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Review

Integration of Lean Construction and BIM in Sustainable Built Environment: A Review and Future Research Directions

by
Yingnan Yang
1,2,
Chunxiao Chen
1,
Xin Liu
1 and
Zhicheng Zhang
1,*
1
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
2
Center for Balance Architecture, Zhejiang University, Hangzhou 310028, China
*
Author to whom correspondence should be addressed.
Buildings 2025, 15(14), 2411; https://doi.org/10.3390/buildings15142411
Submission received: 10 May 2025 / Revised: 28 June 2025 / Accepted: 4 July 2025 / Published: 9 July 2025
(This article belongs to the Special Issue Advances in Project Development and Construction Management—2nd Edition)
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Abstract

Despite growing interest in integrating Lean Construction (LC) and Building Information Modeling (BIM) to advance sustainability in the Architecture, Engineering, and Construction (AEC) industry, research remains fragmented and lacks a unified implementation framework. This study bridges this gap by conducting a systematic literature review (2010–2024) of 96 journal articles to (1) analyze research trends in BIM-LC integration; (2) evaluate its benefits for sustainable built environments; and (3) identify barriers to adoption. A key contribution is the development of a novel four-dimensional BIM-LC integration framework, encompassing information integration, supply chain management, waste management, and life cycle management, which synergizes LC principles with BIM’s technical capabilities to reduce waste, enhance resource efficiency, and support carbon neutrality goals. The findings reveal that while BIM-LC integration significantly improves construction productivity and reduces environmental impacts, technical challenges in data interoperability and fragmented lifecycle management persist. Actionable solutions are further proposed, including semantic model standardization, AI-driven supply chain resilience, and circular economy integration. This framework provides both scholars and practitioners with a roadmap to advance BIM-LC adoption for sustainable construction.

1. Introduction

The Architecture, Engineering, and Construction (AEC) industry is facing increasing pressure to achieve sustainability goals while addressing chronic inefficiencies, fragmented workflows, and resource waste [1]. The integration of Building Information Modeling (BIM) and Lean Construction (LC) has the potential to fill the research and practice gaps in the field of sustainable construction, overcome interoperability barriers, enhance real-time decision-making across the supply chain, and address persistent industry challenges including data silos, reactive interruption management, and the lack of standardized environmental performance indicators. BIM provides a micro-level digital representation of building components, enabling precise visualization, clash detection, and data-driven decision-making. In contrast, LC operates at a macro level, focusing on optimizing processes across the construction value stream to eliminate waste and maximize value [2].
Despite the growing body of research on BIM-LC integration and its recognized potential for sustainable built environments, significant limitations and research gaps persist. Current studies often exhibit fragmentation [3], focusing predominantly on isolated phases (e.g., design clash detection [4,5] or construction scheduling [6]) rather than holistic lifecycle management. Furthermore, technical challenges related to data interoperability between the micro-level detail of BIM and the macro-level process focus of LC hinder seamless integration [5,7,8,9]. A critical gap is the lack of standardized semantic models and bidirectional data exchange mechanisms, limiting the synergistic potential of these approaches. Additionally, while benefits like waste reduction are frequently cited [10,11,12,13,14], there is a scarcity of unified frameworks that comprehensively link BIM-LC integration to quantifiable sustainability metrics aligned with broader goals (e.g., UN SDGs) across the entire project lifecycle. These limitations underscore the need for a cohesive and integrative framework that bridges technical interoperability gaps, facilitates end-to-end lifecycle management, and provides a structured approach for evaluating sustainability performance. This paper aims to address these gaps by proposing such a framework.
The three research questions developed for this research are listed below:
  • RQ1: What are the research trends of the integration of LC and BIM?
  • RQ2: What are the benefits of integration of LC and BIM in the context of sustainable built environments?
  • RQ3: What are the current barriers impeding the integration of LC and BIM in the context of sustainable built environments?
BIM-enabled information transparency and sharing enable the construction team to accurately understand design intent and requirements, leading to more efficient resource deployment and process optimization during construction. Secondly, integrating BIM and LC can significantly improve construction efficiency [12,14]; BIM can be used to simulate the construction process, identify potential problems, and optimize them in advance, reducing rework and delays [15]. Meanwhile, LC emphasizes value creation and waste elimination, and BIM technology can help construction teams better identify and reduce waste during the construction process, such as material waste [13]. In addition, this combination helps improve construction quality. Through the collision detection and quality control functions of the BIM model, the construction team can identify and solve quality problems in a timely manner before and during construction to ensure that the construction quality meets the standards [16]. Finally, BIM technology facilitates construction planning optimization to reduce resource consumption and environmental impact, while LC emphasizes energy conservation, emission reduction, and environmental protection throughout the construction process. The integration of BIM and LC thus promotes the sustainable development of the construction industry [17].
Specifically, this research makes three key contributions. First, we enhance the knowledge of the integration of BIM and LC by analyzing their interactions in the AEC industry. Second, we summarize the evolution of LC research. Third, based on the results from the integration of BIM and LC, we propose a framework of BIM-LC integration in the industry. To guide researchers in applying BIM and LC within the AEC industry, this paper comprehensively reviews the related literature from the last decade using bibliometric analysis. The current status and practical applications of BIM-LC integration are summarized from four perspectives: information integration, supply chain management, waste management, and life cycle management. Furthermore, current research gaps and future directions are identified, forming a roadmap for enhancing BIM-LC integration and expanding its applications within the sustainable built environment. This paper aims to develop a framework to guide the analysis of BIM-LC integration, which is targeted to address the above issues. Addressing this gap represents a significant contribution to the existing knowledge, as it is the first time such a framework has been proposed. The remainder of the paper is structured as follows. The next section illustrates the methodology used in the study. Section 3 is dedicated to provide a bibliometric analysis. This is followed by a detailed description of the developments in BIM-LC integration studies. Section 5 proposes a framework for BIM-LC integration, and Section 6 provides a discussion. Finally, Section 7 concludes the study by summarizing the findings and pointing out the limitations of the study.

2. Methodology

A systematic literature review is an in-depth research method employing predetermined strategies to systematically review and analyze previous studies. This research employs a scientometric methodology using CiteSpace 6.3.1 software to meet its objectives. This approach facilitates close engagement with existing publications, provides detailed insights, and fosters the development of new knowledge. Scientometric methods can construct network models by visualizing publications, citations, keywords, collaborations, and emerging topics within a specific knowledge domain. This enables researchers to conduct comprehensive, systematic, and data-driven analyses, and to identify research hotspots and emerging trends [18,19]. This approach addresses specific research questions by carefully selecting and evaluating relevant studies, synthesizing the gathered data, and presenting the findings in a structured manner that allows the researcher to draw insightful conclusions [18]. Conducting the systematic literature review involves several key steps: (1) determining research questions; (2) locating and searching relevant literature; (3) selecting studies; (4) analyzing and synthesizing data; (5) reporting and interpreting the results. A summary of the research methodology is presented in Figure 1. The first stage involves establishing research questions aligned with the objectives of the systematic literature review.

2.1. Paper Retrieval

Unrelated paper were removed from the analysis based on the following criteria. Firstly, the literature was retrieved from the core database of Web of Science (WoS) and Scopus with the following keyword combinations: “BIM” or “building information modeling” or “building information modelling” or “building information model” or “as-built model” and “lean construction”, which were published from 2010 to 2024. According to the first criterion, a total of 335 papers were retrieved. Secondly, papers not written in English, book reviews, editorials, and conference papers were eliminated, then a total of 173 journal articles were reviewed. Furthermore, journal articles typically offer more detailed and in-depth analyses of specific research questions, presenting discussions more comprehensively, making them suitable for rigorous literature reviews [20]. Thirdly, only papers in peer-reviewed English journals were included for the review with considering their impact positions in the construction research in terms of SCImago Journal Rank and H-index. As shown in Table 1, 15 journals were selected in this process. These journals have published at least one paper that fits the first criterion, and are highly ranked by construction management researchers (e.g., Mok, et al. [21]; Oppong, et al. [22]; Jin, et al. [23]). The fourth step involves screening the merged database to remove duplicate and out-of-scope studies. Irrelevance was determined by reviewing titles, abstracts, and full texts. To mitigate potential selection bias, the content of each paper was screened independently by different authors to identify those suitable for analysis. This step also encompassed complementary forward and backward snowball searches to identify missing publications relevant to the study’s scope. Following these steps, 96 papers were retained for the final review.

2.2. Review Steps

The objectives of this review were to: (1) examine applications of BIM-LC integration within the sustainable built environment, (2) describe the current status and practical applications of this integration, and (3) analyze future development trends. To achieve these objectives, the literature was examined from three perspectives: First, relevant literature was screened and comprehensively analyzed based on annual publication counts, research fields, and keyword co-occurrence analysis pertaining to BIM-LC integration; Second, the BIM-LC integration process and its current applications were described and analyzed; Third, the prospects for BIM-LC integration and its applications were discussed.

3. Bibliometric Analysis

3.1. Time Series Analysis

Figure 2 presents the annual number of articles published between 2010 and 2024, totaling 96. The data indicates that research on LC within the context of BIM emerged in 2010, exhibiting a lower growth rate between 2010 and 2017, likely attributable to the early-stage immaturity of BIM technology. Driven by national policy promotion and rapid technological advancement, which enhance construction project efficiency, publication numbers rose sharply from 2018 onwards. Despite a brief dip in 2022, a rapid recovery ensued, culminating in a peak in 2023, coinciding with the global push towards carbon neutrality targets. This trend underscores growing scholarly interest in this field over the past decade. In recent years, advancements in BIM technology have increasingly facilitated its application in achieving LC. However, research specifically addressing the application of BIM to LC within the sustainable built environment remains limited, presenting significant opportunities and challenges.

3.2. The Keyword Co-Occurrence Network

A publication’s core themes and focus can be captured through the author’s keywords, identifying prominent topics within a field. Publications addressing similar subjects are expected to exhibit strong interconnections [24]. Co-occurrence analysis of keywords reveals their relationships based on the frequency of their joint appearance within documents [25]. Consequently, mapping all keywords within a set of publications provides a reliable overview of different fields of study and topics within a particular area of interest. This research employed co-occurrence analysis based on the keywords to accurately depict the diverse research themes.
High-frequency keywords are typically regarded as indicators of research hotspots, identifying specific fields of high analytical value in bibliometrics. CiteSpace was utilized for keyword co-occurrence analysis of the 96 selected papers. The node type was set as Keywords, and the top 40 keywords with frequency were selected for co-occurrence analysis to obtain the visual word co-occurrence network. Node size corresponds to keyword frequency, arcs represent co-occurrence relationships between keywords, and line thickness indicates the strength of those relationships.
In Figure 3, high-frequency keywords associated with BIM include “BIM-based technologically enhanced workflow”, “Internet of things”, and “project management”. These technologies and concepts, integral to BIM, are crucial for BIM-LC integration, expanding BIM’s functionality and application scope. Regarding LC, high-frequency keywords such as “lean production”, “value stream analysis”, and “sustainable development” reflect its core applications in construction management. These keywords focus on enhancing efficiency and reducing waste through process and resource optimization. Furthermore, the high frequency of keywords such as “waste reduction”, “supply chain management”, and “life cycle management” indicates that BIM-LC research is expanding from single-technology applications towards broader project management. Researchers are now exploring how BIM-LC integration can achieve whole life cycle optimization and sustainable development goals in construction projects.

4. The Evolution of LC Research

4.1. The Evolutionary Stages of LC Research

Over the past two decades, significant improvements have occurred in contract relationships, project governance, and project planning and control within the construction industry. These advancements can be largely attributed to the introduction and development of LC and BIM [17]. Based on theoretical and practical developments, the evolution of LC can be categorized into four distinct stages, as illustrated in Figure 4.
In the Stage 1 (LC 1.0), the concept of LC was introduced into the AEC industry. Despite the obvious differences between the construction and manufacturing sectors, there are similarities between the two in terms of process control, resource management, and value streams. These similarities enabled the tailoring and adaptation of Lean Manufacturing principles, technologies, and tools to address the specific needs of the construction industry [26]. Applying these adapted Lean Manufacturing principles, technologies, and tools to construction aimed to maximize customer value, minimize waste, improve productivity, and effectively address industry challenges [27]. Ballard et al. [28] stabilized the work environment by “shielding” production from upstream uncertainty and variation, while optimizing downstream processes.
Construction and manufacturing differ significantly in the physical features of the product. In manufacturing, finished goods are typically movable to retailers or end customers. Construction, on the other hand, deals with larger units that cannot be transported. Additionally, the construction industry is characterized by site-based production, project uniqueness, high fragmentation, and a limited understanding of LC methods [29]. Collectively, these factors pose significant obstacles to LC promotion and application within construction.
In the Stage 2 (LC 2.0), lean management tools were gradually introduced into the AEC industry. Construction-specific lean tools and management modes gained researchers’ attention. Concurrently, diverse research perspectives on LC emerged, encompassing sustainability, BIM, integrated project delivery (IPD), and the lean project delivery system (LPDS) [30]. At this stage, BIM functioned primarily as a visualization tool, represented by intelligent 3D models. Gonzalez et al. [31] applied the Last Planner System (LPS) for project planning and control in a residential construction project located in Santiago, Chile. The study introduced two new indicators, PRI and PPI, to measure LPS effectiveness. The results indicated that improving planning reliability can significantly enhance project performance.
Stage 3 (LC 3.0) witnessed BIM evolving into a platform integrating various tools and systems, enabling digital management of information flows, building data, and construction processes [32]. BIM transitioned into a collaborative platform, effectively integrating with lean tools like LPS and Information and Communication Technology (ICT). This platform supports all stakeholders to work concurrently during the project planning and execution phases. Through methods such as clash analysis, design review, project planning, and scheduling, it optimizes processes and minimizes delays to the greatest extent [33].
Concurrently, the rapid development of prefabricated construction fostered Lean Prefabricated Construction (LPC), which utilizes LC techniques and tools for real-time tracking and control of modular and off-site progress, enabling continuous optimization [34]. LPS serves as an effective means to realize industrialized construction, promoting energy efficiency and low-carbon emissions [35]. Moreover, the synergistic nature of BIM-LC integration improves construction processes, reduces waste, and significantly enhances sustainability potential.
In the fourth stage (LC 4.0), under the digital transformation of the AEC industry, LC has been further advanced through the integration of advanced technologies like BIM, Artificial Intelligence (AI), and the Internet of Things (IoT). For example, digital twins (DT) creates a virtual replica of the project to enable real-time monitoring and optimization of project operations. AI intelligently analyzes data and optimizes decision-making processes. Through the synergy of these technologies, LC maximizes construction productivity and enables digital management of the entire construction production lifecycle [36].
A keyword timeline view (Figure 5) was generated based on relevant publications from 2010 to 2024. The visualization reveals that post-2010, “building information modeling” emerged as a central keyword, frequently co-occurring with terms like “lean construction”, “project management”, and “last planner system”. This indicates that BIM gradually evolved from a visualization tool in the 2.0 stage into a digital collaboration platform, integrated with tools such as LPS to enhance collaboration, streamline processes, and optimize resource allocation in order to improve project success rates, marking the transition to the LC 3.0 stage. Additionally, keywords like “information technology”, “supply chain management”, and “collaboration” began emerging, reflecting research expansion into more complex collaborative systems.
After 2018, the appearance of advanced high-tech keywords such as “digital twins”, “decision making”, and “integrated project delivery” indicates that research has entered the LC 4.0 stage. In this phase, LC is deeply integrated with BIM, IoT, AI, and DT technologies, enabling real-time optimization and intelligent decision-making across the entire project lifecycle. Concurrently, the increasing prominence of keywords like “construction waste” and “facility management” reflects a growing research focus on BIM-LC contributions to sustainable development, waste management, and lifecycle-based project management.

4.2. The Key Dimensions of LC Research

By analyzing the selected 96 selected papers, this paper explores the main research directions of LC in the AEC industry from the following four dimensions: information integration, supply chain management, waste management, and life cycle management, as shown in Figure 6.

4.3. The Four Applications of LC Tools

Over the past decade, the promotion of LC in the AEC industry has prompted scholars to pay attention to the application of LC methods and tools. Table 2 lists the primary LC methods applicable to the AEC industry.

5. A Framework of the Integrated BIM-LC

To enable the effective synergy between LC and BIM in sustainable built environment, an integrated framework has been developed, as shown in Figure 7. The proposed framework includes four key dimensions of integration: information integration, supply chain management, waste management, and life cycle management. Each dimension is supported by specific technologies and methods. This framework serves as a strategic guideline to help understand how the integrated BIM-LC can address common challenges in the AEC industry, such as inefficiency, waste, and fragmented data flows.

5.1. Information Integration

Due to the complexity of technology, ongoing changes in supply chain management systems, enhanced contract terms, and the urgent need for smart and green buildings [37], data management in the construction industry has become increasingly complicated [38]. Meanwhile, BIM is an effective tool to enhance communication and collaboration among major players in the AEC industry [39], which has significant benefits for information integration and collaboration.
The promotion and implementation of BIM have greatly accelerated the development of the AEC industry and provided possibilities for the integration of new technologies [40]. BIM can significantly enhance project productivity and efficiency when combined with LC [41], primarily reflected in three aspects: real-time data-driven processes, visualized collaboration, and automated decision-making. In terms of real-time data-driven, Teizer et al. [42] proposed BIM-IoT-LC methodology allows for the construction of real-time data sets, improving the effectiveness of data and information rotation. In order to accurately track and match the supply status of dynamic field demand and materials, Chen et al. [43] built an integrated BIM-RFID database system that integrates material demand information to a look-ahead plan. To enable multi-dimensional content viewing and collaboration, based on LC principles, BIM integrates with visualization tools such as XR [44] and AR [45] to enable more efficient and effective project management. In terms of optimizing processes and decision-making, Heigermoser et al. [40] proposed a construction management tool, which combined LPS and BIM, integrated the construction data in all directions, and performed automatic engineering quantity calculation, 4D construction simulation, manpower allocation, waste quantification and so on. Sbiti et al. [46] developed a system that integrates BIM and LPS, which automatically generates phase plans by combining BIM data with the Work Breakdown Structure (WBS) database.
Through the synergy of BIM and lean concepts, accurate modeling, collaboration, design and construction information from various disciplines throughout the project life cycle can be integrated [47]. Regarding BIM as an information sharing platform, Michaud proposed a lean approach to optimize BIM information flow, and the virtual integration of information among project stakeholders would alleviate the problem of process fragmentation [48]. Situating BIM as a key technology for LC, Barkokebas et al. [49] proposed a BIM-LC framework applied to off-site construction. This framework integrates BIM with other information systems to store and share inter-departmental data in real time, while applying LC to optimize off-site construction practices and digital functions, enabling continuous information flow and ongoing project improvements.

5.2. Supply Chain Management

The construction industry has long faced issues such as low productivity, non-value-added activities, and significant waste, primarily due to the fragmentation of the value chain, the large number of stakeholders, and the inherent complexity of projects [50]. LC practices have significantly streamlined the entire construction supply chain (CSC) workflow, greatly improved CSC efficiency while eliminating waste and adding more value [51,52,53,54].
The integration of LC with information technology, particularly the introduction of BIM, has become a key driver of CSC development [55]. The concept of the integrated BIM-lean supply chain (BIM-LSC) has gradually gained widespread attention and recognition in the industry and has become a hot research topic [56]. BIM helps improve CSC at multiple levels, such as shortening design and development cycles, reducing rework, improving the predictability of investment and lifecycle costs [57], sharing lifecycle information [54], and improving activity scheduling and planning [6] to maximize value delivery and reduce waste [51]. More importantly, BIM can help achieve communication and collaboration across multiple supply chain layers [58], enhance the flexibility to respond to complex supply chain requirements, promote the sustainability of construction projects, and promote lean supply chain integrated management [59,60]. The versatility and scalability of BIM-LC, extending from 3D to nD modeling, enables flexible representation of CSC projects facing multiple challenges. Utilizing automated data collection, nD models enable dynamic virtual analysis of various issues, including scheduling, cost, stability, sustainability, maintainability, and safety. They provide real-time data on prefabricated components [61], empowering companies to rapidly respond to complex supply chain demands and market changes [62].
Furthermore, BIM-LSC can support strategic, tactical, and operational goals of CSC [54]. Zhang et al. [56] proposed a model to assess the reliability of the BIM-LSC approach, which improves the accuracy of BIM-based supply chain reliability analysis and forecasting in uncertain environments. Le PL et al. [63] proposed a framework based on BIM and lean concepts in supply chain management, providing recommendations for CSC decisions at each stage. As a collaborative fusion of technological advancement and process optimization, BIM-LSC enhances construction supply chain management efficiency, contributes to achieving socio-economic and environmental sustainability goals, and supports the construction industry’s green transformation [56].
Under the background of lean, the integration of BIM and other technologies can better realize supply chain management. For example, Deng et al. [64] combined lean principles to develop an integrated framework based on 4D BIM and Geographic information systems (GIS). The proposed framework was designed for coordinating transportation collaboration of construction supply chains between construction project sites and other related locations. To simulate the process of prefabricated housing project (PHP) from production and logistics to field assembly, Li et al. [65] proposed RFID/BIM/Lean-PHP (RBL-PHP) simulation game through the integration of RFI-supported BIM platform and LC, which is instructive for supply chain practitioners. Furthermore, Chen et al. [43] constructed an integrated BIM-RFID database system that can accurately track and match dynamic field demands and the supply status of materials for better supply chain management.

5.3. Waste Management

The construction industry has long been plagued by issues such as non-value-added activities, significant resource wastage, and negative environmental impacts, which have attracted considerable public attention [10]. With the introduction of the “dual carbon” targets and the green transformation of the construction industry, significant innovations, including BIM and LC, have been adopted to improve production efficiency while reducing waste [3,66].
On the one hand, LC promotes BIM adoption by enhancing stakeholder communication and collaboration, thereby improving construction project efficiency and reducing waste. On the other hand, BIM is widely applied throughout the project lifecycle, supporting project visualization, scheduling, communication, and team collaboration, thus providing technological support for the implementation of LC [10]. However, the use of BIM alone still presents certain challenges, such as insufficient accuracy of information, collaboration issues, communication gaps, and unclear requirements [67], preventing its full potential from being realized. Similarly, relying solely on LC is insufficient to achieve lean objectives, such as waste elimination and value enhancement [68]. To fully realize the potential benefits of BIM and lean methods, BIM and LC must be integrated and used collaboratively within projects [69].
Numerous studies have shown that the synergy between lean and BIM can enhance productivity and efficiency [70] while reducing resource waste and construction debris [10,13,71], with these benefits spanning the entire process from design to construction.
In the design phase, BIM is used as a lean tool to minimize construction and design waste by eliminating design errors detected during construction through design reviews and clash detection [14]. Gbadamosi et al. [72] integrated the principles of design for manufacturing and assembly (DFMA), BIM, and LC to develop a design evaluation system for design optimization, which enables efficient material selection, waste minimization, and rapid project delivery. Herrera et al. [69] designed a BIM usage assessment (BUA) tool to identify and analyze how BIM improves the design process in lean design management (LDM) through design reviews, design creation, visualization, and clash detection, ultimately reducing waste in the construction industry.
In the construction phase, frameworks combining LC tools and BIM have been proposed and validated for waste management applications in real-world contexts. For example, Heigermoser et al. [40] proposed a building management tool that integrates LPS and 3D visualization, aiming to increase productivity and reduce construction waste, with proven effectiveness. Mandujano et al. [73] reviewed extensive literature on virtual design and construction (VDC) and LC, showcasing the benefits of applying LC in VDC and providing examples of waste reduction and opportunity improvements through lean methods.

5.4. Life Cycle Management

Currently, the traditional fragmented management and data silos in the construction industry lead to low production efficiency and high resource waste. The global construction industry is seeking to improve overall efficiency throughout the entire project lifecycle. As advanced concepts and tools in the construction industry, LC and BIM are key components in this pursuit [74]. Through their collaborative integration at various stages, LC and BIM reduce waste, improve construction efficiency, and create maximum value. BIM-LC brings a fresh perspective and practice to the management of the entire building lifecycle [75].
The design phase is one of the most critical stages of a construction project [76], as it determines the building structure, material selection, process flow, and technical implementation. During the design phase, BIM-LC integration enables the design team to share project data in real-time. Through virtual modeling and clash detection, design errors and omissions are reduced, rework is avoided, and design and construction plans are optimized. Waste in the design process is identified and eliminated [14]. In the construction phase, by combining BIM models with LC tools, the project team can plan and schedule resources more accurately, while also tracking construction progress in real-time [6]. BIM-LC integration also plays an important role in the operation and maintenance (O&M) phase of a building. BIM provides comprehensive lifecycle data support, which can be used for data collection, energy consumption monitoring, and proactive maintenance.
By integrating BIM and LC throughout the entire lifecycle of a construction project, BIM-LC effectively achieves sustainability goals, reducing waste while improving the functionality and value of buildings. Mellado et al. [11] combined BIM, LC, and sustainability to propose a comprehensive management framework (BLS). Typically, sustainability approaches focus more on the design and operational phases, while LC is primarily concerned with the construction phase. By integrating these three elements into a unified system, BIM-LC enables collaborative management across the project lifecycle, enhancing synergies between them and driving improvements in sustainability, efficiency, and value of the construction project. Similarly, Moradi et al. [77] combined BIM, LC, and sustainability to develop a project delivery framework that supports the achievement of sustainable development goals (SDG) in the field of zero/low-energy buildings. Additionally, with the rapid development of technologies such as DT [78], AI, IoT [79], and blockchain, BIM-LC, through integration with these intelligent technologies, enables improvements from LC management to entire building lifecycle management, providing new momentum for the digital transformation and sustainable development of the construction industry.

6. Discussion

The integration of BIM and LC presents transformative potential for advancing sustainable construction practices. However, this synergy faces multifaceted challenges that must be addressed to unlock its full benefits. This section critically examines the technical and application barriers and proposes actionable pathways for future research and implementation.

6.1. Technical Challenges in BIM-LC Integration

6.1.1. Limited System Interoperability

The primary technical hurdles stem from the inherent differences in BIM and LC paradigms. BIM operates at a micro-level, emphasizing detailed geometric and semantic data, while LC focuses on macro-level process optimization. This misalignment complicates data interoperability, as LC tools like LPS require streamlined and process-oriented inputs rather than granular BIM data. Ensuring effective integration and data transmission between LC tools and BIM platforms is crucial. However, BIM and LC tools typically operate within different software ecosystems. For example, BIM models are commonly developed using platforms such as Autodesk Revit or Bentley, whereas LC tools like LPS are often based on Excel, specialized web applications, or other lightweight systems. This fragmentation at the tool level hinders seamless data integration, particularly in areas such as communication, schedule control, and resource coordination. To overcome this, the development of cross-platform middleware or API is essential to enable smooth data flow and exchange, thereby improving compatibility across heterogeneous systems. Additionally, the asynchronous update cycles between LC tools and BIM platforms limit real-time synchronization, increasing the risk of delayed safety alerts [36].

6.1.2. Data Inconsistency and Semantic Gaps

A critical gap lies in the bidirectional flow of information. Current integrations often prioritize one-way data extraction (e.g., using BIM for visualization in LC planning), limiting holistic optimization [40,46]. LC reports often contain large volumes of textual descriptions, whereas BIM systems primarily support structured numerical data. This inconsistency in data formats significantly increases the likelihood of errors during data transformation. Additionally, the lack of standardized semantic models for LC impedes data mapping across platforms (e.g., [49]). For instance, a geometric attribute in a BIM model cannot be automatically translated into a corresponding “construction task” in LC processes. This issue is particularly critical in large-scale projects, where it poses a major barrier to automation and intelligent project execution. While frameworks like BIM-LC attempt to bridge this gap, their reliance on third-party platforms introduces inconsistencies in data formats and computational inefficiencies. Future efforts should prioritize unified semantic models aligned with Industry Foundation Classes (IFC) and enhanced bidirectional data exchange.

6.1.3. Data Privacy and Security

The integration of BIM and LC involves extensive data sharing across multiple platforms and stakeholders, covering areas such as design, construction, workforce management, and resource allocation. Such data sharing inevitably raises significant privacy and security concerns. It is essential to implement advanced encryption algorithms to protect both data in transit and at rest, and to deploy multi-factor authentication mechanisms and role-based authorization strategies to ensure that data handling complies with applicable data protection regulations [36]. However, the lack of a unified data governance framework, including standardized access control, encryption protocols, and regulatory compliance measures, remains a major barrier to the practical adoption of BIM-LC integration in real-world projects.

6.2. Application Challenges in BIM-LC Integration

6.2.1. Stakeholder Resistance

The integration of BIM and LC is not only a technological innovation but also a transformation of organizational behavior and management culture. Resistance to change represents a significant challenge. Traditional mindsets and practices continue to dominate the construction industry, and some project teams lack sufficient understanding of BIM and LC methodologies, particularly in the early stages of planning and design. This unfamiliarity leads to hesitation in adopting lean practices, or results in superficial and symbolic implementation. These practices are often perceived as high-risk with uncertain returns, further hindering widespread adoption of BIM-LC [80]. When the stakeholders involved in the project fail to provide sufficient collaboration, this issue becomes even worse [5].

6.2.2. Lifecycle Management

Despite theoretical support for end-to-end integration, practical applications remain fragmented. Most studies focus on isolated phases (e.g., design clash detection or construction scheduling) rather than holistic lifecycle management [10,69]. For instance, although post-construction feedback mechanisms are crucial for the continuous improvement of LC, they are rarely integrated with the BIM’s operational data. This leads to a lack of effective closed-loop feedback in the later stages of the project. Future frameworks should emphasize circular economy principles, extending waste reduction strategies to demolition and material reuse phases.

6.2.3. Supply Chain Management (SCM)

While BIM-LC integration improves material tracking and logistics [51,56], dynamic disruptions (e.g., transportation delays) often undermine real-time systems like BIM-RFID [43,65]. Adaptive, AI-driven SCM frameworks could enhance resilience by predicting disruptions and optimizing contingency plans.

6.2.4. Waste Management

Although BIM-LC integration reduces waste through clash detection and process simulation [10,14], quantification metrics lack alignment with global sustainability benchmarks (e.g., UN SDGs). Standardized metrics for waste reduction, carbon emissions, and energy efficiency are urgently needed to validate environmental impacts of BIM-LC integration.
To address the above challenges, the successful integration of BIM and LC requires close collaboration between governments, construction companies, educational institutions, and software developers. Governments should take the lead in formulating unified data formats and interface standards between BIM and LC systems, such as semantic models aligned with IFC, to ensure full interoperability across different software platforms [80]. At the same time, governments should encourage developers to provide open API access, facilitating the creation of a highly connected technology ecosystem. To address data privacy and security issues, the BIM-LC integration platform must have features such as data encryption, authentication, multi-level, and role-based authorization, and clearly defined industry security thresholds [36]. In addition, the government should focus on promoting the BIM-LC integration approach, such as promoting pilot projects or offering tax incentives, to encourage more construction companies to adopt it. Collaborating with educational institutions and industry associations to cultivate more technical talent and enhance employee skills is essential [81,82]. Establishing institutional knowledge and improving technical competence is crucial for the successful implementation of BIM-LC [44]. Finally, promoting end-to-end lifecycle management in engineering projects by incorporating “information asset delivery” into project acceptance agreements, promoting circular economy principles, and implementing carbon tax incentives, will encourage companies to extend lean waste reduction strategies to the demolition and material reuse stages, contributing to the construction industry’s carbon neutrality goals.

6.3. Measurable Performance Indicator

In order to systematically evaluate the effectiveness of BIM-LC integration in practical applications, some performance indicators can be suggested to support quantitative assessment in actual project applications (shown in Table 3).

7. Conclusions

This study presents a systematic literature review of BIM-LC integration in sustainable built environments, employing bibliometric analysis and critical synthesis of 96 core journal articles (2010–2024). The analysis reveals that while BIM-LC integration has gained substantial research momentum, particularly in four key domains, information integration, supply chain management, waste reduction, and lifecycle management, current research exhibits significant fragmentation across project phases and persistent technical barriers. Critical challenges include data interoperability limitations between micro-level BIM systems and macro-level LC processes, siloed lifecycle management implementations, and the absence of standardized sustainability metrics aligned with global benchmarks.
The contribution of this article lies in three aspects. First, the progression from LC 1.0 (adoption of lean manufacturing principles) to LC 4.0 (integration with AI, IoT, and DT) highlights the growing synergy between LC and digital tools like BIM. Second, BIM-LC integration demonstrates significant potential in four areas, information integration, supply chain management, waste reduction, and lifecycle management, though practical implementation often lags behind theoretical frameworks. Third, technical barriers (e.g., data interoperability) and application gaps (e.g., fragmented lifecycle management) remain to be addressed. Addressing these requires unified semantic models, advanced technologies (e.g., DT), and policy support.
Despite its contributions, this study has limitations. The review is confined to English-language journals indexed in Scopus and WOS, potentially excluding non-English publications, gray literature (e.g., industry reports), and emerging empirical studies. Additionally, keyword-based selection may have omitted relevant works. Future research should broaden the scope to include diverse sources and empirically validate the proposed framework through real-world case studies. Furthermore, integrating emerging technologies, such as DT for real-time process simulation and AI for predictive supply chain analytics, should be prioritized to enhance the framework‘s adaptability and decision-making capabilities in sustainable built environments.
Based on the above discussion, future research should prioritize the following areas:
  • Enhanced Interoperability: develop LC-specific ontologies using semantic web technologies (e.g., RDF) to align with BIM standards like IFC.
  • Integration with Emerging Technologies: leverage DT for real-time process simulation and AI for predictive analytics in SCM.
  • Lifecycle-Oriented Frameworks: expand BIM-LC integration to encompass demolition and circular economy practices.
  • Standardized Sustainability Metrics: establish quantifiable indicators (e.g., waste-to-value ratios) to better align BIM-LC workflows with global sustainability goals.
  • Policy and Collaboration: advocate for government mandates on BIM-LC interoperability standards and incentivize IPD models to foster stakeholder collaboration.

Author Contributions

Conceptualization, Y.Y.; Methodology, Y.Y.; Formal analysis, C.C. and X.L.; Writing—original draft preparation, Y.Y. and C.C.; Writing—review and editing, Y.Y. and X.L.; Project administration, Z.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Natural Science Foundation of China (Grant No. 71673240 and 42271179) and the Major National Social Science Programs of China (Grant No. 24&ZD081), and funded by Center for Balance Architecture, Zhejiang University.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Steps to search for papers in the WoS and Scopus core collection database.
Figure 1. Steps to search for papers in the WoS and Scopus core collection database.
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Figure 2. Number of relevant papers published in each year between 2010 and 2024.
Figure 2. Number of relevant papers published in each year between 2010 and 2024.
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Figure 3. Keywords co-occurrence map.
Figure 3. Keywords co-occurrence map.
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Figure 4. The goals development of LC.
Figure 4. The goals development of LC.
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Figure 5. Timeline view.
Figure 5. Timeline view.
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Figure 6. Key applications of LC.
Figure 6. Key applications of LC.
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Figure 7. Framework of the integrated BIM-LC.
Figure 7. Framework of the integrated BIM-LC.
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Table 1. Distribution of the selected papers among different journals.
Table 1. Distribution of the selected papers among different journals.
Journal TitleNumber of Selected Papers
Buildings17
Automation in Construction16
Engineering, Construction and Architectural Management15
Sustainability13
Journal of Construction Engineering and Management9
Construction Innovation-England7
International Journal of Lean Six Sigma4
Canadian Journal of Civil Engineering3
Journal of Cleaner Production3
Journal of Civil Engineering and Management2
Journal of Building Engineering2
Journal of Management in Engineering1
Ain Shams Engineering Journal1
Developments in the Built Environment1
Computer-Aided Civil and Infrastructure Engineering1
Table 2. The efficacy of LC tools in four applications.
Table 2. The efficacy of LC tools in four applications.
ToolsInformation
Integration		Supply Chain
Management		Waste
Management		Life Cycle
Management
5s onsite management√ √√
Justin-time (JIT)√√√√
Value based management (VBM)or
value stream mapping (VSM)		√ √
Concurrent engineering (CE)√√
Lean Six Sigma √
Prefabrication √√
Virtual design construction (VDC)√√ √
Integrated project delivery √ √
Target value design (TVD) √
Last planner system (LPS) √
Benchmarking √
Pull scheduling/planning√ √√
Kanban system√ √
Total quality management (TQM)√ √
Continuous flow (CF) √√
Table 3. Measurable performance indicator.
Table 3. Measurable performance indicator.
DimensionPerformance Indicators Measurement Focus
EconomicCost Saving Indicator
Budget Deviation Index		Measures avoided costs [83] and budget accuracy [84]
Environmental
Sustainability		CDW Generation Rate/Quantity
CDW Recycling Rate
Total Carbon Emissions
Carbon Emission Intensity (CEI)		Tracks waste reduction [85], recycling efficiency [85,86], and carbon footprint per unit area [10,87]
QualityDefect Rate (DR)
Zero Defect Rate
Compliance Metrics
BIM Model Average Quality Score (AQS)		Quantifies defects [88,89,90], regulatory adherence [91], and BIM model accuracy/consistency for decision-making [92]
SchedulePercent Plan Complete (PPC)
CFI Index
Time Savings
Delays Avoided		Evaluates on-time task completion [34,65,93], process efficiency [93], reduced cycle time, and avoided rework delays [84]
Technology
Innovation		Data Interoperability
Technology Integration Index		Assesses data-sharing efficiency and integration depth with emerging tech (e.g., DT [78], blockchain [94], and AR/XR [44])
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Yang, Y.; Chen, C.; Liu, X.; Zhang, Z. Integration of Lean Construction and BIM in Sustainable Built Environment: A Review and Future Research Directions. Buildings 2025, 15, 2411. https://doi.org/10.3390/buildings15142411

AMA Style

Yang Y, Chen C, Liu X, Zhang Z. Integration of Lean Construction and BIM in Sustainable Built Environment: A Review and Future Research Directions. Buildings. 2025; 15(14):2411. https://doi.org/10.3390/buildings15142411

Chicago/Turabian Style

Yang, Yingnan, Chunxiao Chen, Xin Liu, and Zhicheng Zhang. 2025. "Integration of Lean Construction and BIM in Sustainable Built Environment: A Review and Future Research Directions" Buildings 15, no. 14: 2411. https://doi.org/10.3390/buildings15142411

APA Style

Yang, Y., Chen, C., Liu, X., & Zhang, Z. (2025). Integration of Lean Construction and BIM in Sustainable Built Environment: A Review and Future Research Directions. Buildings, 15(14), 2411. https://doi.org/10.3390/buildings15142411

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