Bridging BIM maturity with emerging paradigms: understanding the role of industry 4.0 and sustainability in the digital transformation of construction

PurposeThis study develops an innovative building information modelling (BIM) maturity model integrating Industry 4.0 (I4.0) and sustainability principles. It addresses the need to consider sustainable practices to guide digital transformation in construction.Design/methodology/approachThe research employs design science research (DSR), combining literature analysis with practical model development through an iterative process. This includes semi-structured interviews and focus groups with eight international experts, ensuring theoretical rigour and practical applicability. The study considers the implications of disruption on human interaction with BIM and I4.0 technologies.FindingsThe study identifies six key dimensions (processes, technology, people, organization/strategy, policy and sustainability) and six maturity levels for assessing BIM implementation in I4.0 and sustainability contexts. A systematic evaluation framework highlights critical improvement areas, including training needs and strategies to fight resistance to change. Additionally, 42 critical success factors aligned with dynamic capabilities and cumulative capability development theories are identified.Originality/valueThis paper presents a novel BIM maturity model uniquely integrating I4.0 and sustainability principles. This comprehensive approach addresses technological advancements and sustainable practices, filling a gap in current BIM maturity assessments. It considers BIM’s future in a disruptive industry, addressing challenges of human-technology interaction and providing a roadmap for evolving organizational capabilities in construction.

Despite the benefits of Building Information Modelling (BIM), the adoption level of BIM remains much lower than expected. Construction companies should appraise the existing condition in the BIM implementation to ascertain the applicable progress avenues that fit the user’s traits. To achieve this aim, the objectives of this paper are i) to identify the trends of BIM maturity studies ii) to conceptualise what is BIM maturity; iii) to identify the existing models of BIM maturity iv) to identify the indicators for measuring BIM maturity in the company, the project and the industry. A systematic review was conducted on BIM maturity articles, published in the Scopus database from 2008 to April 2018. The results reveal that most BIM maturity studies are dominated by authors from the United Kingdom and the United States, but the top three authors highly-cited were from Australia, Canada and the United Kingdom. The results highlight four aspects in the conceptualisation of BIM maturity: quality of use, the extent of use, the context of use and stages of the processes. The four most frequently quoted BIM maturity models are the National BIM Standard Capability Maturity Model, BIM maturity, BIM proficiency matrix and BIM implementation models. The results revealed seven major indicators for assessing BIM maturity namely information, people, policy, process, technology, organisation and BIM output. The findings advance the practitioners’ understanding of important indicators that must be considered to initiate or increase the BIM maturity levels in their respective companies or projects.

ABSTRACTBuilding information modelling (BIM) has been adopted with increasing frequency by the construction industry in the last few years due to its potential to enhance construction business performance. While there is a general belief that higher BIM proficiency will lead to higher business performance, few empirical studies have tested this relationship. This research explores the extent to which a positive relationship exists between BIM adoption and organisational learning. The impact of BIM maturity and years of experience on the absorptive capacity (AC) of contractors to adopt new information for organisational learning is investigated through a survey of Australian building contractors. While BIM experience was found to be a significant predictor for contractor AC, the analysis of variance showed no significant relationship between BIM maturity and AC. The literature indicates a pervasive belief in a potent relationship between BIM maturity and organisational learning, yet it seems that factors traditionally viewed as more peripheral play a bigger role than expected in determining the impact of BIM on learning and business performance. Subsequent interviews found that (1) poor business ties, (2) willingness to share information and (3) organisational cultural values weaken the expected relationship between BIM maturity and AC. The results suggest that the extent of an organisation's experience with BIM is a greater predictor of learning performance than the complexity of BIM usage within the organisation. The main contribution of this paper is to reveal the complexity surrounding the relationship between BIM and business performance.

Technologies like Artificial Intelligence (AI), the Internet of Things (IoT), cloud computing, and big data analytics are converging and leading the construction industry to a transformation towards digitization and enhancing construction efficiency. At the centre of this evolution sits Building Information Modeling (BIM), transforming from rudimentary 3D modeling tools to a holistic building lifecycle management tool. This article presents a literature review of AI applications in BIM with a focus on how machine learning, deep learning, reinforcement learning, generative adversarial networks, natural language processing, and computer vision reshape the construction industry. AI has been integrated with BIM to improve project efficiency, minimize mistakes, enhance resource allocation, and transition towards a more sustainable practice. This review also highlights current technical obstacles causing the delay of projects such as the pilot studies based on AI-enhanced BIM in the field and future research directions liaising interdisciplinary infrastructure with IoT, blockchain, augmented reality, etc. The article concludes by discussing the gradual co-evolution of adaptive artificial intelligence systems and BIM, concluding that innovation in sustainable development must always be nurtured.

Physical assets are, nowadays, more and more included in the digital environment, providing huge amount of data, and involving a complex network of stakeholders. Many Information Communication Technologies (ICTs) are employed in Architecture, Engineering, Construction and Operation (AECO), in order to tackle the digital transformation. Currently, one of the most acknowledged approaches for managing the new complexity of the built environment is Building Information Modelling (BIM). This article addresses the issue of the maturity of organisations, which adopt or are willing to adopt a BIM approach. Therefore, research aims at providing a critical review on BIM maturity of organisations operating in AECO. The BIM approach can be considered a step forward for supporting the development of digital processes able to foster the achievement of their business objectives. The scope of the research concerns the overall dynamics of the AECO sector concerning the digital revolution affecting management of the built environment processes along the life cycle of physical assets. Therefore, a literature review on Scopus databases has been carried out and most relevant dynamics in the literature production have been identified and investigated trough bibliometric, trend and cluster analyses carried out on the selected sample of articles. In summary it can be stated that the BIM maturity allow to evaluate organisations’ digitalisation potential enabling the reengineering of business processes. Moreover, the evaluation of organisations’ BIM compliant approaches can provide a sound assessment method during a bid process, contributing to the transparent and effective selection of the most virtuous firms.

The paradigm shift in the construction industry from 2D to Building Information Modelling (BIM) presents unforeseen challenges for new entrant construction industries. Experiences from advanced industry users of BIM shape the directions for future use. In Malaysia, BIM maturity is fast appreciating with increasing demand for efficiency and competitive advantages. However, adoption rate encounters resistance from several factors highlighted in previous research: people, process and technology. To improve on Information technology (IT) adoption models factors such as business process re-engineering, computer integrated construction and BIM adoption were considered for this research. This paper represents findings of an ongoing research, presenting the designed questionnaire to access perception of construction industry professionals (Architects, Quantity Surveyors, Engineers and Contractors) knowledge on BIM softwares and BIM attributes. Responses were derived from 120 construction professionals in the pilot phase of the research. The data is analyzed using SPSS for a descriptive overview of the most prominent BIM software usage. Smart PLS was utilized to analyze the path coefficient effects of each variable in the model. The Cronbach Alpha derived fell within an agreeable minimum threshold of above 0.60. The factors loaded appropriately to each variable. The path coefficient revealed people perception had the highest effect on collaborative processes, business process re-engineering (BPR) had the highest effect on BIM adoption and model variance R2 explained 24.6% of BIM adoption. The results will demonstrate the current state of BIM adoption in Malaysian construction industry complimenting current efforts to improve BIM awareness. At this stage, future research focuses on developing the second phase of the model and recommends towards extending and redefining the model with other mediating variables.KeywordsBuilding Information Modelling (BIM)Construction IndustryInformation TechnologyMalaysiaPartial Least Square (PLS)

In the recent decade, there has been a significant increase in the number of maturity models offered in Building Information Modelling (BIM). However, several problems exist, such as no proper criteria for model choice for organisations and no adequate understanding of BIM maturity model (BIMMM) application areas. Thus, a systematic literature review (SLR) was undertaken using 32 papers published between 2010 and 2021, directed with a descriptive and content analysis, following the PRISMA standards. The results of this paper extend the knowledge on BIMMM development, application and validation. BIMMM development has always been initiated with a literature review on existing maturity models. National BIM Standard’s Interactive Capability Maturity Model is the most dominant base for developing and applying BIMMMs. However, the literature lacks applications and validation of mainstream models. The application of BIMMMs is mainly focused on assessing BIM performance, while a few studies tried to explore new avenues such as applying BIMMMs to other contexts, finding the relationship between maturity level and other factors, and understanding the impact of BIM maturity level on factors like project performance. Despite interviews and case studies being popular methods of model validation, doubts on the validity of the models have been raised due to the dearth of information on how most of the models were validated. The results of the study lead future research in the BIMMMs and inform the development and application of valid BIMMMs in practice.

The present study uses a bibliometric and systematic literature review (SLR) to examine the use of Building Information Modeling (BIM), the Internet of Things (IoT), and Digital Twins (DT) in the construction industry. The network visualization and other approaches based on the Web of Science (WOS) database and the patterns of research interactions were explored in 1879 academic publications using co-occurrence and co-citation investigations. Significant publications, conferences, influential authors, countries, organizations, and funding agencies have been recognized. Our study demonstrates that BIM, IoT, and DT in construction, Heritage BIM (HBIM), Smart Contracts, BIM, and Ontology, and VR and AR in BIM and DT are the main study themes. Finally, several prospective areas for future study are identified, including BIM and Metaverse technology, BIM and Artificial Intelligence (AI), Metaheuristic algorithms for optimization purposes in BIM, and the Circular Economy with BIM and IoT.

Building information modelling (BIM) offers a powerful means to enhance collaboration and efficiency in construction project delivery. However, many organisations still face persistent technical, organisational, and environmental challenges during implementation. BIM maturity has emerged as a key factor in addressing these issues, yet few studies have empirically examined how maturity influences the ability to manage such challenges. This study investigates how BIM maturity affects implementation challenges from the perspective of UK construction contractors. The research adopted a quantitative approach using a structured questionnaire administered to 65 professionals from UK contracting organisations. The survey measured BIM maturity across technology, process, and policy domains and examined how organisations manage common implementation challenges. The analysis employed descriptive statistics, Spearman’s rank correlation, and independent-sample t-tests. Findings reveal that most organisations operate at Capability Stage 2, with moderate maturity across key BIM areas. Technological maturity, especially in software use, ranked highest. Organisations with higher BIM maturity managed challenges more effectively, although the correlation was moderate. These results underscore the value of assessing and developing BIM maturity as a strategic tool for overcoming barriers. Practically, construction firms can use maturity assessments to identify gaps, prioritise improvements, and enhance BIM implementation success across their projects.

Building Information Modelling (BIM) is an expanding collection of concepts and tools which have been attributed with transformative capabilities within the Architecture, Engineering, Construction and Operations (AECO) industry. BIM discussions have grown to accommodate increasing software capabilities, infinitely varied deliverables, and competing standards emanating from an abundance of overlapping definitions attempting to delineate the BIM term. This chapter will steer away from providing its own definition of BIM yet concurs with those identifying it as a catalyst for change (Bernstein, 2005) poised to reduce industry’s fragmentation (CWIC, 2004), improve its efficiency (Hampson & Brandon, 2004) and lower its high costs of inadequate interoperability (NIST, 2004). In essence, BIM represents an array of possibilities and challenges which need to be understood and met respectively through a measurable and repeatable approach. This chapter briefly explores the multi-dimensional nature of the BIM domain and then introduces a knowledge tool to assist individuals, organisations and project teams to assess their BIM capability, maturity and improve their performance (Figure 1). The first section introduces BIM Fields and Stages which lay the foundations for measuring capability and maturity. Section 2 introduces BIM Competencies which can be used as active implementation steps or as performance assessment areas. Section 3 introduces an Organisational Hierarchy/Scale suitable for tailoring capability and maturity assessments according to markets, industries, disciplines and organisational sizes. Section 4 explores the concepts behind ‘capability maturity models’ and then adopts a five-level BIM-specific Maturity Index (BIMMI). Section 5 introduces the BIM Maturity Matrix (BIm³), a performance measurement and improvement tool which identifies the correlation between BIM Stages, Competency Sets, Maturity Levels and Organisational Scales. Finally, Section 6 introduces a Competency Granularity Filter which enables the tailoring of BIM tools, guides and reports according to four different levels of assessment granularity.

– This review explores the integration of digital innovation and sustainability within the construction industry, highlighting key technological advancements that are reshaping traditional practices. Technologies such as Building Information Modeling (BIM), Internet of Things (IoT), Artificial Intelligence (AI), digital twins, 3D printing, robotics, drones, and blockchain have emerged as pivotal tools to enhance project efficiency, safety, and environmental responsibility. The review underscores the benefits of digital transformation, including improved data management, automation, waste reduction, energy efficiency, and lifecycle assessment, while identifying challenges related to adoption barriers, interoperability, and skills gaps. Through comprehensive analysis of recent literature, this study offers insight into how digital solutions contribute to sustainable construction by optimizing resource use, reducing carbon footprints, and fostering collaboration among stakeholders. The results highlight the need for a well-planned approach, continuous workforce training, and collaboration across different sectors to fully harness digital technologies for promoting sustainable construction. This summary serves as a basis for future studies and the development of practical models aimed at combining innovation and sustainability within the construction industry. Keywords: digital innovation, sustainability, construction industry, BIM, IoT, artificial intelligence, digital twins, 3D printing, robotics, blockchain, energy efficiency

Building information modelling (BIM) has over a decade of development history in Hong Kong’s architect, engineering and construction industry. Its benefits have been well proven and widely recognised in a lot of previous studies. This paper looks into the amount of BIM value realisation and level of BIM participation by project members from the angle of implementation approach and procurement strategy. The past experience from different pioneers is collected and reviewed through in-depth interviews and open literature. It is found that most projects in the local market are at level 1 BIM maturity using a ‘one-sided management process’. Although some sort of project collaboration can be realised, it is still far from the full potential that BIM could offer. It is suggested that more consideration should be put on resource utilisation during the planning of BIM execution to enable better productivity through the use of technology.

The construction industry has often been described as stagnant and out-of-date due to the lack of innovation and innovative work methods to improve the industry (WEF, 2016; Ostravik, 2015). The adoption of Building Information Modelling (BIM) within the construction industry has been relatively slow (Cao et al., 2017), particularly in the South African Construction and Built Environment (CBE) (Allen, Smallwood & Emuze, 2012). The purpose of this study was to determine the critical factors influencing the adoption of BIM in the South African CBE, specifically from a quantity surveyor’s perspective, including the practical implications. The study used a qualitative research approach grounded in a theoretical framework. A survey questionnaire was applied to correlate the interpretation of the theory with the data collected (Naoum, 2007). The study was limited to professionals within the South African CBE. The study highlighted that the slow adoption of BIM within the South African CBE was mainly due to a lack of incentives and subsequent lack of investment towards the BIM adoption. The study concluded that the South African CBE operated mainly in silos without centralised coordination. The BIM adoption was only organic. Project teams were mostly project orientated, seeking immediate solutions, and adopted the most appropriate technologies for the team’s composition. The study implies that the South African CBE, particularly the Quantity Surveying profession, still depends heavily on other role-players in producing information-rich 3D models. Without a centralised effort, the South African Quantity Surveying professionals will continue to adopt BIM technology linearly to the demand-risk ratio as BIM maturity is realised in the South African CBE.

Building Information Modeling (BIM), Integrated Project Delivery (IPD), and Lean Construction (LC) are individually gaining increasing penetration in the Architecture, Engineering, and Construction (AEC) industry. Existing maturity models for each of these areas allow organisations to assess their current capability and guide their future pathways to increasing competence. There are significant mutual dependencies among these approaches; hence it would be useful for organisations to understand how to apply them to maximise the benefits across all three initiatives. An integrated BIM-IPD-LC (BIL) maturity model (MM) would break the silos among the initiatives by supporting this synergy. However, there is no comprehensive study on integrated organisational BIL maturity model design and development. This article presents the analysis of BIM maturity models as the starting point of research toward BIL MM development. BIM MMs are more widely cited and used within the construction industry compared to MMs for LC and IPD. This study uses the compatibility of BIM with IPD and LC in the context of MMs to identify how these three concepts can be synchronised. Comparative analysis is conducted using ten accessible, free, research-based, and frequently cited BIM MMs.They were then compared with a number of existing LC and IPD MMs. The results show that VDC Scorecard and BIM2FR are the most compatible BIM MMs with LC, and both the BIM Maturity Matrix and the VDC Scorecard closely correlate with the IPD characteristics compared with other BIM MMs. The findings of this study can be used as a basis for establishing the structure of a future integrated BIL maturity model.

Building information modelling (BIM) has considerable potential for addressing sustainability issues in construction, but its benefits can be constrained by the failure to adopt BIM across the full project life cycle. Systematic whole-of-life BIM adoption can be supported by maturity models, but most models are limited by a lack of theoretical grounding, socio-technical dichotomies and the failure to adequately consider the full asset life cycle, often by overlooking the operations phase. This study aims to (1) develop a BIM maturity model that addresses these limitations by (2) using an in-depth analysis of an early adopter case study, thus addressing the lack of empirical research in BIM adoption experiences. A single interpretive research study was conducted to qualitatively analyse a US-based university. The data were gathered through interviews, field visits and document analysis. Actor–network theory (ANT) concepts scaffolded the analytical approach. The findings show that a complex BIM socio-technical network emerged, developed and converged during the project management stage but struggled to achieve durability as an ongoing solution to facilities management. By analysing the elements of success and failure across each stage, the researchers distilled five key lessons to achieve whole-of-life BIM maturity and proposed a life cycle BIM maturity model (LCBMM) supported by a practice guide.