings particularly valuable for capturing emerging trends in the rapidly evolving BIM domain.

3.9. Thematic Analysis

The thematic analysis followed a rigorous, theory-driven approach anchored in organizational learning mechanisms. As this review synthesized qualitative evidence using thematic analysis, no statistical effect measures (e.g., risk ratios or mean differences) were applicable. Using Zollo and Winter [24] framework of experience accumulation, knowledge articulation, and knowledge codification as the theoretical foundation, we developed a structured coding protocol to systematically analyze BIM’s impact on organizational learning. Pre-defined coding categories were established to map BIM functionalities and implementations to these three learning mechanisms. For experience accumulation, we coded instances where BIM facilitated practice-based learning, trial-and-error experimentation, and operational routine development. Knowledge articulation coding focused on how BIM enabled the externalization of tacit knowledge through collaborative practices, stakeholder interactions, and knowledge sharing processes. For knowledge codification, we identified patterns in how BIM supported the systematic documentation, storage, and retrieval of project knowledge.

The authors independently conducted the coding process using NVivo software version 15, following Saldana [50] guidelines for ensuring interpretive convergence and analytical rigor. The coding process followed a two-cycle approach based on Saldana’s methodology. In the first cycle, coding focused on identifying and summarizing descriptive information related to BIM’s impact on organizational learning mechanisms. This initial phase involved applying predetermined theoretical codes derived from [24] Zollo and Winter’s (2002) framework of experience accumulation, knowledge articulation, and knowledge codification. Two researchers independently evaluated the primary studies, coding relevant text segments that aligned with these theoretical constructs.

In the second cycle, the initial codes were systematically refined and reorganized into a smaller number of nodes to define sub-themes and themes based on similarity in descriptions and theoretical relevance. This phase was instrumental in understanding how BIM contributes to organizational learning mechanisms (RQ1) and identifying limitations in current applications of BIM to knowledge creation, sharing, and codification processes (RQ2). Four examples of this two-step coding process are shown in

Table 1. Examples of two-step coding process.

Extracted from Literature	Initial Coding	Sub-Themes	Themes (Final Coding)	Reference
“With the help of BIM, designers can foresee and envisage the likely errors in design and subsequently adjust the designs early in order to reduce the possibility of project failure.”	BIM supports decision-making in the early stage of a project	Early decision making in a project	Enhanced Decision-making	Oduyemi and Okoroh [51]
“One means of using BIM to improve decision making in building design is simply to reduce the amount of work involved in evaluating multiple options early in the design process.”	BIM improves decision-making at the beginning of the design process	Early decision making in a project		Bank, et al. [52]
“As shown inFigure 8, the interactive environment provides a visualization of the space similar to the physical world while providing a more realistic impression than a two-dimensional computer screen of how the finishing material collocation plans.”	BIM visualization provides a more realistic impression of the finishing materials	Better understanding of project processes (i.e., improved comprehensibility)	Agility of Thinking and Reasoning Skills	Balali, et al. [53]
“The results indicate that the development of such models supports a better understanding of the retrofit process on site.”	BIM visualization provides a better understanding of project activities and processes	Better understanding of project processes (i.e., improved comprehensibility)		Justin, et al. [54]

.

3.10. Thematic Saturation

Inter-coder reliability was established through regular comparison and discussion of coding decisions, with discrepancies resolved through team deliberation. This systematic approach enabled the identification of specific BIM functionalities and practices that support different aspects of organizational learning in the AEC-FM context, while revealing thematic trends and gaps within the existing body of research. Thematic saturation was reached when no new themes emerged during the continued review of sources, indicating that the identified themes were comprehensive and non-redundant.

4. Results

4.1. The Results of the Bibliometric Analysis

Academic sources including journal articles, book chapters and conference papers were extracted from the Scopus database using the keyword search strategy explained earlier. In total, 104 academic sources were used in the SLR process. Figure 2 shows the publication years of the studies published between 2009 and 2025.

As depicted in Figure 2, there is a consistent rise in publications from 2009 to 2019, with a significant surge during the 2017–2019 period. This surge may align with major advancements in BIM and the extensive focus on its increasing maturity in construction between 2009 and 2019. This trend highlights the increasing recognition of BIM’s importance in enhancing business processes. Primary studies have been compiled from conference papers, Journal articles, and book chapters accessed from Scopus database. The distribution of academic sources based on publication types is shown in

Table 2. The distribution of academic sources.

Type of Document	No.
Journal Article	77
Conference paper	25
Book Chapter	2

. Among the conference proceedings, the following were the most common: ISARC–Proceedings of the International Symposium on Automation and Robotics in Construction, Construction Research Congress, and Computer Applications–Selected Papers from the Construction Research Congress.

Among the journals where the selected articles appeared are “Automation in Construction”, “Advanced Engineering Informatics”, and “Journal of Construction Engineering and Management” with 15%, 5% and 5% of total publications, respectively.

Table 3. Top 5 journals within the database.

Journal Title	Relevant Published Articles	% of Total Publications
Automation in Construction	16	15%
Advanced Engineering Informatics	5	5%
Journal of Construction Engineering and Management	5	5%
Journal of Management in Engineering	3	3%
Journal of Information Technology in Construction	3	3%

shows the top 5 journals within the database. All studies were sorted based on 29 areas of focus, with 15% related to “Built Heritage” and 13% related to “Maintenance and Facilities Management” articles as shown in Figure 3.

After quality assessment of articles, VOSviewer (version 1.6.20) was used to construct co-occurrence networks of terms extracted from literature. The title and abstract of 104 articles were imported into VOSviewer. Figure 4 shows visualization structural network of the 32 most repeated terms in VOSviewer extracted from 104 articles. The minimum number of occurrences was set to 10. VOSviewer grouped these 32 most repeated terms into three clusters based on association strength: Cluster 1 encompasses the terms: Approach, construction, construction industry, data, domain, information, management, ontology, research, rule, stakeholder, use; Cluster 2 encompasses the terms: BIM environment, case study, challenge, information modelling, integration, knowledge, knowledge management, system, technology, tool; Cluster 3 encompasses the terms: BIM, building information modelling, collaboration, construction project, decision, decision-making, framework, process, project. These co-occurrence networks of terms were investigated in depth during the thematic analysis (

Table 4. Summary of the clusters in VOSviewer.

Cluster ID	Top Terms	No. of Items in Each Cluster
1	Approach; construction; construction industry; data; domain; information; management; ontology; research; rule; stakeholder; use;	12
2	BIM environment; case study; challenge; information modelling; integration; knowledge; knowledge management; system; technology; tool;	10
3	Analysis; BIM; building information modelling; collaboration; construction project; decision; decision-making; framework; process; project;	10

).

In Figure 4, size of the nodes shows the most repeated terms, and the link thickness and length indicate the degree of relationship strength between terms. As presented in Figure 4, the three clusters discussed above are highlighted in different colors:

Cluster 1 in red, focusing on ontology, information, data management:

This cluster represents foundation aspects of BIM research, where the primary focus was establishing BIM models as an information-centric model. Studies within this cluster focus on defining information structures, rule-based BIM models and ontologies to enable consistent data storage, exchanges and interoperability across construction domains. The prominence of terms such as ontology and domain indicates an emphasis on knowledge codification.

Cluster 2 in green, knowledge, knowledge management, integration, system, tool:

In cluster 2, the co-occurrence of terms such as knowledge, knowledge management, integration, and system indicate a shift in BIM research from a focus on data representation toward supporting information reuse, improved coordination, and the development of organizational memory. This cluster treats knowledge as an artefact to be stored and shared through BIM platforms, reinforcing a knowledge management paradigm.

Cluster 3 in blue, BIM, process, collaboration, decision-making, decision, project:

In cluster 3, “BIM”, “process”, and “knowledge” terms dominated the structural network with total link strengths of 742, 553, and 552, respectively. The terms associated with BIM that had the strongest link strength encompass “process” with link strength of 48, “project” with link strength of 41, “knowledge” with link strength of 46, “approach” with link strength of 45, “information” with link strength of 43, “project” with link strength of 40, and “system” with link strength of 39. Cluster 3 reflects a more practice-oriented direction in BIM research, emphasizing collaboration, decision-making, and project processes. BIM is no longer viewed solely as a data repository or knowledge system, but as an enabler of collective action, coordination, and decision support across project stakeholders. The prominence of decision-making, process, and collaboration indicates an emerging shift toward understanding how BIM influences organizational practices and project outcomes. This cluster focuses more on the behavioral and organizational dimensions, particularly through improved collaboration and decision quality.

The evolution of the research paradigm, as revealed through analyses conducted in VOSviewer (Figure 5), indicated a clear thematic progression over time. Early studies around 2017 concentrated primarily on Building Information Modelling (BIM) as a standalone focus. Subsequent work began to integrate BIM with knowledge management, reflecting a growing interest in leveraging BIM for organizational learning and knowledge management. By 2020–2021, the research landscape had further advanced toward the convergence of BIM with ontology development and semantic web technologies, signaling a shift toward more sophisticated, interoperable, and machine-readable knowledge frameworks within the built-environment domain.

4.2. Thematic Analysis

The aim of the thematic analysis of SLR was to extract the potential of BIM in fostering AEC-FM organizational learning capabilities. The results of the visualization structural network in VOSviewer were considered by the researchers during the thematic analysis. The VOSviewer results identified some correlations and degrees of strength between most repeated terms. The results of thematic coding identified seven themes and sixteen sub-themes of BIM which are expected to have positive impacts on learning mechanisms. All these themes extracted from literature review are discussed in the following sections (

Table 5. Sub-themes and final codes extracted from literature review.

No.	Themes	Sub-Themes	No. of Articles	Relevant Organizational Learning Mechanism
1	Agility of Thinking and Reasoning Skills	Better understanding of the complexities of project processes (i.e., improved comprehensibility)	10	Experience Accumulation
		Creative problem-solving	24
		Increased accuracy of information processing	9
2	Enhanced Decision-Making	Reliable and informed decision-making	19
		Early decision-making in a project	10
3	Integrated Business Processes	Interdisciplinary use of BIM	10	Knowledge Articulation
		Simultaneous execution of project activities	7
4	Interconnected stakeholders’ relationships	Coordinated problem-solving	13
		Early involvement of AEC-FM stakeholders in the project	3
		Enhanced AEC-FM stakeholders communication and collaboration for knowledge sharing	12
5	BIM-facilitated Project Knowledge Retention	Codification and definition of mandatory requirements, terms, manuals, specifications, and rules to perform a task	40	Knowledge Codification
		The definition and collection of heritage knowledge	12
6	BIM-facilitated project knowledge sharing	Transferring project knowledge and lessons learned among project stakeholders in a project	20
		Classifying and Transferring Project knowledge, information, and lessons learned for future use in a new project	5
7	BIM-supported project knowledge extraction	Compliance review and evaluation	14
		Visualization and extraction of knowledge	46

).

4.2.1. Theme 1—Agility of Thinking and Reasoning Skills

Sub-Themes Identified

The thematic coding revealed that agility of thinking and reasoning skills contributes to experience accumulation through three key nodes. The sub-themes were reviewed, and irrelevant references were removed from each code under the corresponding main theme:

▪

Better understanding of project processes;

▪

Creative problem-solving;

▪

Increased accuracy of information processing.

Strategic Impacts of Agility of Thinking on Experience Accumulation Dimension:

BIM functionalities such as simulation and parametric modelling enhance problem-solving capabilities and deepen the understanding of complex project processes within AEC-FM firms by offering a visual representation of project data. BIM tools and systems deliver significant project data such as cost and schedule data that aid in forecasting and improving problem-solving skills. BIM visualization allows engineers, designers, and contractors to see the entire project scope within a single BIM model, enabling them to solve project complex issues, track progress and identify any delays. In this regard, Hanna, et al. [55] observed 70% reduction in field conflicts by visualizing the spatial relationships between electrical and mechanical components in BIM. Visualization and simulation tools in BIM provide a structured environment for collective reflection by enabling project participants to explore potential consequences of design and construction decisions prior to physical execution. BIM representations embed spatial relationships and the locational attributes of building components, thereby facilitating multiple forms of analytical exploration and comparison among alternatives. From an organizational leaning perspective, simulation-based representations/BIM models function as interpretive artifacts that support reflective sensemaking during recurrent project interactions (e.g., BIM coordination meeting and design reviews) among AEC-FM professionals. Consistent with organizational learning literature, it is through these socially mediated reflective practices rather than through the replication of embodied experience that learning becomes stabilized at the organizational level [56]. In this context, BIM visualization acts as learning artifacts that facilitate reflection on action, supporting the rapid evaluation of alternatives and what-if scenarios in project environment. Therefore, learning occurs through the iterative interpretation of visual representation in relation to project outcomes. In this sense, BIM enabled visualization contributes to experience accumulation by enabling vicarious learning which complement on-site experiences [57]. The use of BIM in daily business tasks also increases the precision of information processing. Project stakeholders are able to perform their daily tasks with higher accuracy in a BIM environment compared to traditional 2D drawings. Use of BIM in daily business tasks also increases the precision of information processing. All these attributes gained from using BIM will empower AEC-FM businesses to think more critically and tackle design and construction challenges with greater confidence and creativity, leading to more agile thinking [58]. Agile thinking, also known as mental agility, is one of the key dimensions of learning agility. Learning agility is defined as “the ability to learn from experience, with a subsequent application of the learned skills for successful performance in new or first situations” [59]. According to the literature, experience accumulation refers to the learning mechanisms through which operational routines are developed [24]. These operational routines are the result of iterative processes, where knowledge accumulation and expertise are built over time through practice-based learning and problem-solving activities within a specific domain [60]. The advancement of problem-solving skills and a better understanding of project processes collectively contribute to the learning agility of AEC-FM organizations, enabling them to assimilate new experiences and apply acquired insights in innovative contexts, thereby fostering the development of new operational routines [61].

4.2.2. Theme 2—Enhanced Decision-Making

Sub-Themes Identified

Another important BIM learning mechanism that positively influences the experience accumulation dimension is enhanced decision-making. BIM supports experience accumulation through two decision-making mechanisms:

▪

Reliable and informed decision-making;

▪

Facilitation of early decision-making.

Strategic Impacts of Enhanced Decision-Making on Experience Accumulation Dimension:

A firm’s innovation knowledge accumulates through learning-by-doing activities such as trial-and-error experiments [24,62]. One clear advantage of trial-and-error experiments is that they allow for learning from failures, leading to more confident decision-making. Trial-and-error experiments help AEC-FM businesses investigate the reasons for unsuccessful attempts, like design failures, and acquire valuable insights to improve their decision-making process. In other words, by examining each experiment, organizations can develop a better understanding of their capabilities and subsequently use this knowledge to make more informed decisions about their future initiatives.

BIM enables trial-and-error experiments to solve project-related issues by evaluating different scenarios until the desirable solution is achieved [63]. The application of BIM at the beginning of a project enables AEC-FM organizations to perform a variety of trial-and-error experiments (i.e., what-if scenario analysis) to solve design-related issues. This function of BIM enables AEC-FM organizations to employ trial-and-error/what-if analyses at the project’s outset to enhance the decision-making capabilities of AEC-FM firms. For instance, Bank, Thompson and McCarthy [52] utilized a BIM-based decision-making platform to transfer sustainability data between a BIM model and system dynamic tool to facilitate sustainability decision early in their project.

Trial-and-error is not very feasible in traditional design and construction workflows; therefore, if a potential issue is overlooked during the design phase, it may turn out to be costly to be fixed in the construction phase. However, BIM can facilitate early decision-making in a project by simplifying the process of evaluating multiple what-if scenarios [64,65]. Trial-and-error experiments can be applied in BIM environment by modifying the original design and analyzing the effects on project performance such as cost and time of the overall project. Project simulation in BIM environment supports AEC professionals to solve project-related challenges independently and make reliable decisions. In this regard, by simulating different retrofit options in BIM, Tzortzopoulos, et al. [66] investigated how BIM simulation can support decision-making in choosing retrofit solutions for social housing based on client’s needs. They observed that by using BIM, the construction client was able to make informed decisions regarding the retrofit options for social housing. In another example, Wu, et al. [67] used BIM 4D visualization as a basis of their real-time visual warning system to plan for hazard prevention on the construction site. In their project, digital twins (DT), mixed reality (MR), and deep learning (DL) platforms were integrated with BIM to provide project teams with hazard information.

The ability to make reliable decisions early is a hallmark of effective decision making. This ability is instrumental in identifying risks, bottlenecks, and opportunities within organizational contexts. In other words, being able to make informed decisions serves as a driving force for enhancing operational efficiency. As a result, AEC-FM organizations are better equipped to foster innovation and address similar challenges in future projects.

4.2.3. Theme 3—Integrated Business Processes

Sub-Themes Identified

Knowledge articulation across partner organizations is strengthened through Integrated Business Processes, a major transformation driven by BIM adoption. This theme is supported by two key mechanisms:

▪

Interdisciplinary use of BIM;

▪

Simultaneous execution of project activities.

Strategic Impacts of Integrated Business Processes on Knowledge Articulation Dimension:

Collaboration and inter-organizational interactions are essential elements to foster knowledge articulation [68]. “The interdisciplinary use of BIM” across various disciplines integrates business processes within the construction industry. A BIM model can be exchanged between different computer programs, enabling system integration, as well as between various disciplines involved in a project, fostering business process integration [69]. Project teams from different disciplines are able to work on a single BIM model, ensuring the smooth integration of architectural, engineering and MEP designs. As a result of this integration, AEC-FM organizations are better able to collaborate and exchange knowledge through BIM models with external partners regarding feasibility, constructability, availability of project resources etc. Within an integrated environment, the likelihood of learning occurring is higher compared to a discrete project environment. By integrating processes, AEC-FM stakeholders can check interferences between disciplines such as between the structural elements and the mechanical, electrical, plumbing (MEP) systems. In this context, through 16 interviews with managers and engineers, Jaradat, et al. [70] observed that service engineers used digital technologies to integrate engineering details into an architect’s model, avoiding the need to start designing from scratch. Ho and Hou [71] social network-enabled BIM platform to improve knowledge sharing and collaboration across different sectors. This approach highlights the social dimension of BIM. BIM, as a socio-technical platform, reorients focus from solely technical capabilities to the human dynamics within project environments. Its social dimension underscores how AEC-FM stakeholders interact, collaborate, and coordinate their efforts throughout the construction process. Rather than viewing BIM merely as a tool for tasks like modeling or clash detection, this perspective highlights its role in shaping organizational behavior and communication. In the construction sector, BIM fosters deeper collaboration and enhances clarity in communication. By integrating both technological and social elements, BIM supports more cohesive and responsive project delivery. The review of the literature identified several examples of BIM’s social dimension, including coordination meetings, BIM-enabled knot working sessions, and BIM-based concurrent engineering (CE) practices. For instance, in a public sector construction project, A. Kuprenas [72] found that BIM coordination meetings allowed sub-contractors to exchange their experience with each other and proactively resolve conflict at an early stage in the project. They observed less requests for information (RFI) and changed orders throughout the project. Use of BIM in design meetings encourages collaborative engagement of AEC-FM experts by providing seamless access to a shared interactive model. This streamlined approach incorporates diverse disciplinary inputs, thus reducing misinterpretation of project information. Oduyemi and Okoroh [51] realized the importance of a unified BIM model for a sustainable design which requires the contractor to initially collaborate with the designer and other project teams to create such a unified model.

The interdisciplinary use of BIM allows “the simultaneous execution of project activities” in construction projects. This approach is known as CE and is often used to enhance efficiency and promote collaboration among different teams. Quiso, et al. [73] deployed BIM-based CE sessions and observed that as a result of the CE and BIM sessions, engineers–construction masters–foremen were able to transmit information more smoothly. CE sessions that utilized BIM as a collaboration tool enhanced the understanding of essential tasks required for efficient project delivery among construction supervisors, such as foremen and construction masters. These sessions leverage BIM models and incorporated input from various specialists.

4.2.4. Theme 4—Interconnected Stakeholders Relationships

Sub-Themes Identified

BIM strengthens knowledge articulation by transforming stakeholder relationships through three mechanisms:

▪

Coordinated problem-solving;

▪

Enhanced communication;

▪

Early stakeholder involvement.

Evidence from Literature

▪

A total of 13 studies highlighted coordinated problem-solving enabled by BIM-centric collaboration.

▪

A total of 3 studies emphasized the early involvement of AEC-FM stakeholders in BIM-enabled projects, contrasting with traditional sequential processes.

▪

A total of 12 studies discussed improved communication and collaboration for knowledge sharing among project stakeholders.

Strategic Impacts of Interconnected Stakeholders Relationships on Knowledge Articulation Dimension:

In BIM projects, it is imperative that project stakeholders engage in collaborative efforts to address complex design and construction challenges [74]. With BIM-centric mechanisms such as 3D coordination meetings, AEC-FM businesses can collaborate on project-specific challenges. Previous studies have shown that BIM is a highly effective means of communication in 3D design coordination meetings [72,75]. During BIM coordination meetings and seminars, there exists the opportunity for the articulation of AEC-FM knowledge. An instance of this is to solve project complex issues collaboratively. For instance, in an infrastructure construction project, Gächter, et al. [76] used BIM 360 as the coordination tool and found that 3D coordination meetings led to proactive integrated solution management at the interface between disciplines, resulting in greater design quality.

BIM also requires early engagement of AEC-FM stakeholders in a project to define quality objectives collaboratively. Early engagement of AEC-FM stakeholders in the project strengthens AEC-FM relationships. From the beginning of the project, stakeholders are connected early on, facilitating knowledge articulation. One example of this early engagement was observed in a healthcare facility, where BIM adoption during the conceptual stage required project team members to collaborate with other stakeholders throughout the project’s lifecycle using BIM methods [77]. Given that interorganizational interaction plays a crucial role in knowledge sharing among organizations and across geographical boundaries [78], it is evident that heightened interaction among AEC-FM professionals involved in BIM projects fosters the articulation of knowledge.

4.2.5. Theme 5—BIM-Facilitated Project Knowledge Retention

Sub-Themes Identified

Thematic analysis identified two primary ways BIM supports the capture of project knowledge:

▪

Codification of mandatory requirements, manuals, specifications, and rules (Reported in 40 studies): BIM tools and databases store essential project guidelines and regulatory information, enabling rule-checking and supporting inspection tasks during construction and operation.

▪

Definition and collection of heritage information (Recognized in 12 studies): BIM facilitates the structured capture of heritage-related data for conservation, renovation, and long-term asset management.

Strategic Impacts of BIM-facilitated Project Knowledge Retention on Knowledge Codification Dimension:

As previously mentioned, when a project is rapidly terminated, its resources are quickly reassigned to new projects, leaving little opportunity to reflect on past failures, particularly in paper-based communication. Consequently, valuable information and project knowledge may be lost if not promptly captured by the teams involved. Nowadays, BIM supports AEC-FM businesses by offering the ability to store crucial project knowledge, such as historical information in built heritage projects (known as HBIM), or project guidelines, issues, and regulations in new design and construction projects. With respect to knowledge retention, HBIM structures heritage-related information and refurbished building components through object-oriented approach supported by standardized classification codes and parameters. Learning emerges through repeated enactment in everyday business practice. In heritage projects, FM teams repeatedly engage with BIM models during refurbishment and maintenance activities. Through iterative cycles of model consultation, on-site execution, and post-intervention evaluation, team members begin to recognize recurring patterns regarding heritage constraints, feasible solutions, and effective decision heuristics. Over time, this recurrent interaction reshapes how FM organizations collect, interpret, and apply heritage information using BIM (i.e., compared to traditional approach), leading to the stabilization of modified routines and decision-making practices.

A similar mechanism is observed in new construction projects, where safety regulations and requirements are embedded within BIM-based ontological frameworks. These codified rules do not function solely as static repositories of safety information; instead, they are operationalized through visualization-supported risk identification, cross-trade coordination, and on-site problem-solving. Through repeated exposure and application in everyday construction activities, safety knowledge becomes embedded in habitual work practices and shared expectations among project participants. Consistent with organizational learning literature, it is this process of enactment and routinization, rather than the mere storage of information, that enables knowledge to be retained and sustained at the organizational level. This structured approach facilitates the definition, dissemination, and practical application of safety knowledge, supporting its retention and continuous use throughout the construction process.

BIM enables the capture and codification of project knowledge into easily understandable and actionable codes. AEC-FM can easily refer to the BIM system to find relevant rules, changes, or solutions without heavily relying on paper documents. The knowledge codification dimension of organizational learning refers to the process of storing and codifying knowledge in a structured manner, enabling easy access and sharing. Therefore, the key requirements of knowledge codification are knowledge storage, transfer, and extraction. In this section, we discussed how BIM facilitates knowledge capture. The subsequent themes will explore BIM-facilitated project knowledge sharing and BIM-supported knowledge extraction.

4.2.6. Theme 6—BIM-Facilitated Project Knowledge Sharing

Sub-Themes Identified

Two main scenarios of knowledge transfer were identified:

▪

Transfer within an ongoing project among active stakeholders (Highlighted in 20 studies);

▪

Transfer for use in future projects (Mentioned in 5 studies).

Strategic Impacts of BIM-facilitated project knowledge sharing on Knowledge Codification Dimension:

BIM facilitates project knowledge transfer by “Converting project information into other file formats,” allowing each project participant to open, read, edit, and update specific project knowledge [79]. This potential became the main method for exchanging project knowledge using BIM tools among stakeholders in an ongoing project or for application in future projects. “Cloud-based technologies” was the second approach to transfer project knowledge specified between project stakeholders in an ongoing project. Compared to the paper-based commoditization in traditional design and construction processes, BIM systems have streamlined knowledge transfer between project teams more efficiently. This capability of BIM has led to enhanced productivity in AEC-FM companies, as it reduces the time required to send and receive project documents, instructions, standards, revised drawings, and more.

4.2.7. Theme 7—BIM-Supported Project Knowledge Extraction

Sub-Themes Identified

BIM-based platforms enable AEC-FM organizations to extract project knowledge through two key capabilities:

▪

Compliance review and evaluation

▪

Visualization and extraction of domain-specific knowledge

Strategic Impacts of BIM-supported Project Knowledge Extraction on Knowledge Codification Dimension:

The third aspect of knowledge codification dimension in organizational learning literature is the ability to retrieve knowledge for future use. In a new project, teams can access all defined instructions, rules, and standards within a BIM model for compliance review and evaluation. This capability of BIM has automated the inspection and knowledge retrieval process. The visualization features of BIM tools aid in the retrieval and rule-checking process. AEC-FM businesses simply need to compare their BIM models against the coded rules or guidelines to identify any non-conformance issues in their project.

The second approach discussed in the literature concerning knowledge retrieval involves extracting project knowledge through the use of BIM systems, such as instructions, historical information, and standards on how problems were resolved in previous projects. Project stakeholders can refer to a BIM model to find the solutions they previously defined, helping them understand how similar problems were addressed in past projects [41]. Knowledge retrieval via BIM tools benefits AEC-FM organizations by enhancing the consistency and accuracy of information from digital models, boosting construction efficiency and productivity through quicker and easier access to construction data, and aiding decision-making tasks related to purchasing and method selection [80].

5. Discussion

This study advances BIM literature by exploring how BIM can facilitate organizational learning mechanisms within the AEC-FM sector. The results of the thematic analysis show that the learning capacities of BIM lead to considerable learning success within AEC-FM companies, helping them stay competitive in a volatile market. AEC-FM companies can leverage BIM-enabled learning mechanisms to generate more innovative outputs and maintain their business relationships with potential clients. These achievements can be credited to a reduction in errors and better decision-making, due to the lessons learned from utilizing BIM in their projects.

5.1. Theoretical Contributions

This study contributes to BIM literature by highlighting previously overlooked capacities of BIM that influence organizational learning. The findings reveal that the disproportionate focus on technical aspects of BIM implementation limits our understanding of its broader organizational learning impacts, particularly in areas such as tacit knowledge exchange and inter-organizational learning dynamics within the AEC-FM sector. By introducing BIM-enabled organizational learning factors, this study expands the theoretical scope in BIM field to encompass a broader range of influences on AEC-FM organizations performance. Figure 6 summarizes BIM-enabled organizational learning factors and their relationships with organizational learning mechanisms.

The thematic analysis of the literature review identified seven BIM-enabled organizational learning factors that facilitate learning processes within organizations. These include: “agility of thinking and reasoning skills”, “enhanced-decision-making”, “integrated business processes”, “interconnected stakeholders’ relationships”, “BIM-facilitated project knowledge sharing”, “BIM-supported project knowledge retention”, and “BIM-supported project knowledge extraction”. These capacities were evaluated for the first time in the literature in relation to three learning mechanisms, namely, experience accumulation, knowledge articulation, and knowledge codification, thereby contextualizing BIM’s technical features within the broader dimensions of organizational learning. The study finds that BIM-enabled agility of thinking can transform organizational learning from a slow process of knowledge integration into a fast and iterative process [81]. According to Zollo and Winter [24] framework on organizational learning mechanisms, experience accumulates through the gradual formation of routines through repeated practice. However, with the use of BIM, this process is accelerated and becomes more agile. This means that learning cycles become shorter and highly interactive, instead of routines emerging slowly over time. This shift suggests that digitalization, through BIM, has the potential to fundamentally reshape how AEC-FM organizations refine and evolve their operational practices [82]. In this regard, McGraw Hill’s research in Australia indicates a strong level of BIM adoption, particularly among contractors who prioritize collaborative workflows and data integration [83]. According to this report, most of the architecture, engineering, and contracting firms that participated in the study reported a strong positive Return on Investment (ROI) resulting from the adoption of BIM. Therefore, it can be proposed that:

“The agility of thinking fostered by BIM can transform organizational learning toward iterative processes, extending Zollo and Winters’s concept of dynamic capabilities.”

Also, being able to make reliable decisions early in a project environment is a key enabler of experience accumulation, as this capacity allows AEC-FM organizations to identify risks and opportunities early. Reliable decision-making is achieved through rich-data BIM models, which provide AEC-FM organizations with the ability to analyze project outcomes by accessing the diverse information stored in the BIM model, often referred to as the project repository [84,85]. Reliable decision making allows organizations to filter useful experiences for their businesses, resulting in reduced uncertainty and innovative outcomes [86]. Using BIM features such as what-if scenario analysis, visualization, and the simulation of project processes strengthens early decision-making, which supports AEC-FM organizations in learning from operational routines and fostering innovation. The ability to make decisions early in a project informs future learning. For example, early understanding and decisions about project time, risks, and resources help AEC-FM organizations better apply their lessons learned [87]. This suggests that improving the quality of decision-making, along with repeating routines, can enhance the accumulation of experience. These findings indicate that, in addition to repetition:

“The ability to make reliable decisions can significantly impact innovation within AEC-FM organizations, thereby enhancing their capacity for experience accumulation.”

In BIM projects, stakeholders’ interactions combined with integrated business processes foster cross-boundary learning environments [11]. In this learning environment, AEC-FM businesses are better able to articulate, share and interpret knowledge across internal teams and external partners. This dynamic supports Zolo and Winter’s framework, which posits that knowledge articulation primarily occurs among colleagues and industry peers. By using BIM as a socio-technical platform, AEC-FM organizations can strengthen collaborative problem-solving and accelerate collective learning. Social dimension of BIM shifts attention away from purely technical functions toward the people involved and how they interact/work together in a project environment. It highlights the broader societal effects of BIM in the construction sector, emphasizing stronger collaboration, clearer communication, and improved satisfaction among AEC-FM stakeholders. The social side of BIM reshapes how communication flows both inside individual organizations and across organizational boundaries. It influences key elements of social capital within project teams such as the formal structure of interactions and the shared understanding that guide stakeholders’ relationships. These shifts play a vital role in supporting organizational learning. Therefore, the following can be proposed:

“Interconnected stakeholder relationships and integrated business processes in BIM projects facilitate the assimilation of knowledge among AEC-FM organizations.”

Zollo and Winter [24] concept of knowledge codification, where tacit knowledge is formalized into explicit formats such as manuals, guidelines, and databases, BIM enables the systematic codification of project requirements, data, specifications, and heritage information through integrated tools and structured data environments. BIM supports project knowledge transfer by enabling information to be converted into various file formats, allowing participants to access, edit, and update relevant data. Alongside cloud-based technologies, this approach has become a primary means of sharing knowledge among stakeholders during ongoing projects and for future applications. Compared to traditional paper-based processes, BIM streamlines the exchange of documents, instructions, standards, and drawings, during design and constructability reviews, enhancing efficiency and productivity across AEC-FM organizations. These capabilities allow project tacit knowledge such as solved problems and insights of project participants to be captured, formalized, and stored in explicit formats like structured models, manuals, and digital records. Therefore,

“By converting informal, experience-based understanding into accessible, standardized documentation, BIM ensures that valuable knowledge is preserved beyond individual team members and can be reused consistently across projects.”

This transformation of tacit into explicit knowledge in construction projects, enabled by BIM, not only aligns with Zollo and Winter’s concept of knowledge codification but also strengthens organizational learning by making knowledge transferable and applicable to future contexts.

The introduction of the identified propositions signifies a clear gap in the literature to examine how digitally mediated learning influence organizational learning mechanisms, and how such insights can inform the refinement of learning theories. While these findings help identify the lack of in-depth studies on the role of digital transformation in reshaping organizational learning mechanisms, especially in the construction industry, it provides a foundation for future research. It is recommended that future studies use these propositions as a basis to design a theoretical model for investigating the impact of digitalization on the evolution of organizational learning theories.

5.2. Practical Implications

The findings of this study provide significant practical implications for AEC-FM organizations seeking to leverage BIM for organizational learning. Our analysis demonstrates that BIM transcends its technological role through its dynamic impact on organizational performance [37], offering three key pathways for enhancing organizational learning through experience accumulation, knowledge articulation, and knowledge codification.

In terms of experience accumulation, BIM’s technical capabilities facilitate practice-based learning through visualization and scenario analysis. AEC-FM organizations can implement structured learning programs that leverage BIM’s simulation and parametric modelling capabilities to improve problem-solving and understanding of complex design and construction processes. Our analysis of 30 studies revealed that BIM tools provide crucial support for R&D activities, enabling teams to view entire project scopes, track progress, manage job-site safety, and identify delays through enhanced visualization. To maximize these benefits, organizations should establish dedicated roles for coordinating BIM-enabled decision-making processes and develop metrics to track how these tools enhance learning agility and problem-solving capabilities.

Knowledge articulation can be strengthened through five identified BIM-centric mechanisms: ‘social network-enabled platforms’, ‘knot working sessions’, ’coordination meetings’, ‘CE sessions’, and ‘knowledge-sharing seminars’. These mechanisms are particularly crucial in large-scale projects where interdisciplinary BIM models help reduce fragmentation by enhancing cross-disciplinary communication. These mechanisms also reflect the social dimension of BIM, reinforcing integration, supporting knowledge articulation, and strengthening collaboration among project-based organizations. AEC–FM organizations should actively embrace this social dimension by establishing regular knowledge-sharing sessions and clear protocols for collaborative problem-solving within BIM’s socio-technical environment. This approach ensures that expertise/knowledge is effectively transferred among AEC-FM members and across projects, fostering continuous learning and organizational improvement.

For knowledge codification, our analysis of 63 papers revealed that BIM offers robust mechanisms for capturing and preserving project knowledge. AEC-FM organizations should implement standardized frameworks for documenting construction rules, safety requirements, and project specifications through BIM systems. Integration with complementary technologies, such as database management systems and ontology-based platforms, can further enhance knowledge capture and retrieval capabilities. The results also highlight a predominant focus on explicit knowledge codification in BIM research, reflecting a broader tendency for studies to prioritize technical aspects over other dimensions of BIM. For example, only a limited number of studies addressed the business value of BIM, with three papers highlighting early involvement of AEC–FM stakeholders through 3D design and coordination meetings, and five papers examining the transfer of project knowledge for future use. While the evidence base for these sub-themes is relatively small, their recurrence across independent studies suggests emerging areas of interest that warrant further empirical investigation. Particular attention should be paid to establishing clear processes for knowledge transfer during project handover phases, ensuring that valuable insights are not lost during project transitions.

The findings of this research provide valuable insights for industry leaders developing BIM standards and policies, highlighting the need to integrate organizational learning dimensions into existing frameworks. Standards developers and policymakers can enhance current BIM guidelines by incorporating specific provisions for organizational learning mechanisms. The BIM-enabled organizational learning factors introduced in this paper, along with the conceptual model, help organizations understand and assess how BIM fosters and influences their learning processes in BIM projects. By systematically applying these insights, AEC-FM businesses can better understand how BIM influences knowledge acquisition, sharing, and integration across project stakeholders, ultimately strengthening their organizational learning capabilities. This research particularly emphasizes the importance of including organizational learning capabilities in BIM maturity assessment tools and standards, moving beyond technical competencies to evaluate how effectively organizations leverage BIM for knowledge management. Such enhanced standards would encourage AEC-FM firms to maximize BIM’s potential as a catalyst for organizational learning while providing clear metrics for assessing learning outcomes. However, successful implementation requires sustained commitment from both organizational leadership and industry stakeholders to foster an environment that prioritizes and rewards knowledge sharing through BIM-enabled platforms, supported by appropriate governance structures and incentive mechanisms.

The findings of this study reveal that BIM can offer considerable potential to support organizational learning. However, its effects are not uniformly positive. Over-reliance on BIM tools may reduce opportunities for developing professional judgement, and highly standardized BIM-enabled processes may limit exploratory forms of learning. Although BIM can facilitate organizational learning, excessive dependence on digital representation may weaken AEC-FM engineers’ intuitive judgement.

6. Limitations of the Study and Future Research Directions

While the scope of the paper was conceptual, focusing on developing a framework of BIM-enabled learning factors, it is important to recognize several limitations to accurately interpret the results. First, this paper adopted SLR on the available sources in the literature to develop BIM-enabled organizational learning factors. However, it is acknowledged that the learning capabilities of BIM in business processes can extend beyond the factors discussed and may not be limited to the factors introduced here. Therefore, future research is anticipated to expand upon the findings of this paper regarding the organizational learning capacities of BIM. Second, as SLR relies on published studies, future research will aim to empirically validate the conceptual model and theoretical propositions introduced in this paper by conducting case studies across different BIM-supported projects. The aim of this study was to identify the key learning functions of BIM to support organizational learning in the AEC-FM context, and the authors agree that future research should examine discipline-specific perspectives and cross-level dynamics more specifically for each discipline through empirical investigations to avoid treating learning as a homogenous process. This approach will offer practical insights and help refine the conceptual model for real-world applications. The findings of this paper can be used as a basis for future research to further examine the impact of BIM-enabled learning factors on AEC-FM performance particularly on their organizational learning performance. This review relied exclusively on the Scopus database, which, although comprehensive, may not capture all relevant studies indexed in other major databases such as Web of Science. Future research could strengthen the breadth of evidence by employing a multi-database retrieval strategy.

The SLR shows limited studies on BIM’s practical advantages at the organizational level, with 63 out of 104 articles focusing on BIM’s technical capabilities for project knowledge codification, overlooking its impact on knowledge articulation and stakeholder relationships. Only 22 articles addressed business process changes and stakeholder relationships due to BIM. Within Zollo and Winter’s organizational learning framework, this imbalance suggests that in the existing BIM literature, organizational learning is disproportionately focused on knowledge codification through documentation and data storage. This extra focus on knowledge codification deviates from Zollo and Winter’s view on organizational mechanisms, which considers experience accumulation, knowledge articulation, and codification as three important mechanisms. The findings reflect an emphasis on explicit knowledge codification in BIM literature. This deviation also suggests that most studies focus on the technical aspects of BIM. However, BIM is more than a data tool and is referred as a socio-technical system, where technical features (e.g., data integration, parametric modelling, etc.) are inseparable from organizational social structures, cultures, and behavioral routines [11]. Socio-technical BIM has the potential to integrate cultural, human, and organizational contexts with its technical aspects. This study identified some of the socio-technical features of BIM, such as ‘knot working sessions’, ‘coordination meetings’, and ‘concurrent engineering sessions’, which are supported by the technical features of BIM. Socio-technical BIM-mediated learning can enhance the three mechanisms of organizational learning as discussed in this study [11,88]. These facts also necessitate a refinement of the enabling factors of organizational learning mechanisms to better demonstrate how socio-technical platforms like BIM can reshape learning processes, such as generating hybrid learning environments that are not considered in the definition of organizational learning mechanisms in [24] framework. Therefore, the theory may need to be updated to reflect the impact of socio-technical platforms and show what is truly happening in practice. Future research could investigate the impact of BIM on stakeholders’ relationships by introducing other non-technical mechanisms to facilitate knowledge articulation. It is essential to understand how AEC-FM businesses can optimize their organizational performance, especially in relation to the influence of BIM on their internal business processes and their interactions with partner businesses and customers. This study focused mainly on BIM’s role at the organizational and inter-organizational level, with limited insight into how BIM supports individual and team-based learning. Future research should therefore examine BIM’s social dimensions more explicitly, including how BIM-enabled practices influence learning at the individual and team levels, and how social interactions mediate the effectiveness of BIM as a socio-technical system. Finally, the review process included 25 conference papers, which may not always undergo the same level of peer review scrutiny as journal publications, they were retained due to their relevance to the research topic and their contribution to emerging discussions in the field. It is recommended that the conclusions should be interpreted with this limitation in mind.

7. Conclusions

BIM, as a multidisciplinary collaboration platform, has significantly altered business processes, yet few studies have examined its effects on AEC-FM organizations’ performance, particularly regarding learning capacities. This paper addresses this gap by exploring BIM’s role as a learning platform and its impact on organizational learning mechanisms, extending the theoretical framework of organizational learning by highlighting BIM’s learning potential. Our analysis shows that the existing BIM literature places strong emphasis on explicit knowledge codification, with much of the research centering on BIM’s technical capabilities. This focus overlooks the broader understanding of BIM as a socio-technical system in which technical functionalities such as data integration, visualization, knowledge repository, and parametric modelling are deeply intertwined with organizational structures and everyday work practices.

The study highlights several socio-technical features of BIM in practice, including knot-working sessions, coordination meetings, and concurrent engineering activities, all of which rely on and are enabled by BIM’s technical affordances. These findings demonstrate that socio-technical BIM environments support richer forms of learning by integrating human, cultural, and organizational dimensions with technological processes. As a result, socio-technical BIM-mediated learning has the potential to strengthen organizational learning mechanisms.