A Systematic Review of Lean Construction, BIM and Emerging Technologies Integration: Identifying Key Tools

Abstract

The construction industry, a cornerstone of global economic growth, continues to struggle with entrenched inefficiencies, including low productivity, cost overruns, and fragmented project delivery. Addressing these persistent challenges requires more than incremental improvements, it demands a strategic unification of Lean Construction, Building Information Modeling (BIM), and Emerging Technologies. This systematic review synthesizes evidence from 64 academic studies to identify the most influential tools, techniques, and methodologies across these domains, revealing both their individual strengths and untapped synergies. The analysis highlights widely adopted Lean practices such as the Last Planner System (LPS) and Just-In-Time (JIT); BIM capabilities across 3D, 4D, 5D, 6D, and 7D dimensions; and a spectrum of digital innovations including Digital Twins, AR/VR/MR, AI, IoT, robotics, and blockchain. Crucially, the review demonstrates that despite rapid advancements, integration remains sporadic and unstructured, representing a critical research and industry gap. By moving beyond descriptive mapping, this study establishes an essential foundation for the development of robust, adaptable integration frameworks capable of bridging theory and practice. Such frameworks are urgently needed to optimize efficiency, enhance sustainability, and enable innovation in large-scale and complex construction projects, positioning this work as both a scholarly contribution and a practical roadmap for future research and implementation.

1. Introduction

The construction industry is a crucial sector globally, contributing significantly to economic growth, infrastructure development, and employment generation. It produces a wide range of buildings and civil infrastructure that enhance economic, health, and social well-being [1]. The global construction industry plays a substantial economic role, contributing approximately 13% to global Gross Domestic Product (GDP) and employing over 220 million people worldwide [2]. Rapid urbanization, population growth, and increasing demand for smart and sustainable infrastructure are driving investments in large-scale construction projects worldwide, where governments and private sectors are prioritizing infrastructure development to foster economic diversification, enhance urban livability, and support long-term sustainability goals [3]. Globally, the value of the construction industry is projected to grow at a steady rate, with compound annual growth rate (CAGR) projections ranging between 2.5% to 6% across different regions due to rising demands for infrastructure, housing, and sustainable development solutions [4]. Many countries have set forward looking at initiatives that prioritize construction as a driver for future economic growth [5,6]. Despite its significance, the construction industry continues to grapple with persistent challenges such as low productivity, cost overruns, schedule delays, and quality management issues [7,8]. These inefficiencies have prompted industry leaders to explore innovative solutions for optimizing project delivery and efficiency. One promising approach is the integration of Lean Construction, Building Information Modeling (BIM), and Emerging Technologies. Lean Construction is a philosophy and process-oriented methodology which has a set of tools that focus on eliminating waste, improving workflow reliability, and enhancing project efficiency, which can be particularly beneficial for ambitious projects [9]. Recent research has demonstrated that Lean principles, when applied during the design phase, can significantly reduce construction waste by optimizing material usage and improving workflow coordination [10]. Waste, in this context, includes elements that do not add value to the project, such as waiting, defects, and overproduction. Globally, Lean Construction principles have been implemented across various sectors, from commercial buildings to large-scale infrastructure projects, demonstrating their effectiveness in improving cost efficiency and project performance [11]. For instance, in developed countries like Finland, Lean Construction techniques have been widely implemented to enhance project delivery and resource management across various construction sectors [12]. BIM, on the other hand, is a digital representation of a physical asset, facilitating visualization, analysis, and simulation of the construction process. This digital approach can identify and eliminate potential issues before construction begins, improving communication and collaboration between stakeholders [13,14]. The use of BIM extends beyond 3D modeling, incorporating dimensions such as 4D (time management), 5D (cost estimation), and even 6D (sustainability analysis), making it a powerful tool for project optimization [15,16]. When integrated with Lean Construction principles, BIM enhances project efficiency by providing real-time data analytics, reducing uncertainty, and improving decision-making processes [17]. Recent studies have further emphasized the role of BIM in enhancing project efficiency when integrated with AI and IoT, particularly in prefabricated construction, highlighting its potential to streamline workflows and reduce waste [18]. Emerging Technologies, including big data [19], AI [20], and machine learning [21], are being explored to enhance efficiency, reduce costs, and improve overall quality in projects [22,23]. Despite the growing momentum in optimizing construction processes and toward digital transformation in construction, the absence of a comprehensive framework that fully integrates Lean Construction, BIM, and Emerging Technologies represents a critical impediment to progress. This fragmentation not only limits the ability to harness synergies between process optimization, digital modeling, and advanced automation but also perpetuates inefficiencies, inhibits scalability, and constrains innovation, particularly in complex, large-scale projects where integration is most urgently needed. Without a unified approach, the industry risks continuing with siloed solutions that fall short of delivering transformative improvements in productivity, cost efficiency, and sustainability. Addressing this gap is therefore a pressing scholarly and practical priority, as it directly impacts the capacity of the construction sector to meet the demands of a rapidly evolving built environment [24,25]. This literature review systematically analyzes 64 academic papers to identify the key tools and techniques used within Lean Construction, BIM, and Emerging Technologies. By categorizing and evaluating these tools, this study provides a structured pathway for future research to develop an integrated framework that unifies these domains. The findings of this review serve as a critical foundation for the next phase of research, which focuses on constructing a comprehensive framework that optimizes construction processes particularly in large-scale projects where unique challenges demand tailored solutions. By bridging the gap between theory and practice, this review highlights specific tools, technologies, and performance metrics used in practice which can contribute to the ongoing discourse on digital transformation in construction, offering insights into the synergies that can drive efficiency, productivity, and sustainability in the industry.

2. Research Method and Article Selection Process

2.1. Research Method

In the context of enhancing construction project management through the integration of BIM, Lean, and Emerging Technologies, various applications were identified, along with the level of integration between these domains. To achieve this objective, a three-stage methodology was developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. A completed PRISMA 2020 checklist is included in Appendix A, Figure 1 present the research method, and the updated PRISMA-compliant flow diagram is presented in Figure 2. This structured protocol enhances transparency and reproducibility, aligning with best practices for systematic reviews.

As illustrated in Figure 1, the methodology comprises three interconnected stages adapted from [26].

Stage 1: Bibliometric Analysis

The first stage seeks to understand the interrelation between BIM, Lean Construction, and Emerging Technologies in enhancing construction project management. To achieve this objective, an analysis was conducted using bibliometric data obtained from an extraction protocol adapted from previous studies, focusing on a meta-analysis of existing literature [27]. The bibliometric data was analyzed to identify key research themes, influential authors, frequently cited papers, and evolving trends within the domain. The findings from this stage provided critical insights that informed the selection criteria for the systematic literature review in Stage 2. Specifically, the most cited articles, key thematic clusters, and dominant research gaps identified in the bibliometric analysis were used to refine the inclusion criteria for the systematic review. This ensured that Stage 2 focused on extracting and categorizing techniques that align with the research gaps and emerging trends identified in Stage 1. Thus, the bibliometric analysis serves as a filtering and guiding mechanism for the structured content extraction conducted in the next phase.

Stage 2: Systematic Literature Review

The second stage focuses on identifying the techniques of Lean Construction, BIM, and Emerging Technologies that have been used in their integration to enhance construction project management. A systematic literature review was conducted from a content-based perspective, where the content was extracted and structured from successive readings of the articles. This stage identifies specific tools used in the integration of these approaches across various phases of construction projects and categorizes them based on their application to design, planning, and execution. By mapping these techniques, the study provides insights into how Lean, BIM, and Emerging Technologies have improved efficiency, collaboration, and decision-making in construction project management.

Stage 3: Synthesis and Analysis

The third stage integrates the findings from both the bibliometric and systematic literature reviews to provide a comprehensive synthesis of key themes and techniques. This stage ensures an in-depth analysis of the most relevant concerns regarding Lean Construction, BIM, and Emerging Technologies. The findings respond to the research questions and highlight critical areas where further integration is needed, providing a structured pathway for future research aimed at developing an integrated framework.

2.2. Article Selection Process

To the best of the authors’ knowledge, a review of the Lean Construction, BIM and Emerging Technologies integration has not been conducted so far. However, some studies have discussed the approach independently, but no specific studies have been proposed that integrate the three approaches together (Lean Construction, BIM, and Emerging Technologies). In response to the research questions, relevant documents were investigated according to the structure search strategy based on keywords and Boolean operators in

Table 1. Keywords and Boolean operator used to search relevant articles.

Keyword/Terms	Boolean Operator	Keyword/Terms
LEAN + BIM	AND	Technology
LEAN + BIM		Construction Technologies
LEAN + BIM + TECHNOLOGY		Framework
LEAN + BIM + Review		Emerging technologies including Big Data analytics, Blockchain, Mobile Robot Initialization Rule Representation, Deep Learning ANC System (CsNNet), Digital Twin (DT), RFID, Data Mining, AI & Machine Learning, Industry 4.0 (IoT), 3D Laser Scanning, Computer Vision (CV), Geographic Information System (GIS), Blockchain with EDM, Cloud Computing, Augmented Reality (AR), Edge Computing, Mixed Reality (MR), Deep Learning, Unmanned Aerial Vehicle (UAV), and 3D Reconstruction with Photogrammetry

. The search strategy was developed through iterative pilot searches to maximize recall and precision, guided by PRISMA 2020 recommendations. Searches were conducted in Scopus and Web of Science (WoS), chosen for their comprehensive coverage, robust indexing, and citation tracking. Boolean operators, truncation, and proximity functions were applied to capture synonyms and related terms for each construct. The definition of Emerging Technologies often stems from their innovation maturity, relevance to construction needs, and ability to resolve industry challenges, particularly in productivity, safety, and project cost management. Each technology on this list is evaluated for its integration potential, applicability to various construction phases, and ability to address specific industry gaps. The list of emerging technologies in construction is typically defined based on technologies with significant disruptive potential and proven applicability across various construction phases. This includes technologies that aid in design (e.g., Digital Twins, Virtual Reality), enhance on-site productivity (e.g., Robotics, Drones), improve safety (e.g., Wearable Technology), or optimize project management and data handling (e.g., IoT, Blockchain, Predictive Analytics).

In selecting the appropriate documents for this study, specific inclusion criteria were met. If a document fulfilled at least one exclusion criterion (EC), it was eliminated. The exclusion criteria included: (EC1) a duplicate document, and (EC2) an article that did not report an integration approach for efficient project management in the construction sector (using LEAN, BIM, and at least one emerging technology). A total of 241 papers were identified using the search string, including duplicates. The article selection process did not impose a specific publication time frame as a filtering criterion. Instead, the inclusion criteria ensured that only papers explicitly addressing the integration of these three domains were retained for analysis. As a result of this content-based selection, the publication years of the selected papers ranged from 2014 to 2024, reflecting the natural evolution of Industry 4.0 and Construction 4.0 paradigms, which emphasize digital transformation, automation, and lean principles. This period reflects the most relevant advancements in integrating Lean Construction, BIM, and Emerging Technologies, offering insights into both foundational concepts and cutting-edge innovations. The selection was limited to publications up to 2024 to ensure a comprehensive and well-defined scope, with future research encouraged to incorporate developments from 2025 onward. After applying the exclusion criteria, 64 articles remained. The following search engines were used: (1) Scopus, (2) Web of Science (WoS), and (3) ResearchGate. Scopus and Web of Science were selected for the search because they are widely recognized as two of the most comprehensive and reliable databases for academic literature. These databases are particularly valuable for ensuring academic rigor, as both offer citation tracking, enabling researchers to identify key works and trends within specific fields and their influence over time [28]. Together, these databases provide a rigorous and reliable foundation for bibliometric analysis. Additionally, ResearchGate was used only to retrieve full-text versions of records already identified in Scopus/WoS [29]. The article selection process is illustrated in Figure 2.

Following the approach of [26] the data extraction form used in this research is presented in Appendix B. The metadata was obtained, and content-based data were extracted to answer the research questions in Section 3.

This structured approach ensures transparency in the selection and analysis of relevant literature, aligning with the objectives of the study while maintaining academic rigor.

3. Results

In this section, the bibliometric and content data are processed and analyzed using the research method described in Section 2.

3.1. Annual Quantitative Distribution of Literature

The temporal distribution of publications signals not merely increasing interest but the rapid coalescence of a research agenda at the intersection of Lean Construction, BIM, and Emerging Technologies. While Figure 3 documents a steady rise from 2014 and a pronounced uptick from 2020 onward, this pattern should be interpreted through diffusion dynamics: the post-2020 acceleration is consistent with a critical-mass effect driven by (a) intensified Industry 4.0 investment programs, (b) pandemic-era adoption pressures that increased remote/digital practices, and (c) an expanding community of practice crossing academia and industry. However, quantity does not equate to maturity. The preponderance of recent outputs suggests an emergent field with many exploratory and conceptual contributions rather than consolidated, longitudinal evidence. We therefore caution against equating publication counts with validated impact: future work should complement bibliometric mapping with quality indicators (e.g., replication studies, longitudinal case evaluations, and citation-normalized impact metrics) to assess real-world uptake and sustained performance gains [30,31].

This trend underscores the importance of staying updated with advancements in these fields, particularly for practitioners and researchers aiming to leverage synergies between Lean principles, BIM capabilities, and Emerging tools such as AI, IoT, and Digital Twins. For instance, studies like those by [24,32] emphasize the critical role of integrating these methodologies to enhance productivity and efficiency.

3.2. Country Distribution of Selected Articles

Geographical patterns expose important structural drivers of research production and impact. High publication volumes in Italy and the UK likely reflect established research networks (e.g., IGLC participation) and specialized academic communities, whereas China’s disproportionate citation impact suggests concentrated, high-visibility studies—often on large infrastructure and modular construction projects. These disparities reflect more than scholarly preference: national procurement practices, public investment in megaprojects, and targeted R&D funding shape both the research questions pursued and the visibility of results. Moreover, citation counts are influenced by language, co-authorship networks, and database coverage; they therefore provide a noisy proxy for practical adoption. To strengthen global relevance, future reviews should disaggregate findings by regulatory context and procurement regime, and incorporate non-English and practice-oriented literature (industry reports, standards) to reduce selection bias and improve transferability assessments. Figure 4 shows the productivity by country.

3.3. Quantitative Analysis of Main Journals and Conferences

Out of the 64 articles, the majority were conference papers (29), followed by journal papers (25), as illustrated in Figure 5. Additionally, one book chapter was included. These 64 papers originate from 36 distinct sources, primarily covering the areas of Construction Management, Technology in Construction, Computer Engineering, and Architecture and Design Management.

Table 2. Sources with four or more papers.

Source (Journal/Conference)	No. of Papers
Conference of the International Group for Lean Construction (IGLC)	11
International Symposium on Automation and Robotics in Construction (ISARC)	5
Automation in Construction	4
Journal of Engineering, Construction and Architectural Management (ECAM)	4
Buildings	4

highlights the journals and conferences that feature more than one article. Among these, the dominance of conference venues (IGLC, ISARC) highlights the field’s practice-oriented and rapidly evolving character: conferences often capture early, exploratory work and industry-driven prototypes. While this is appropriate for emergent technologies, it implies a publication ecosystem where empirical validation and rigorous journal peer review lag behind conceptual advances. The field would benefit from purposeful “journalization” of prominent conference outputs through extended empirical studies, comparative analyses, and meta-analyses that strengthen internal validity. Thus, the need for mapping themes by venue and elevating high-quality case studies into journal articles to increase methodological rigor and cumulative knowledge. Other prominent sources include Automation in Construction, Journal of Engineering, Construction and Architectural Management (ECAM), and Buildings, each publishing four papers. These sources collectively underscore the interdisciplinary nature of research in Lean-BIM-Technology integration, ranging from management strategies to technological innovations. The first conference specializes in construction management, providing a foundational perspective on Lean principles. Subsequent conferences and journals broaden the scope to include technology applications, offering diverse perspectives on optimizing construction processes. This distribution across sources ensures a comprehensive exploration of the topic, addressing both theoretical frameworks and practical implementations.

3.4. Analysis of Papers Aims

The primary aim of the 64 papers is to explore how emerging technologies and advanced management techniques can be leveraged to optimize construction processes, reduce waste, and improve the quality of project outcomes. A central theme in many papers is the integration of Lean Construction principles with Building Information Modeling (BIM) to streamline workflows, minimize inefficiencies, and enhance collaboration among project stakeholders. This integration aims to address persistent challenges such as low productivity, cost overruns, and poor-quality management.

Several studies investigate the potential of emerging technologies such as automation, robotics, artificial intelligence (AI), blockchain, and the Internet of Things (IoT), to enhance decision-making, improve task coordination, and ensure high-quality outcomes. The use of these technologies is also examined for their ability to improve real-time monitoring, transparency, and overall project efficiency, leading to a reduction in material waste and time delays. For instance, AI-powered tools are used for predictive analytics, enabling early identification of potential risks and optimization of resource allocation [24,33,34].

In addition to these technological innovations, several papers emphasize the importance of sustainability and resource optimization. They propose methods to integrate Lean principles to ensure minimal waste and enhanced environmental sustainability. Some studies, for instance, are interested in Total Quality Management (TQM) and Percent Plan Complete (PPC) metrics to monitor and advance project quality with less defect [31,35,36]. Others stress the role of Target Value Design (TVD) and Lean Design Management (LDM) in controlling costs and maximizing value throughout the design [37,38,39]. Overall, the papers aim to embrace a construction environment where efficiency, waste reduction, and quality are prioritized using innovative technologies and management strategies. Also, research studies assist in the improvement of project delivery systems, stakeholder satisfaction, and sustainability in the construction industry.

Beyond these descriptive aims, the literature reveals a tendency toward aspirational framing rather than empirical validation. While many studies articulate what integrated Lean-BIM-Technology systems should achieve, fewer present rigorous evidence of what they do achieve in operational contexts. This imbalance reflects a maturity gap in the field: conceptual integration models outpace real-world trials. From a socio-technical perspective, the persistence of descriptive aims without robust longitudinal testing suggests that institutional, contractual, and capacity barriers are constraining experimental deployment. Furthermore, adoption theories such as Rogers’ Diffusion of Innovations highlight that without demonstrable relative advantage and observable results, industry uptake will remain slow despite promising technical potential.

To advance the field, future research should align stated aims with measurable, validated outcomes, employing standardized key performance indicators (KPIs) and pre/post implementation assessments. Comparative case studies across varied procurement models and project scales would help determine not only if integration delivers value but also how and under what conditions it does so. By moving beyond descriptive potential toward evidence-based impact, the scholarly discourse can better inform practice, strengthen stakeholder confidence, and accelerate the adoption of integrated Lean-BIM-Technology frameworks in diverse construction contexts.

3.5. Lean Construction Techniques Used

Most of the studies on Lean Construction methodologies indicate that many acknowledge Lean principles broadly, underscoring their foundational role in the construction sector [24,25,33,34,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55]. However, when specific techniques are examined, certain methodologies stand out due to their prevalence and impact. Among these, the Last Planner System (LPS) is the most frequently cited, appearing in 19 papers, highlighting its important role in streamlining workflows, reducing variability, and improving task readiness [17,30,35,36,37,38,56,57,58,59,60,61,62,63,64,65,66,67,68]. This dominance reflects more than functional efficiency; it also illustrates a strong socio-technical fit. LPS offers high perceived usefulness and ease of use, requiring relatively low technological investment while fitting seamlessly into existing project governance structures. This alignment lowers adoption resistance and explains its persistence across both traditional and digitally enabled projects. Organizations with established LPS routines are less likely to overhaul planning systems in favor of less familiar tools.

Unlike traditional scheduling practices, LPS fosters a cooperative and credible planning process by emphasizing stakeholder commitment, short-term work predictability, and continuous workflow improvement. Its adaptability across project scales, from small builds to megaprojects, has entrenched it as a cornerstone of Lean Construction. The integration of LPS with 3D BIM and digital technologies, such as IoT-based tracking systems, further enhances its value, enabling real-time, data-driven decision-making. The prevalence of 3D BIM over higher-order BIM dimensions can be understood through the lens of path dependency: organizations invest heavily in software, training, and workflows optimized for 3D modeling, creating sunk costs and institutional inertia that slow the diffusion of advanced functionalities. Further, 4D and 5D BIM face steeper adoption curves as “complex” innovations requiring greater trialability, observability, and compatibility with existing systems. This explains the paradox in which higher-dimensional BIM offers clear performance advantages yet remains underutilized, revealing an intellectual tension between technological capability and socio-organizational readiness. These patterns suggest that integration frameworks must not only address technical interoperability but also actively engage with organizational culture, change management, and policy incentives to break this cycle.

Visual Management techniques, cited in nine papers, also illustrate how Lean tools can serve as a bridge between analog and digital modes of operation [36,40,59,61,69,70,71,72,73]. Their transparency-enhancing capabilities are amplified when integrated with AR and MR environments, which offer immersive, context-aware displays that strengthen collaborative decision-making in planning, design, and execution. Similarly, the Just-In-Time (JIT) approach, addressed in seven papers [30,31,38,70,71,74,75], leverages digital monitoring, such as IoT sensors, to manage inventory flows dynamically, minimizing delays from overproduction or stockouts.

Other techniques serve as targeted enablers of continuous improvement. The PDCA (Plan-Do-Check-Act) cycle, highlighted in five papers, reinforces iterative learning and complements BIM’s data-driven monitoring capabilities [32,61,62,76,77], Takt Planning and Control, explored in six papers, synchronizes activities into regular intervals [36,61,66,75,78,79], with added precision when paired with 4D BIM scheduling. Total Quality Management (TQM), emphasized in three papers, focuses on defect minimization and systematic quality assurance [31,35,36], and its combination with AI-based predictive analytics opens new avenues for proactive quality control.

Cost optimization and value maximization are the domain of Lean Design Management (LDM) and Target Value Design (TVD) [37,38,39]. TVD’s integration of cost estimation into early design decisions ensures economic alignment with client expectations, while LDM’s early-stage waste minimization aligns with Industry 4.0 principles. Even rarely cited tools such as SCADA (one paper) demonstrate potential when combined with IoT for automated workflow monitoring [80]. Other techniques, such as 5S, Value Stream Mapping, Kanban, and Kaizen, appear in eight papers [36,39,40,62,64,71,72,80], contributing to site organization, process standardization, and cultural transformation. Nine papers discuss Lean Management and Optimization techniques more broadly [17,72,81,82,83,84,85,86,87], often integrating them with BIM, cloud computing, or AI to create adaptive production systems capable of responding to variability in complex projects.

Overall, the prevalence of tools like LPS and JIT reflects an adoption landscape shaped not only by technical merit but also by organizational culture, procurement frameworks, and perceived risk. From a socio-technical systems perspective, many of these techniques succeed because they align with existing work practices and can be incrementally enhanced through digital integration, rather than requiring wholesale process disruption. The challenge for future research lies in expanding adoption to less familiar but potentially more impactful techniques, which will require frameworks that explicitly address training, change management, and evidence-based demonstration of return on investment. See

Table 3. Lean techniques and number of papers cited.

Lean Techniques	No. of Papers
Last Planner System (LPS)	19
Visual Management techniques	9
Just In Time (JIT)	7
Takt Planning and Control	6
PDCA (Plan-Do-Check-Act)	5
Total Quality Management (TQM)	3
Lean Design Management (LDM) and Target Value Design (TVD)	3
Lean Management and Optimization	9
5S methodology, Value Stream Mapping, Kanban and Kaizen	8

.

3.6. BIM Dimensions and Techniques Used

The analysis of the 64 reviewed papers highlights the diverse applications of Building Information Modeling (BIM) across various construction project management dimensions. According to the BIM Uses framework [88], these applications range from design authoring and visualization to cost and facility management, supporting Lean Construction principles. The selection of the Penn State BIM Uses framework as the basis for this research is justified by its comprehensive, well-established, and widely recognized structure for defining BIM applications across the construction lifecycle. Developed by Pennsylvania State University, this framework provides a systematic classification of BIM applications that aligns with key industry needs, ensuring that BIM is effectively integrated into various project phases, including planning, design, construction, and operation. The Penn State BIM Uses have been extensively validated in academic and industry settings, making them a credible and reliable reference for structuring BIM implementation strategies. Furthermore, this structured approach facilitates interoperability, collaboration, and standardization in BIM adoption.

The most referenced BIM dimension is 3D BIM, used for design accuracy and visualization, enhancing collaboration, minimizing waste, and reducing rework. It is cited in 27 papers [17,24,25,32,42,43,46,47,48,53,57,59,60,62,65,69,70,72,73,74,76,78,79,81,86,89,90]. Nonetheless, 4D BIM, mentioned in 22 papers, incorporates scheduling and phase planning, supporting timely project delivery by providing real-time insights and simulating construction sequences [17,24,32,36,42,43,46,47,53,55,56,57,60,65,66,70,73,76,78,79,81,89]. This dimension aligns with Lean principles by improving scheduling and execution efficiency. 5D BIM, cited in 11 papers, integrates cost data, enabling cost estimation and budget management, which supports Lean’s cost-efficiency goals and real-time financial monitoring [32,42,43,46,48,53,56,70,73,80,89]. By incorporating cost information into the model, 5D BIM enhances decision-making and resource allocation during the construction process. BIM is also discussed broadly in several papers, reflecting its intersection with emerging technologies to drive innovation [30,33,34,35,38,39,40,41,44,45,49,50,51,52,54,58,61,63,64,67,70,75,77,80,82,83,84,85,87,91]. 7D BIM, though less common, supports post-construction facility management, optimizing long-term resource use [24,92]. The predominance of 3D BIM is not solely a matter of technical capability, it is also a reflection of entrenched workflows, sunk investments in software ecosystems, and user familiarity that lower the perceived risk of continued use. Further, 3D BIM scores highly on perceived ease of use and compatibility with existing processes, while higher-order BIM dimensions (4D, 5D, 6D, and 7D) often face adoption barriers due to increased complexity, required process re-engineering, and significant training demands. These advanced dimensions are “complex” innovations with lower trialability and observability, which slows their diffusion despite recognized benefits.

The review also reveals that resistance to change, coupled with financial constraints, remains a critical inhibitor. Higher-dimensional BIM requires not only enhanced software capabilities and greater computing power but also interoperable data environments and disciplined information management, conditions more easily met in large firms with dedicated BIM teams than in smaller companies. Without targeted change management strategies, these structural disparities will perpetuate unequal adoption across the industry.

The Common Data Environment (CDE), cited in two papers, enables collaborative workflows and real-time data sharing, reducing miscommunications and improving efficiency [31,37]. Tools like KanBIM and mobile applications such as BIM 360 Field and Glue facilitate construction progress monitoring, directly supporting Lean objectives by providing on-site access to project data and improving decision-making [68,86]. Overall, BIM plays a central role in enhancing project efficiency, reducing waste, and improving quality and safety, thereby promoting an integrated, efficient, and responsive construction landscape. However, realizing the full potential of higher-order BIM dimensions will require a combined strategy: (1) standardizing interoperability protocols, (2) embedding 4D/5D requirements into contractual deliverables, (3) investing in targeted training programs, and (4) demonstrating tangible return on investment through real-world pilots. Without addressing these socio-technical and economic constraints, adoption will continue to cluster around 3D BIM, limiting the transformative potential of integrated Lean-BIM-Technology frameworks. See

Table 4. BIM techniques used and number of papers cited.

BIM Techniques	No. of Papers
3D BIM	27
4D BIM	22
5D BIM	11
7D BIM	1
CDE (Common Data Environment)	2
Specific Applications and Tools: KanBIM system and Mobile Computing and BIM Tools	2

.

BIM Uses [88] can be effectively aligned with the various BIM dimensions [93], each representing specific project data and functionality. See

Table 5. BIM uses with associated BIM dimensions.

Phase	BIM Use	Associated BIM Dimensions
Plan	Capture Existing Conditions	3D (Geometric representation of existing conditions), 7D (Facility management for long term use)
	Author Cost Estimate	5D (Cost estimation and management)
	Author 4D Model	4D (Schedule and sequencing integration)
	Analyze Program Requirements	3D (Program visualization), 4D (Phasing analysis)
	Analyze Site Selection Criteria	3D (Topographical visualization), 4D (Construction feasibility analysis)
	Author Design	3D (Design modeling)
	Review Design Model(s)	3D (Visualization), 4D (Constructability review), 5D (Cost implications of design)
Design	Analyze Structural Performance	3D (Structural modeling), 4D (Simulation of structural systems over time)
	Analyze Lighting Performance	3D (Light path modeling), 6D (Sustainability analysis for energy efficiency)
	Analyze Energy Performance	6D (Sustainability analysis for energy optimization)
	Analyze Engineering Performance	3D (Mechanical, Electrical, Plumbing (MEP) modeling), 4D (Performance over time)
	Analyze Sustainability Performance	6D (Lifecycle sustainability evaluation)
	Coordinate Design Models	3D (Multi-disciplinary model integration), 4D (Schedule alignment across disciplines)
	Author Construction Site Logistics Model	4D (Time-based construction logistics planning)
Construct	Author Temporary Construction Systems Model	4D (Sequencing of temporary systems such as scaffolding)
	Fabricate Products	3D (Fabrication-ready geometric modeling), 5D (Cost for fabrication), 6D (Sustainable material analysis)
	Layout Construction Work	3D (Spatial verification), 4D (Time-based layout optimization)
	Compile Record Model	7D (Facility management), 3D (Geometric documentation)
Operate	Monitor Maintenance	7D (Maintenance tracking and lifecycle management)
	Monitor System Performance	7D (Operational efficiency monitoring)
	Monitor Assets	7D (Asset management)
	Monitor Space Utilization	7D (Space optimization and lifecycle management)
	Analyze Emergency Management	7D (Emergency planning and response analysis)

.

This analysis highlights how BIM helps to ensure quality and safety, improve project efficiency, and cut waste. BIM’s potential is further supported by combining it with Lean Construction and Emerging Technologies, which facilitates smooth communication and informed decision-making throughout the project. The growing use of 4D, 5D, 6D and 7D BIM points to a move toward more integrated and data-driven construction management techniques, even if 3D BIM is still widely used due to technology maturity, industry reluctance, and financial limitations.

3.7. Methods of Integration

This analysis identifies the most widely recognized and effective integration methods, laying a foundation for future research. Among the 64 examined papers, frameworks emerge as the most frequently cited approach, appearing in 32 studies. They provide structured methodologies that enhance collaboration and efficiency in construction projects. Frameworks vary from conceptual models, which establish theoretical foundations, to matrix-based models focused on design optimization and quality management. Technological frameworks integrate tools like BIM, IoT, and mobile apps, aligning with lean principles, while comprehensive frameworks encompass both technical and social elements across the project lifecycle. Implementation-oriented frameworks offer step-by-step guidance for direct application. Frameworks remain the dominant approach for integrating Lean Construction, BIM, and Emerging Technologies due to their structured and comprehensive nature. They provide clear methodologies for combining Lean principles, BIM capabilities, and digital tools, essential in an industry characterized by complexity and diverse stakeholder expertise. Frameworks standardize processes, ensuring consistency and reducing ambiguity [94,95]. Additionally, they facilitate interoperability between Lean Construction, BIM, and Emerging Technologies, enabling seamless data exchange across project phases. For example, BIM-integrated frameworks that incorporate Lean tools such as the Last Planner System (LPS) and IoT sensors enable real-time monitoring and decision-making, improving project efficiency and minimizing waste [67,96]. In addition to frameworks, models support project management and design precision mentioned in 7 papers [24,53,57,59,78,79,90].

Guidelines, mentioned in 8 papers [44,45,48,63,64,71,72,81], enable compliance with industry standards and standardization across the project life cycle. Matrices, though less frequently (4 papers), play a role in optimizing design and decision-making [69,70,73,75]. Technologies, such as digital platforms [61] and AR4C applications [43] facilitate practical applications, and gaming platforms [84] emphasize the educational aspects of integrating these methodologies. The dominance of frameworks can also be attributed to their scalability and adaptability, making them suitable for diverse project types and sizes. This flexibility is crucial in construction, where projects vary significantly in scope and complexity. For instance, frameworks integrating modular construction techniques and digital twins can be applied to both small-scale residential developments and large-scale infrastructure projects [97,98]. Moreover, frameworks help address key industry challenges, such as resistance to change, high implementation costs, and the need for workforce upskilling. By providing clear guidelines and emphasizing the benefits of integration, they facilitate smoother transitions to digital and Lean practices. Frameworks that incorporate training modules and change management strategies have been shown to support successful implementation [99,100]. See

Table 6. Integration approach and number of papers cited.

Integration Method	No. of Papers
Framework	32
Guidelines	8
Model	7
Matrix	4
Digital Platforms and Applications	2
Gaming and Simulation	1

.

However, many frameworks remain conceptual and under-operationalized. The next step is to convert frameworks into modular, testable intervention packages with defined inputs, activities, and measurable outputs, i.e., treat frameworks as hypotheses to be validated. It should propose a typology (technical-first, socio-technical, and implementation-oriented frameworks) and recommend that authors (a) declare the framework’s boundary conditions, (b) provide metrics for evaluation, and (c) pilot the framework in diverse procurement contexts. This approach will distinguish heuristic contributions from implementable solutions and enable comparative evaluation across studies.

3.8. Emerging Technologies

Emerging technologies are transforming the construction industry by enhancing efficiency, collaboration, and precision across various project phases. These technologies can be classified into categories such as design, execution, data management, monitoring, supply chain management, and security, streamlining processes and improving outcomes.

The bar chart above shows the frequency of technologies mentioned in construction papers, grouped into seven categories. Project Execution and Automation has the highest frequency, reflecting its importance in automating tasks and optimizing on-site operations, followed by Design and Visualization Tools, highlighting their role in improving stakeholder engagement and decision-making. Supply Chain and Resource Management technologies are also prominent, emphasizing the need for efficient logistics and resource tracking in modern construction projects. Figure 6 presents the technologies frequency as per the project phases.

Project Execution and Automation: This category of technologies focuses on increasing on-site productivity, schedule optimization, and work automation. According to 13 publications, robotics and automation (e.g., UAVs (Unmanned Aerial Vehicles), AGVs (Automated Guided Vehicles)) help minimize labor-intensive activities and expedite repetitive operations, particularly in offshore construction and prefabrication [24,31,32,33,34,35,40,56,60,70,76,77,80,87,101]. Predictive analytics and resource allocation throughout different construction phases are facilitated by artificial intelligence (AI) and machine learning (ML) [34,55,60,77]. The Internet of Things (IoT) sensors provide real-time data, progress tracking, and process automation, as referenced in 21 publications [26,28,30,31,33,35,44,48,50,51,54,61,62,65,70,71,72,75,77,81,87]. Additionally, 11 studies have addressed Radio Frequency Identification (RFID) and Bluetooth Low Energy (BLE), which enhance supply chain logistics and location monitoring by ensuring timely and accurate material delivery [17,48,49,55,63,67,72,73,75,76,77,85].

Design and Visualization Tools: This category includes technologies that enable precise design creation, scenario simulation, and immersive stakeholder engagement. Ten studies discuss digital twins, which support decision-making and simulations by providing real-time information on project performance and development [24,32,33,40,50,74,76,81,83,91]. Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) enhance stakeholder communication and visualization by allowing users to interact with virtual project models, as cited in 17 studies [32,39,42,43,45,46,56,58,62,68,69,70,73,76,79,81,89]. Furthermore, some studies highlight the role of 3D printing and additive manufacturing in precise modeling and offshore construction, contributing to reduced material waste and improved accuracy [31,34,70,90].

Data Management and Collaboration: This category focuses on tools that enhance collaboration and data sharing among project stakeholders, enabling seamless remote access. Cloud computing, cited in 11 papers, improves team coordination by allowing remote access to BIM models and other project data [24,31,34,40,53,56,61,76,85,86]. The Common Data Environment (CDE, provides a centralized platform for document management, ensuring all stakeholders have access to the most up-to-date information [31,34,86]. Mobile computing, discussed in three papers, enables on-site workers to access BIM models and other critical data in real time, improving decision-making [34,61,86]. Additionally, Geographic Information Systems (GIS), mentioned in two studies, facilitate spatial data management, supporting site planning and infrastructure development [34,47].

Monitoring and Quality Control: These technologies ensure high-quality results and compliance with safety regulations. For example, laser scanning and photogrammetry, referenced in seven papers, are used for precise measurements and quality control during construction [17,32,46,59,70,73,77,102]. Drones and UAVs (Unmanned Aerial Vehicles), mentioned in five papers, facilitate site surveys, structural inspections, and progress monitoring [17,31,56,57,80]. SCADA (Supervisory Control and Data Acquisition), cited in one study, enables real-time control and automation of construction processes [80]. Wearable technology (WT), such as smart vests and helmets, monitors worker health and safety, reducing accidents and improving overall site conditions [34].

Supply Chain and Resource Management: This category focuses on improving supply chain transparency and optimizing resource allocation. According to ten studies, RFID (Radio Frequency Identification) and NFC (Near Field Communication) enhance tracking of materials and resources across the supply chain, reducing inefficiencies and delays [48,49,63,67,72,73,75,76,77,85]. Additionally, blockchain technology enhances supply chain transparency, prevents fraud, and ensures secure transactions [20,28,29,30,32,36,39,49].

Data Analytics and Decision Support: This category leverages advanced analytics to predict potential issues and enhance process efficiency. Big data optimizes workflows by analyzing large datasets to identify patterns and trends [24,31,33,34,39,40,76]. Predictive analytics utilizes AI-powered tools to forecast delays, resource requirements, and cost overruns, enabling proactive decision-making [34,55,60,77,103]. Additionally, edge computing, which enhances real-time decision-making and reduces latency by processing data locally at the source [34].

Security and Risk Management: This category focuses on minimizing risks and ensuring the security of digital assets. Blockchain enhances stakeholder trust by securing data management and ensuring tamper-proof records [35,37,41,44,54,76]. Cybersecurity measures protect sensitive project information from unauthorized access and cyber threats [31,34].

The literature shows a broad technological portfolio but uneven maturity. Robotics, AI, and digital twins appear promising for execution and monitoring, yet many studies are demonstrators rather than evaluated deployments. Technology-centric enthusiasm should be tempered by assessments of Technology Readiness Levels (TRLs), interoperability, data governance, and cybersecurity implications. Moreover, there is limited discussion of economic trade-offs (capital vs. operating costs) and the social consequences (labor displacement, skills demand). Future research should prioritize (1) TRL-based assessments, (2) integrated cost–benefit analyses, and (3) governance studies that address data ownership and privacy.

Table 7. Technologies and number of papers cited.

Category	Technology	No. of Papers
Design and Visualization Tools	Digital Twins (AR), (VR), (MR) 3D Printing/Additive Manufacturing	27
Project Execution and Automation	Robotics and Automation AI and Machine Learning IoT and Sensors RFID and BLE	31
Data Management and Collaboration	Cloud Computing Common Data Environment (CDE) Mobile Computing GIS	11
Monitoring and Quality Control	Laser Scanning, Photogrammetry, and Reality Capture Drones/UAVs SCADA Wearable Technology (WT)	12
Supply Chain and Resource Management	RFID and NFC Blockchain	18
Data Analytics and Decision Support	Big Data and Analytics Predictive Analytics Edge Computing	10
Security and Risk Management	Blockchain for Security Cybersecurity	8

presents an overview of this category, listing the associated technologies along with the number of studies citing them.

3.9. Project Type

Most studies focus on general construction projects, covering a broad range of activities, methods, and technologies without specifying a particular type. These studies highlight trends, practices, and innovations applicable across various construction settings (see Figure 7). A significant number of papers examine facility management projects, emphasizing operational efficiency and strategic planning [34,83,85]. Educational buildings, including schools and universities, are analyzed for their potential to integrate Lean-BIM-Technology approaches during both construction and renovation phases, with a focus on resource optimization and sustainability [58,63,84]. Infrastructure projects, such as urban transportation networks, airports, railways, and power and water facilities, dominate the research landscape due to their complexity and scale. These studies often integrate Lean principles with advanced technologies like drones, IoT, and 4D/5D BIM to enhance scheduling, resource management, and quality control [32,35,46,61,63,87,90]. Residential construction and renovation studies explore cost-effective solutions and streamlined workflows through modular design and prefabrication techniques [50,62]. The increasing adoption of offsite construction and prefabrication is well-documented, with research emphasizing its role in enhancing productivity, reducing waste, and improving precision in projects such as modular housing, prefabricated bridges, and precast components [48,49,53,70,71,90]. Healthcare and hospital projects, whether new constructions or renovations, are discussed in multiple studies, demonstrating how integrated approaches address challenges related to safety, precision, and stakeholder coordination [63,79]. Manufacturing and industrial projects focus on constructing new production facilities and industrial-scale developments, where Lean Construction and BIM are leveraged to streamline processes and enhance workflow efficiency [39,46,81,82]. Some studies also explore specialized applications, such as complex design processes, utility relocation, landscape design, and digitalization, utilizing methods like agent-based simulations and reality capture technologies [37,56,69,74]. Additionally, interior construction and renovation projects emphasize detailed work within buildings, leveraging AR/VR tools for improved visualization and collaboration [68]. This review underscores the diversity of the construction industry and the increasing integration of specialized methodologies such as offsite construction, modular design, and facility management across various sectors.

Project-type distribution reveals bias toward large, formal projects (infrastructure, institutional buildings, offsite construction) which attract R&D and funding. This focus limits generalizability to smaller contractors, informal housing sectors, and retrofit projects—contexts that constitute a large share of global construction activity. To deliver practically useful frameworks, researchers must stratify analyses by project scale, procurement type, and regulatory environment. Comparative studies across small/medium/mega projects will clarify which integration approaches are portable and which require bespoke adaptation.

3.10. Country of Application

The integration of Lean Construction, BIM, and Emerging Technologies spans across various countries, as reflected in the analysis of 64 studies. The United Kingdom focuses on facility management and construction process optimization, particularly through digital twins, IoT, and Lean principles [40,74,82,83,90]. The United States emphasizes digitalization in construction, leveraging AI, IoT, and BIM for real-time monitoring and automation [32,57,64,70,89]. India contributes significantly to research on large-scale civil engineering and infrastructure projects, exploring the integration of Lean Construction and BIM to enhance productivity and quality [35,45,46,62,69]. China leads in modular construction and infrastructure development, utilizing advanced technologies such as robotics, 3D printing, and blockchain to drive innovation [31,48,49,53,90]. Italy focuses on offsite construction and digital integration, combining Lean methodologies with BIM and emerging technologies to improve project outcomes [39,41,43,58,65]. Germany specializes in industrial applications and construction management, emphasizing the synergy between Industry 4.0 concepts and Lean practices [65,78,81,85]. Other European countries explore regional construction practices [50,60], with multi-country collaborations involving China, the UK, and Singapore [90], Taiwan and the USA [32], and France and Luxembourg [36]. Additional mentions include Turkey [87], Sri Lanka [56], Portugal [37], Switzerland [61], Canada [79], Saudi Arabia [51], and Israel [68]. This distribution highlights the widespread adoption of these approaches across various geographical regions, underscoring their versatility in addressing diverse construction challenges. See Figure 8.

Country-level differences map onto governance, procurement, and market structure. For instance, China’s emphasis on modular construction aligns with government-led infrastructure programs and manufacturing supply chains, while the UK’s facility-management focus reflects contractual practices valuing life-cycle performance. These contextual drivers mean that integration frameworks are not one-size-fits-all: they must be sensitive to national procurement models, labor market skills, and regulatory incentives. Reporting contextual variables, such as procurement type, client type, and labor market characteristics, in all empirical studies is recommended to facilitate cross-country learning and adaptation.

3.11. Construction Phase

Most studies address all phases of the construction lifecycle, including design, planning, and execution, see Figure 9. A significant portion of the research focuses on the planning and execution phases, particularly concerning offsite construction and Lean methodologies [17,45,47,50,60,65,66,69,70,73]. Some papers emphasize the execution phase exclusively, particularly in relation to BIM and Emerging Technologies for optimizing on-site processes [43,51,57,58,68,72,75,86]. Additionally, a few studies highlight the operational phase of facility management, demonstrating the broad applicability of these technologies across the entire construction process [40,85].

This distribution highlights the importance of integrating Lean Construction, BIM, and Emerging Technologies across all project phases to optimize resources, time, and quality. The emphasis on planning and execution reflects the critical need to streamline processes during these stages, while the inclusion of facilities management underscores the growing focus on long-term operational efficiency.

3.12. Key Performance Indicators (KPIs)

Performance metrics are essential for assessing the effectiveness of integrating Lean Construction, BIM, and Emerging Technologies in construction projects.

Cost efficiency remains a primary focus, with numerous studies highlighting cost reduction, waste minimization, and adherence to budget constraints [30,33,40,42,44,45,46,47,48,49,55,56,58,60,63,75,76,80,82,86,89]. Time efficiency and project delivery are also prioritized, emphasizing time savings, schedule adherence, and on-time completion [17,24,30,31,42,44,46,49,50,54,56,58,63,64,75,78,79,82,86,89,90]. Productivity and resource utilization are significant areas of study, including workforce efficiency and optimized material and space management [32,40,55,58,59,62,63,65,68,76,80,90]. Waste reduction and Lean principles are emphasized through initiatives aimed at minimizing material waste, streamlining processes, and applying Lean methodologies such as Percent Plan Complete (PPC) [25,32,34,36,42,45,55,58,59,60,63,64,66,68,76,80].

Additionally, quality, safety, and stakeholder satisfaction serve as integral metrics, ensuring compliance with safety standards, enhancing project quality, and fostering collaboration [31,32,40,45,46,48,49,56,57,75,84,86,90,91]. Finally, process optimization and automation focus on real-time data integration and workflow streamlining to enhance overall efficiency [30,56,57,61,72,80,82,90]. This comprehensive evaluation underscores the balance between cost, time, resource efficiency, quality control, safety, and stakeholder engagement.

The literature shows that KPIs tend to focus on the iron triangle of cost, time, and quality, with less emphasis on innovation, adaptability, and sustainability. This is partly due to industry reliance on legacy performance frameworks that prioritize easily quantifiable metrics. While PPC and waste reduction are frequently reported, methods of calculation vary, reducing comparability. Automation-related KPIs, such as real-time decision-making speed, are also underrepresented despite their growing relevance. To maximize the value of Lean-BIM-Technology integration, KPI frameworks should be standardized, embedded from the project’s outset, and expanded to capture broader impacts beyond cost and schedule. See

Table 8. Key performance indicators and number of papers cited.

KPIs	Metrics	No. of Papers
Cost efficiency and savings	Reduction of overall project costs, waste minimization, and ensuring on-budget delivery	21
Time Efficiency and Delivery	Measuring project time savings, adherence to schedules, reducing delays, and on-time delivery.	21
Productivity and Resource Utilization	Worker and equipment productivity, material utilization, space utilization, and resource efficiency.	12
Waste Reduction and Lean Principles	Reduction in material waste, minimizing non-value-adding activities, and applying Lean methods like Percent Plan Complete (PPC).	16
Quality and Safety	Quality control, adherence to safety standards, and enhanced accuracy in project execution and planning	14
Stakeholder Satisfaction and Collaboration	Improving communication, collaboration, and stakeholder satisfaction in the construction process.	9
Process Optimization and Automation	automation of tasks, real-time data integration, and overall process improvements.	8

.

Collectively, these KPIs highlight the diverse benefits of integrating Lean Construction, BIM, and Emerging Technologies, providing a robust framework for assessing project performance and driving further advancements in construction methodologies.

3.13. AI Used

The application of Artificial Intelligence (AI) across the reviewed papers primarily focuses on general AI concepts, machine learning (ML), and specific techniques such as Artificial Neural Networks (ANN) and agent-based simulations. Several studies mention AI in a broad sense, particularly for data processing and optimization [31,34,76,87]. Machine learning algorithms have been employed for predictive analysis and modeling [32,61,80], facilitating data-driven decision-making. For example, computer vision techniques were integrated with machine learning algorithms [57] to track construction progress and activities. ANN was explicitly applied in [35] to predict outcomes in quality management processes, while [70] incorporated ANN alongside other AI techniques, including Support Vector Machines (SVM) and Rule-Based Systems (RBS). Agent-based simulations were utilized in [91] to simulate and analyze the dynamics of Building Information Modeling (BIM) models. Additionally, paper [55] employed predictive analytics, indicating the use of AI-driven decision-making in construction processes. Although many papers do not explicitly detail AI algorithms, the increasing adoption of AI across construction research underscores its significance in enhancing productivity, optimizing processes, and improving decision-making through predictive analytics and simulation techniques.

Minimum reporting standards for construction AI studies should include explicit algorithm names, data provenance, preprocessing steps, validation holdouts, performance metrics, and discussions of explainability and bias. Additionally, studies should clarify whether AI components are embedded within an integrated Lean-BIM workflow or evaluated in isolation.

3.14. Challenges of Implementation

The implementation of Lean Construction, BIM, and Emerging Technologies in the construction industry faces several challenges. A key issue is the complexity of integrating digital technologies such as Digital Twins, AR, VR, and IoT into traditional workflows, often hindered by operational inefficiencies, technological limitations, and stakeholder misalignment [24,25,33,40,42,43,45,46,47,49,55,58,61,62,64,69,73,74,76,77,78,82,83,90,91]. Resistance to change and cultural reluctance further complicate adoption, as many industry professionals remain hesitant to transition from conventional to digital methodologies [9,24,30,31,34,35,36,41,42,43,44,63,64,79,80,85,86,89].

Data integration presents another critical challenge, with the fragmented nature of the construction industry impeding seamless information exchange and necessitating enhanced digital infrastructure [32,38,48,53,55,59,66,68,72,75,81,91,93]. Training and skill development also pose significant barriers, as the effective implementation of these technologies requires comprehensive workforce upskilling [17,30,31,46,50,56,58,59,65,66,79,90]. Legal and regulatory constraints, including the absence of standardized frameworks for technologies such as blockchain and 3D printing, further restrict widespread adoption [30,31,44,51,73].

Moreover, the high initial costs associated with hardware, software, and training deter investment, particularly among smaller firms [24,33,36,49,62,63,89,90]. Addressing these challenges requires a coordinated industry-wide effort to facilitate digital transformation, promote Lean Construction principles, and support technological integration.

3.15. Future Research Directions

The extracted data highlights several future research directions related to the integration of Lean Construction, BIM, and Emerging Technologies in the construction industry. A significant number of studies emphasize the need for developing more comprehensive integration models and robust frameworks to enhance interoperability among Lean Construction, BIM, and Emerging Technologies [17,24,32,34,46,49,50,59,69,71,76,77,81,85,87,89]. These papers stress the importance of extensive testing and validation in real-world construction settings to ensure the practicality and reliability of integrated systems [25,41,43,61,66,68,72,80,91]. Additionally, several studies propose further investigation into AI, IoT, and predictive analytics to enhance real-time data processing, improve decision-making capabilities, and optimize project management efficiency [31,33,45,56,57,63,75,78,82,84,86]. This includes integrating these technologies with BIM and Lean Construction to foster collaborative digital environments that enhance the construction lifecycle.

Many studies also highlight the importance of addressing cultural and organizational barriers, calling for research into overcoming resistance to technological adoption, managing change, and fostering stakeholder engagement [31,33,44,54,55,73,79,86]. Furthermore, there is growing interest in exploring the synergies between Lean principles and digital innovations, particularly within Construction 4.0, Industry 4.0, and circular economy frameworks [31,36,39,40,55,60,70,71,75]. Finally, expanding research on practical applications of technologies such as blockchain, digital twins, and 4D BIM is recommended to enhance real-time communication, resource tracking, and project optimization [30,37,38,44,48,54,58,83,90]. As these future research directions indicate, the construction industry continues to evolve with cutting-edge technological advancements, requiring both theoretical exploration and empirical validation [92]. Addressing challenges related to cost, training, scalability, and stakeholder engagement will be essential for bridging the gap between research and practical implementation, ensuring that Lean-BIM-Technology integration delivers measurable improvements in project performance, sustainability, and efficiency [15].

4. Discussion

The literature review underscores the increasing global interest in integrating Lean Construction, Building Information Modeling (BIM), and Emerging Technologies to address inefficiencies, cost overruns, and quality challenges in construction projects [14,104,105]. Despite growing adoption, the integration of Lean Construction, BIM, and Emerging Technologies remains fragmented, particularly in large-scale projects where resource management is critical. This study identifies key tools within these domains, serving as a foundation for future research to develop a unified framework. While Lean Construction and BIM have been extensively studied and implemented independently, a significant gap remains in establishing a unified approach that incorporates Emerging Technologies. Addressing this gap is essential to overcoming persistent challenges related to productivity and resource optimization in the construction sector [14,104].

The research methodology employed a multi-stage approach to explore key tools. A bibliometric analysis mapped the interrelations between Lean, BIM, and Emerging Technologies, identifying key themes and trends. A systematic literature review (SLR) further extracted specific techniques applied across construction phases, revealing practical applications. The findings emphasize the need for cohesive frameworks that bridge theoretical exploration with empirical validation. Studies by [24,32] highlight the importance of aligning Lean principles with digital tools to enhance decision-making and collaboration. However, the absence of standardized integration methods limits scalability and adaptability across diverse contexts.

Lean Construction techniques, including but not limited to Last Planner System (LPS), Visual Management, and Just-In-Time (JIT) are widely recognized for optimizing workflow, reducing variability, and enhancing decision-making [36,40]. LPS has been extensively applied due to its structured planning cycles that improve coordination among stakeholders [36,40,59,73]. When combined with BIM’s capabilities, such as 3D modeling for visualization and 4D scheduling for precise timing, these techniques significantly enhance collaboration and project management [9]. Techniques like the PDCA cycle and Takt Planning further support continuous improvement, aligning with Lean Construction’s emphasis on waste reduction and quality management [36,61,62,66,76,79]. Despite these benefits, integration challenges persist, particularly regarding the lack of robust implementation guidelines, leading to inconsistencies in practice [58,60,80].

BIM plays a central role in integration, with its multidimensional capabilities (including but not limited to 3D, 4D, and 5D) supporting design accuracy, project scheduling, and cost management [25,42,46,48,53,57,59,60,62,79]. However, despite its widespread adoption, standalone BIM applications do not fully address the dynamic nature of construction projects. The use of 4D BIM for improved scheduling precision and 5D BIM for real-time cost tracking aligns closely with Lean principles but remains underutilized in integrated frameworks. Additional BIM functionalities, such as 7D BIM for facility management and Common Data Environments (CDEs), offer significant potential for lifecycle optimization, yet their implementation is often constrained by technological maturity and user expertise [24,31,37].

Emerging Technologies, including, but not limited to, Digital Twins, AR/VR/MR, and AI-driven automation, are increasingly transforming the construction sector by enhancing design modeling, stakeholder collaboration, and real-time decision-making [24,33,40,50,74,76,91]. Technologies related to project execution, such as robotics, AI, IoT, and RFID/BLE, are frequently discussed for automating tasks, optimizing resource allocation, and enhancing real-time decision-making [13,24,31,56,70]. Data management tools like Cloud Computing and CDE enhance collaboration and ensure that project teams can access and share information in real-time, further contributing to improved efficiency [24,34,40,53,56]. Monitoring technologies like laser scanning and UAVs, along with supply chain management tools such as RFID and blockchain, ensure quality control and transparency, improving overall project outcomes, yet integration challenges persist due to interoperability issues and high implementation costs [46,59,63,85]. Data analytics and security technologies, such as Big Data, predictive analytics, and cybersecurity, are increasingly integrated into construction projects to optimize workflows and protect digital assets [24,33,34,39,40,76,85].

Empirical studies demonstrate the impact of Lean-BIM-Technology integration in real-world applications. For instance, BIM adoption in off-site manufacturing has been shown to reduce construction waste by up to 84.7% [13]. A Finnish pilot case study integrating LPS with 4D BIM resulted in a 35% improvement in scheduling accuracy, reducing project delays and cost overruns [12]. In China, a Lean-BIM-Blockchain integration strategy for prefabricated modular buildings improved supply chain transparency, reducing material wastage by 22% and enhancing cost estimation accuracy by 18% [25]. A UK-based infrastructure project utilizing a cloud-based CDE demonstrated significant stakeholder collaboration improvements, reducing rework by 28% [14]. Additionally, a US study on AI-powered Lean-BIM safety analysis for high-rise construction showed a 40% reduction in on-site accidents and improved adherence to safety protocols [21]. A Singapore-based study integrating Takt Planning with 5D BIM cost estimation reported a 20% reduction in construction time and 15% total cost savings [42].

While these case studies confirm the effectiveness of Lean-BIM-Technology integration in enhancing project efficiency, cost control, and risk management, significant barriers remain. Resistance to digital transformation, high implementation costs, and the need for specialized training limit widespread adoption. For example, Lean-BIM-Blockchain frameworks, despite their documented benefits in supply chain transparency, face challenges related to interoperability with mainstream BIM software and the high computational costs of blockchain transactions. Although theoretical advantages are well recognized, practical implementation remains scarce due to the reliance on universal blockchain adoption within the construction sector.

The reviewed literature identifies several critical gaps, including the absence of standardized integration protocols, insufficient consideration of socio-technical factors, and limited exploration of synergies between Lean Construction, BIM, and Emerging Technologies [44,58,62,64,73,90]. While many studies discuss Lean-BIM integration, few delve into the complexities of incorporating AI, Digital Twins, and IoT into existing frameworks [24,33,34,39,76,85]. Future research should focus on developing adaptable frameworks that address these challenges while considering regional variations, project scales, and organizational cultures. Furthermore, longitudinal studies examining the impact of these integrations on project outcomes could provide deeper insights into their effectiveness and adaptability [39,58,60,73]. Finally, fostering collaboration between academia and industry is essential to accelerating the development and validation of practical integration solutions, bridging the gap between conceptual models and real-world applications [58,73,90].

5. Conclusions

The global construction industry, a key driver of economic growth, continues to face persistent challenges such as low productivity, cost overruns, and quality concerns. This review aims to identify the key tools of Lean Construction, Building Information Modeling (BIM), and Emerging Technologies to establish a robust foundation for developing a future research framework. Lean Construction tools, including but not limited to the Last Planner System (LPS), Just-In-Time (JIT), and Visual Management, are identified in this study, along with other essential tools that contribute to efficiency, waste reduction, and process optimization within construction projects, align closely with BIM capabilities in 3D, 4D, 5D, 6D, and 7D modeling, enabling precise design, scheduling, cost management, lifecycle analysis, sustainability assessment, and facility management, thus fostering collaboration and data-driven decision-making. Emerging Technologies further enhance this integration by enabling automation, real-time monitoring, and advanced data analytics, thereby improving overall project outcomes. Despite these advancements, a comprehensive and cohesive framework that fully integrates Lean, BIM, and Emerging Technologies remains elusive, particularly in addressing the unique demands of large-scale projects and regional variations. The literature review indicates a growing interest in integrated approaches since 2020, with frameworks being the dominant method for unifying these tools, yet challenges such as integration complexity, high implementation costs, resistance to change, and the need for workforce upskilling continue to hinder widespread adoption. Additionally, the reliance on secondary data and literature reviews limits insights into real-world applications, while large-scale frameworks may overlook the specific needs of smaller firms. To bridge these gaps, future research should prioritize developing adaptable frameworks validated across diverse contexts while considering both organizational and cultural challenges. Theoretically, this study advances the understanding of Lean-BIM-Emerging Technology integration, while practically, it provides actionable insights for industry stakeholders, with key strategies including workforce training to enhance digital and lean competencies, pilot projects to assess feasibility and return on investment, and foster organizational cultures that support innovation and change management. By adopting these strategies, the global construction industry can significantly enhance project efficiency, cost-effectiveness, and sustainability, paving the way for more resilient and high-performing built environments.

Limitations on This Review

While this review adhered to PRISMA 2020 guidelines and employed a structured, multi-stage methodology, several limitations should be acknowledged to contextualize the findings. The keyword-based search strategy, despite iterative refinement, may not have captured studies using alternative terminology for similar concepts. As with all systematic reviews, there is a potential for publication bias, with positive or novel findings more likely to be published. Finally, the review captures literature up to 2024; developments emerging thereafter are outside the scope of this analysis. Recognizing these limitations allows for a balanced interpretation of the results and highlights the need for ongoing research to capture the rapidly evolving nature of construction technologies.