BIM Implementation: A Scientometric Analysis of Global Research Trends and Progress of Two Decades

Abstract

Over the past decade, Building Information Modelling (BIM) has become increasingly adopted across the Architecture, Engineering, Construction, and Operation (AECO) industry. As its use in practice has expanded, BIM has also received growing scholarly attention. Existing research has largely concentrated on specific applications of BIM, such as construction management, sustainable building design, infrastructure development, and facility management. However, comparatively limited attention has been given to examining BIM implementation from a global perspective. This study addresses this gap by applying a scientometric approach to analyse global BIM implementation research published between 2004 and 2023. The analysis is conducted using co-authorship, co-word, and co-citation analysis to map the structure and development of the research field. A total of 1349 published articles were obtained from the Scopus database for the analysis. The study identifies the most productive and influential contributors to BIM implementation research, including leading researchers, research institutions, countries, subject areas, and academic journals. In addition, the analysis highlights several key thematic domains within global BIM research. These include topics related to Industry Foundation Classes (IFC), Internet of Things (IoT), Geographic Information Systems (GIS), Historic Building Information Modelling (HBIM), and Digital Twin technologies, which appear as prominent keywords within the BIM implementation literature. Beyond mapping these trends, this paper integrates dispersed scientometric evidence into a coherent global perspective, revealing how BIM implementation research has evolved, matured, and diversified across regions and disciplines. It also establishes a structured knowledge base that can serve as a benchmark for future comparative studies, performance assessments, and policy development initiatives in the digital construction domain. These findings provide valuable insights for researchers, practitioners, and policymakers by illustrating landscape of BIM-related research and highlighting potential directions for future investigation.

1. Introduction

Building Information Modelling, which represents a digital representation and integrated process for managing the physical and functional characteristics of built assets, has played a significant role in advancing digital transformation across the AEC industry [1]. Rather than functioning solely as a digital modelling tool, BIM operates as a collaborative information management framework that supports the development and use of data-rich models to assist decision-making across the entire project lifecycle. The geometric and semantic information embedded within these models facilitates key processes such as design coordination, procurement, manufacturing, and construction. Initially, BIM was primarily applied during the pre-planning, design, and construction phases of buildings, infrastructure, and integrated projects. However, contemporary research and practice have expanded its scope to encompass maintenance, refurbishment, reconstruction, and decommissioning processes [2].

Over the past decade, as BIM has rapidly advanced, numerous new research directions have emerged. The fusion of BIM with various other cutting-edge technologies has become increasingly prevalent. Javier Irizarry proposed an integrated system that combines BIM with GIS to visually represent the current status of materials throughout the supply network [3]. Another Study developed a conceptual framework for managing building defects by combining ontology and augmented reality (AR) with BIM to strengthen on-site defect management processes [4]. In the backdrop of worsening global environmental conditions, greater emphasis has been placed on the conservation of natural resources. The construction industry has increasingly reached a broad consensus on the importance of sustainable development within this context. Yujie Lu introduced a taxonomy known as the “green BIM triangle,” which conceptualises the interplay between BIM and green buildings [5]. This taxonomy offers valuable insights into the advantages and challenges associated with the implementation of BIM. A framework was proposed that integrates BIM with Genetic Algorithm optimisation and Monte Carlo simulation. This integrated approach provides a decision-support tool for the construction industry, assisting stakeholders in selecting suitable building materials while enhancing the environmental and economic sustainability of buildings [6].

In parallel with these technological advancements, the AEC sector has been undergoing a broader process of digital transformation, within which BIM has emerged as a central enabling platform for integrating digital information, processes, and stakeholders across the project lifecycle. Recent research highlights that BIM plays a key role in supporting digital transformation initiatives within the built environment by improving information flow, enabling collaborative data environments, and facilitating data-driven decision-making across construction projects [7,8,9].

Furthermore, the increasing adoption of BIM and other digital technologies has led to growing interest in evaluating the digital maturity of organisations within the construction sector. Digital maturity assessment frameworks have been developed to measure the capability of organisations to implement and manage digital technologies effectively, including BIM-enabled processes and information management systems. Such frameworks help identify organisational gaps in skills, processes, and technological infrastructure, thereby supporting strategic planning for advancing digital transformation within the construction industry [10,11].

Positioning Within Existing Scientometric Reviews

As shown in

Table 1. Summary of prior review and scientometric studies.

Study	Period Covered	Database(s)	Method	Sample Size	Main Focus	Limitation
Zhao (2017), A scientometric review of global BIM research: Analysis and visualization, [12]	2005–2016	Web of Science	Co-author, co-word, co-citation analysis	614	Global BIM research status, hot topics, trend visualisation	Broad BIM mapping; not implementation-specific and limited to the 2005–2016 window.
He et al. (2017), Mapping the managerial areas of Building Information Modeling (BIM) using scientometric analysis, [13]	2007–2015	Scopus + Web of Science	Scientometric analysis; knowledge mapping	126	Managerial/non-technical areas of BIM	Narrowly focused on managerial BIM rather than the wider implementation literature.
Santos et al. (2017), Bibliometric analysis and review of Building Information Modelling literature published between 2005 and 2015, [14]	2006–2015	Web of Science	Bibliometric review + content categorisation	381	Research categories, most cited works, emerging BIM fields	Broad BIM categorisation; not implementation-specific limited to the 2006–2015 window.
Olawumi et al. (2017), Evolution in the intellectual structure of BIM research: A bibliometric analysis, [15]	2006–2016	Web of Science	Bibliometric analysis + research category analysis	445	Intellectual structure, categories, funding structure, project sectors	Broad BIM intellectual structure and formation, limited to 2006–2016
Li et al. (2017), Mapping the knowledge domains of Building Information Modeling (BIM): A bibliometric approach, [16]	2004–2015	Web of Science	Bibliometric approach; core and expanded datasets	1874	BIM knowledge domains and knowledge base	Very broad knowledge-domain mapping limited to 2004–2015
Saka and Chan (2019), A global taxonomic review and analysis of the development of BIM research between 2006 and 2017, [17]	2006–2017	Web of Science	Comparative taxonomic review + scientometric analysis	914	Continental comparison of BIM development, themes, and trends	Strong geographic comparison, but still a broad BIM-development study rather than an implementation-focused one.
Liu et al. (2019), A Review and Scientometric Analysis of Global Building Information Modeling (BIM) Research in the AEC Industry, [18]	2004–2019	Web of Science	Scientometric review	1455	Global BIM research in AEC, major clusters and trends	Broad BIM/AEC scope with no BIM Implementation focus.
Wen et al. (2021), The progress and trend of BIM research: A bibliometrics-based visualization analysis, [19]	2010–2019	Web of Science	Bibliometrics-based visualisation analysis	1369	BIM research progress and development trends	Broad BIM trend study, not centred specifically on implementation and adoption research.

, several bibliometric and scientometric studies have previously examined the broader knowledge structure of BIM. Earlier work examined global BIM research, managerial BIM themes, knowledge domains, intellectual structure, and regional development patterns using bibliometric or scientometric techniques. For example, Zhao (2017) analysed 614 Web of Science records from 2005 to 2016 using co-author, co-word, and co-citation analysis [12]; He et al. (2017) reviewed 126 papers on managerial areas of BIM using Scopus and Web of Science [13]; Santos et al. (2017) reviewed 381 BIM papers published between 2006 and 2015 [14]; Olawumi et al. (2017) analysed 445 Web of Science articles to identify research categories and funding structures [15]; Li et al. (2017) mapped BIM knowledge domains using 1874 Web of Science records [16]; Saka and Chan (2019) examined 914 Web of Science journal articles across six continents [17]; Liu et al. (2019) reviewed 1455 Web of Science records covering global BIM research from 2004 to 2019 [18]; and Wen et al. (2021) analysed 1369 Web of Science publications from 2010 to 2019 using bibliometric visualisation methods [19].

However, most of these studies focused on BIM research broadly defined on specific subdomains such as managerial BIM, or on regional and thematic segmentation rather than on BIM implementation as a distinct knowledge stream. Even where implementation-related themes were discussed, they were typically embedded within wider BIM literature, making it difficult to isolate how implementation research itself has evolved, what its dominant clusters are, and which implementation-oriented papers and themes have shaped the field. Accordingly, the present study can be positioned more precisely as a global scientometric analysis centred specifically on BIM implementation research.

Taken together, these studies demonstrate that BIM research has been examined from several perspectives, including global publication trends, intellectual structures, thematic domains, and regional patterns of development. Nevertheless, most prior scientometric investigations have treated BIM as a broad research field rather than isolating BIM implementation as a distinct analytical focus. As a result, the specific evolution, structure, and thematic development of BIM implementation research remain comparatively underexplored. The present study therefore focuses specifically on BIM implementation literature, enabling a clearer understanding of how BIM implementation-related research has developed over time, which thematic clusters dominate the field, and which influential publications and research communities have shaped this area of study.

To address this gap, the present study applies a scientometric approach to analyse global BIM implementation research published between 2004 and 2023. Using bibliometric visualisation techniques, including co-authorship, co-citation, and keyword co-occurrence analyses, the study maps the intellectual structure, collaboration patterns, and thematic evolution of BIM implementation literature. This approach enables the identification of major research clusters, influential publications, and emerging research directions within the field.

2. Materials and Methods

Scientometrics, a subfield of information science, focuses on the quantitative analysis of patterns within scientific literature. Its primary aim is to provide a comprehensive understanding of emerging trends and the intellectual structure of research domains. In recent years, scientometric analysis has become one of the most widely adopted approaches for evaluating research performance. This method is applied not only to assess the contributions of individual researchers but also to evaluate the performance of departments, faculties, universities, countries, and academic journals [20].

Co-citation analysis is a method used to examine the relationships between scientific publications. It identifies influential or core works within a research field by analysing how frequently two or more publications are cited together in subsequent literature. These citation relationships illustrate that scientific knowledge develops through interconnected and systematic linkages rather than through isolated contributions. Co-citation patterns therefore reflect the objective evolution of scientific research, demonstrating the cumulative, continuous, and inheritable nature of scholarly knowledge, as well as its interdisciplinary connections. Citation networks further enable researchers to trace the intellectual origins of ideas and follow their subsequent development across time. Importantly, citations in scientific literature are not evenly distributed; instead, they exhibit patterns of concentration and dispersion, reflecting the varying levels of influence and attention that different publications receive within the academic community.

Co-word analysis is a bibliometric technique first introduced by Callon [11]. It is based on the statistical examination of words that co-occur within the same body of literature. By analysing the frequency with which terms appear together, the method evaluates the strength of relationships between concepts and identifies patterns of association or divergence. As a form of content analysis, co-word analysis enables the mapping of relationships among informational elements within textual data. It focuses particularly on keywords shared across publications and organises related literature according to the interactions among these keywords. Consequently, the keywords used to summarise the content of publications act as fundamental elements in shaping the conceptual structure of research fields [21]. This approach offers insights into the thematic connections and relationships within a body of literature. For example, frequent co-occurrence of terms such as “BIM implementation,” “interoperability,” and “IFC” may indicate a thematic cluster focused on data exchange standards, whereas links between “Digital Twin,” “IoT,” and “facility management” reflect emerging directions in integrating BIM with smart asset management technologies.

To ensure comprehensive and reliable research data, Scopus was selected as the primary data source for this study. As summarised in Table 1, most previous scientometric analyses of BIM research have relied predominantly on the Web of Science database. Therefore, this study deliberately utilised Scopus to provide a complementary perspective and broaden the coverage of BIM implementation research. Scopus is widely recognised for its extensive journal coverage in engineering, construction management, and built environment disciplines, and it indexes a large number of peer-reviewed publications relevant to BIM research. Comparative studies have also shown that Scopus offers broader journal coverage than Web of Science, particularly in engineering and applied sciences, while providing comprehensive citation and metadata export capabilities suitable for bibliometric analysis [22,23].

Journal articles published over the last two decades (2004–2023) were retrieved using BIM implementation main keywords, resulting in a data set of 1378 literature entries. However, the number of entries that shared a similar acronym but had irrelevant implications, such as “Budget Impact Model (BIM),” among others were manually eliminated, resulting in a refined dataset of 1349 literature entries. Conference papers were subsequently excluded from the dataset, and only journal articles were retained for detailed analysis. The overall methodology adopted in this study is shown in Figure 1. A PRISMA-inspired screening workflow was adopted to improve the transparency and replicability of the dataset construction process. The literature identification process began with a Scopus search using the predefined Boolean search string applied to the title, abstract, and keyword fields. The initial search returned 1378 records. These records were then screened to remove publications that were not relevant to the intended meaning of BIM within the architecture, engineering, and construction context, including records in which the acronym “BIM” referred to unrelated terms. After this screening step, 1349 journal articles remained and were retained as the final dataset for the scientometric analysis.

The inclusion criteria comprised: (i) journal articles indexed in Scopus; (ii) publications written in English; (iii) studies published between 2004 and 2023; and (iv) publications relevant to BIM implementation or adoption within the built environment domain. The exclusion criteria comprised: (i) conference papers and other non-journal document types; (ii) non-English publications; and (iii) records unrelated to Building Information Modelling in the construction context. In addition to the full scientometric dataset, a refined subset of 364 articles explicitly addressing BIM implementation or BIM adoption in their titles was identified for the focused analysis presented in Section 3.6.

To identify relevant publications, a structured search strategy was developed using the Scopus database. The search query was designed to capture studies related to BIM implementation and adoption within the construction domain. The following Boolean search expression was used: TITLE-ABS-KEY (“BIM”) AND TITLE-ABS-KEY (implementation OR adoption). Searching within the title, abstract, and keyword fields ensures that the retrieved publications are strongly related to the research topic while maintaining adequate coverage of relevant studies.

The search strategy was deliberately structured around the core terms “BIM” and “implementation/adoption”, as the objective of this study is to examine BIM implementation research as a distinct knowledge domain. In bibliometric research, search design requires a balance between comprehensiveness and conceptual specificity, as overly broad search strings may introduce adjacent but analytically different studies and thereby reduce the coherence of science-mapping results. The selected terms represent the most widely established and consistently used descriptors of BIM implementation in the AEC literature. While related expressions such as “integration”, “diffusion”, “BIM strategy”, and “digital construction adoption” are present in the wider literature, these terms are often used in broader or context-dependent ways and may extend beyond the specific scope of BIM implementation research. Accordingly, the final search query was defined to maintain a clear conceptual boundary and ensure the relevance and internal consistency of the dataset. This focused keyword strategy is consistent with previous scientometric studies on BIM research [12], where a limited set of core keywords is commonly used to retrieve literature directly relevant to the investigated topic while avoiding the inclusion of unrelated records.

To conduct the scientometric analysis, VOSviewer version 1.6.20 was employed as the primary analytical tool in this study. VOSviewer is widely recognised as a specialised software for constructing and visualising bibliometric networks and has been extensively applied in scientometric studies across engineering and construction management research. The software enables the analysis of relationships among various research entities, including publications, journals, authors, research institutions, countries, and keywords. These relationships can be examined through several bibliometric techniques, such as co-authorship analysis, keyword co-occurrence, citation analysis, bibliographic coupling, and co-citation analysis [24]. One of the key advantages of VOSviewer is its ability to efficiently process large bibliographic datasets and generate clear network visualisations that reveal the structure and thematic clusters of a research field. In addition, the software is highly compatible with bibliographic data exported from the Scopus database, which facilitates reliable data processing and network mapping. VOSviewer also quantifies both the number of connections and the strength of relationships between nodes, enabling the generation of graphical network maps that support the interpretation of bibliometric structures and research trends [25].

3. Results and Discussion

This section presents and discusses the results of the scientometric analyses conducted on the selected literature related to BIM implementation in the AEC industry.

3.1. Geographical and Temporal Distribution of BIM Implementation Research (2004–2023)

In the typical progression of technological development within any research field, there is a general similarity. The process typically initiates with an initial conception phase. Subsequently, as research tools become more widely available, the capacity and scope of the research expand, marking the onset of the proliferation phase. During this stage, researchers often apply the developed research methods to other fields. Ultimately, the field enters a declining phase as the technology becomes less prominent or is surpassed by newer developments [26].

In this study, an analysis was conducted on the number of papers published in the field of BIM Implementation over the past two decades (2004–2023), along with an examination of the countries or regions where these papers originated. Figure 2 presents the yearly distribution of BIM-related publications retrieved from the Scopus database between 2004 and 2023. The results indicate a steady and sustained growth in BIM implementation research over the last twenty years. During (2004–2013), the number of publications remained relatively low, reflecting the emerging stage of BIM research within the AEC industry. From approximately 2014 onwards, publication output increased consistently, with particularly strong growth observed after 2017. The publication trajectory shows a gradual expansion of scholarly attention to BIM implementation as the technology became more widely adopted in practice and academia. Several policy and standardisation developments occurred during this period, including the UK Government BIM Level 2 mandate in 2016 and the publication of the ISO 19650 series beginning in 2018 [27]. While these initiatives are widely recognised as important milestones in the global diffusion of BIM, the publication data suggest that research activity expanded progressively associated with specific policy events.

These milestones encouraged both academia and industry to explore BIM implementation strategies, maturity assessment, and integration with emerging technologies such as IoT, cloud computing, and Digital Twins, leading to a surge in related publications. Between 2004 and 2013, publication output in the BIM field displayed fluctuations, with fewer than 100 papers published. This limited output reflects the exploratory phase of BIM research, when conceptual discussions and pilot projects were still emerging, software interoperability was under development, and global awareness of BIM’s potential benefits remained relatively low. This suggests that BIM research was in its early conception stage during this period. However, from 2013 onwards, as BIM technology gained wider adoption in engineering practice and various software tools were actively promoted, the number of BIM-related publications experienced a marked increase between 2014 and 2023. By 2017, the total number of publications had exceeded 300, indicating that BIM research had entered a phase of rapid expansion.

From 2020 to 2023, over 150 journal articles were published annually, with the total number exceeding 1000 in 2020. The trajectory of BIM publications demonstrates and accelerating rise, indicating its entry into a stage of rapid growth. Notably, over five years (2018–2023), 75% of the total papers related to BIM Implementation were published.

The geographical spread of publications was determined using author affiliation data extracted from the bibliographic records and analysed using VOSviewer. Countries were attributed based on the institutional affiliations of all authors associated with each publication. Using the full counting method implemented in VOSviewer, each country represented in the author affiliations of a publication was assigned one publication count. Consequently, publications involving international co-authorship contribute to the counts of multiple countries, and the total across countries may exceed the total number of publications.

The geographical distribution of BIM research was also examined by identifying the top 20 countries or regions that have contributed most actively to BIM-related studies during the last two decades, as presented in

Table 2. Top 20 contributing countries.

Ranking Based on Articles			Ranking Based on Citations		Ranking Based on Citation Index
Rank	Country	Articles	Country	Citations	Country	Citation Index
1	UK	216	UK	8624	Israel	77
2	China	180	USA	6787	Belgium	66
3	USA	168	Australia	4945	Slovenia	63
4	Malaysia	123	China	3881	Finland	61
5	Australia	101	Hong Kong	2675	Australia	49
6	Hong Kong	68	South Korea	1965	South Korea	47
7	Italy	66	Canada	1435	Netherlands	45
8	Spain	58	Germany	1396	USA	40
9	Germany	52	Malaysia	1366	UK	40
10	Canada	51	Netherlands	1348	Hong Kong	39
11	South Korea	42	Italy	1176	Singapore	37
12	Portugal	35	Singapore	992	Sweden	36
13	Iran	33	Israel	918	Taiwan	35
14	Saudi Arabia	32	Finland	853	Canada	28
15	Turkey	32	Taiwan	846	Germany	27
16	New Zealand	31	Sweden	787	Ghana	27
17	Egypt	30	Spain	727	Norway	27
18	India	30	Nigeria	719	Pakistan	26
19	Netherlands	30	New Zealand	704	Nigeria	25
20	Nigeria	29	Portugal	557	UAE	24

. Among them, the United Kingdom ranks first in terms of publication output, with 216 publications, representing approximately 16% of the total. This dominance can be attributed to the UK Government’s early and strategic commitment to BIM adoption, particularly following the 2011 Government Construction Strategy and the implementation of the Level 2 BIM mandate in 2016, which positioned the UK as a global leader in BIM policy, standardisation and practice. The UK’s strong network of research-intensive universities, such as the University of Cambridge and University College London, further accelerated scholarly contributions through collaborative industry-academic research on BIM frameworks, maturity models, and digital transformation in construction. China follows closely with 180 publications, representing 13.3%. The United States, Malaysia, Australia, among others, follow in the subsequent positions. In addition to total publication output and citation counts, a citation index was calculated to provide a normalised indicator of research influence by country. The citation index represents the average number of citations per publication, calculated by dividing the total citation count by the number of articles attributed to each country.

The citation index highlights countries that produce comparatively fewer publications but achieve high scholarly impact. For example, Israel and Belgium appear among the highest-ranked countries in the citation index despite not being among the top producers of BIM-related publications. This suggests that although their publication volume is relatively limited, their contributions have achieved a strong academic influence within the BIM research community.

The international collaboration network generated using VOSviewer is presented in Figure 3. The network is based on co-authorship relationships between countries, derived from the institutional affiliations of authors in the analysed publications. Each node represents a country, while links indicate collaborative relationships formed through co-authored articles. The size of each node reflects the number of publications attributed to that country, and the thickness of the links represents the strength of collaboration between countries. The colour gradient represents betweenness centrality, a network metric indicating the extent to which a country acts as an intermediary connecting different parts of the collaboration network. Countries such as the United States, Germany, United Kingdom, Italy, Spain, Canada, Poland, and the Netherlands exhibit relatively high centrality, suggesting their important role in linking international research communities within BIM implementation studies.

3.2. Analysis of Journal Co-Citations

A journal co-citation analysis was conducted using VOSviewer. Journal co-citation occurs when two documents published in different journals are cited together by another document in a separate journal [28,29]. Figure 4 illustrates the co-citation network of journals related to BIM implementation. In this visualisation, each node represents a journal, and the size of the node indicates the number of citations received within the co-citation network, reflecting the journal’s relative influence in the BIM research domain. The links between nodes represent co-citation relationships, while the number and thickness of these links indicate the strength of the connections between journals.

As illustrated in Figure 4, journals are grouped into several clusters, representing sets of journals that are frequently cited together within the BIM literature. These clusters reflect related research areas within the broader BIM knowledge structure. “Automation in Construction” occupies a central position with a dense network of connections, indicating its strong influence within BIM-related research.

Table 3. Top 10 most influential journals.

No	Source	Host Country	Count	Citations
1	Automation in Construction	Netherlands	97	10,193
2	Journal of Construction Engineering and Management	USA	40	2080
3	Engineering, Construction and Architectural Management	UK	67	1831
4	Journal of Management in Engineering	USA	26	1169
5	Architectural Engineering and Design Management	UK	24	943
6	Advanced Engineering Informatics	UK	21	898
7	Sustainability (Switzerland)	Switzerland	69	863
8	Journal of Cleaner Production	USA	10	853
9	Buildings	Switzerland	88	801
10	Journal of Building Engineering	Netherlands	22	753

presents the ten most highly co-cited journals. Automation in Construction is the most influential journal in terms of total citation frequency, with a significantly higher number of citations compared to other journals. This suggests that Automation in Construction holds a robust authority in the field of BIM. Following closely are influential journals such as Journal of Construction Engineering and Management, Engineering, Construction and Architectural Management, Journal of Management in Engineering, Architectural Engineering and Design Management, and Advanced Engineering Informatics. In addition to citation counts, the table also reports the host country of each journal publisher in order to illustrate the geographical distribution of major publication outlets. Notably, all the highest cited journals originate from Europe and USA, underscoring that the primary research hubs for BIM are still concentrated in these regions.

The relationship with the data presented in Table 3 is also evident in Figure 4, where Automation in Construction appears at the centre of the network, highlighting its strong influence and contribution to BIM research. The similar colour-coding in Figure 4 indicates the close association among these journals, while the spatial proximity between nodes reflects the strength of their co-citation relationships.

3.3. Analysis of Author Co-Citation

Author co-citation analysis serves to unveil relationships among authors whose works are cited in the same articles, enabling the analysis of the evolution of research communities. Figure 5 illustrates the author co-citation network, where node size corresponds to the number of articles authored by each individual. The links between authors signify indirect cooperative relationships established through co-citation frequency. Consequently,

Table 4. Top 10 contributing authors.

No	Author	Articles	Citations	Affiliations
1	Chan, Daniel W.M.	13	691	Hong Kong Polytechnic University
2	Olawumi, Timothy O.	12	733	Edinburgh Napier University
3	Kassem, Mohamad	11	1041	Newcastle University
4	Othman, Idris	11	268	Universiti Teknologi PETRONAS
5	Chong, Heap-Yih	10	174	Curtin University
6	Rahman, Rahimi A.	10	123	Universiti Malaysia Pahang
7	Dawood, Nashwan	9	539	Teesside University
8	Li, Heng	9	316	Hong Kong Polytechnic University
9	Wang, Guangbin	9	376	Tongji University
10	Cao, Dongping	8	264	Tongji University

showcases the most contributing authors identified through this analysis.

The geographical diversity observed in the locations of these highly cited authors highlights the global reach of BIM research, indicating that significant contributions have been made from various parts of the world.

3.4. Analysis of Articles Co-Citation

Articles co-citation analysis serves to understand the underlying intellectual structures within a knowledge domain and illustrate both the quantity and authority of references cited by publications. Through this analytical process, co-citation clusters were identified. The summarised list of the top 20 cited articles can be found in

Table 5. The top 20 BIM cited articles.

No	Article	Citations	No	Article	Citations
1	Succar (2009) [30]	975	11	Cerovsek (2011) [38]	259
2	Becerik-Gerber (2012) [31]	631	12	Liu (2017c) [39]	257
3	Eadie (2013) [32]	482	13	Chen (2014) [40]	242
4	Azhar (2012) [33]	467	14	Khajavi (2019) [41]	236
5	Singh (2011) [34]	457	15	Sacks (2010) [42]	234
6	Arayici (2011b) [35]	374	16	Succar (2015) [43]	221
7	Porwal (2013) [36]	325	17	Tan (2019) [44]	211
8	Miettinen (2014) [37]	315	18	Zou (2017) [45]	207
9	Li (2019b) [46]	309	19	Sebastian (2011) [47]	201
10	Jung (2011) [48]	279	20	Pauwels (2011) [49]	201

. According to the Scopus citation metric, Succar 2009 [30], Becerik-Gerber (2012) [31] and Eadie (2013) [32] received 975, 631 and 482 citations, respectively, and occupied the top three positions, followed by Azhar et al. (2012) [33] (frequency = 467), Singh Vishal (2011) [34] (frequency = 457) Arayici Y (2011) [35] (frequency = 374), Porwal Atul (2013) [36] (frequency = 325), and Miettinen, Reijo (2014) [37] (frequency = 315). Succar [30] formulated a BIM framework with well-defined knowledge components, laying the groundwork for both research and practical implementation within the industry for various stakeholders.

Among the analysed publications, the article by Succar (2009) [30] is identified as the most highly cited paper within the dataset. This work has played a significant role in shaping BIM research by proposing a structured framework for understanding BIM maturity and capability levels. Its high citation count reflects the substantial influence of this conceptual framework on subsequent studies investigating BIM implementation, adoption, and maturity assessment within the construction industry.

Figure 6 illustrates a network of document co-citations and co-citation clusters. Each node within the network represents a document and is labelled with the first author’s name and the publication year. The links between nodes signify the co-citation relationship between the respective documents. Additionally, the size of each node reflects the co-citation frequency of the associated article.

3.5. Analysis of Co-Occurring Keywords

Keywords play a crucial role in representing the core content of articles and demonstrating the evolution of research topics over time. In the VOSviewer software, two types of keywords are identified: (i) “author keywords,” supplied by the authors, and (ii) “Index keywords,” recognised by the VOSviewer software. In this study, author keywords extracted from the 1349 bibliographic records were used to construct the keyword co-occurrence network, as they more accurately reflect the thematic focus defined by the authors of each publication.

Keyword co-occurrence analysis was conducted using VOSviewer to identify the most frequently occurring research themes and the relationships between them within the BIM implementation literature. Prior to conducting the co-occurrence analysis, a thesaurus file was used in VOSviewer to standardise the keyword dataset by merging synonymous and conceptually overlapping terms. This step ensures that each node represents a unique concept, thereby improving the reliability of co-occurrence relationships and the clarity of the resulting clusters. In the generated network (Figure 7), each node represents a keyword, while links between nodes indicate the frequency with which two keywords appear together in the same publication. The size of each node reflects the occurrence frequency of the keyword, and the thickness of the connecting links indicates the strength of co-occurrence between keyword pairs. Clusters represent groups of keywords that frequently appear together and therefore reflect related thematic areas within the BIM research landscape.

As illustrated in Figure 7, highly frequent keywords are “BIM”, “Implementation”, “construction industry”, “information management”, “construction management”, “barriers”, and “benefits”. The prominence of these keywords indicates that a substantial portion of the BIM literature focuses on organisational adoption, implementation challenges, and the management of digital information within construction projects.

These dominant keywords reflect the foundational stage of BIM implementation research, where the primary emphasis has been on understanding adoption drivers, organisational readiness, and the challenges associated with integrating BIM into existing construction practices. This suggests that early research efforts were largely oriented towards identifying barriers and demonstrating the benefits of BIM as a means of encouraging wider industry uptake.

Additional keywords appearing within the network include “interoperability”, “IFC”, “GIS”, “virtual reality”, “augmented reality”, and “education”. Their presence within the co-occurrence network indicates that these topics are frequently discussed alongside BIM implementation in the analysed literature. For example, interoperability and the IFC data schema are often discussed in relation to information exchange between software platforms and stakeholders involved in BIM-enabled projects [50].

The emergence of these keywords indicates a shift in the research focus from basic adoption concerns towards more advanced implementation challenges, particularly those related to information exchange, system integration, and the extension of BIM into wider digital ecosystems. This reflects the increasing maturity of BIM implementation research, where attention is moving beyond whether BIM should be adopted to how it can be effectively integrated with other technologies and workflows.

The keyword clusters identified in Figure 7 therefore reflect several major thematic areas within the BIM implementation literature, including BIM adoption and implementation practices, digital construction technologies, information interoperability, and applications supporting project management and decision-making.

From an analytical perspective, these clusters collectively illustrate the evolution of BIM implementation research from an initial focus on adoption and barriers towards a more structured and multi-dimensional discourse encompassing process integration, interoperability, and digital innovation. This progression highlights a transition from exploratory research aimed at validating BIM benefits to more mature studies concerned with optimisation, standardisation, and integration within the broader digital construction landscape. Keywords related to virtual reality and augmented reality appearing in the co-occurrence network suggest growing interest in the use of immersive technologies to support BIM-based visualisation, design review, and construction planning processes [51]. This indicates that recent research is increasingly positioning BIM as a central platform within a wider ecosystem of emerging digital technologies, rather than as a standalone tool.

Education also appears as a recurring theme within the keyword network. The presence of keywords related to BIM education indicates the importance of integrating BIM knowledge and digital construction skills into civil engineering and construction management curricula. Incorporating BIM into construction education aims to equip students with the competencies required for digital project delivery and collaborative information management within the construction industry [52]. The prominence of education-related keywords further suggests a growing recognition that successful BIM implementation is not solely a technological challenge but also a skills and capability issue, requiring long-term investment in workforce development and knowledge transfer.

3.6. BIM Implementation Articles Analysis

The analysis involved a meticulous review of 1349 articles, with a focus on those explicitly addressing either BIM implementation or BIM adoption in their titles. A refined selection process yielded a total of 364 articles, organised based on their impact in BIM implementation research, measured by the citation count of each article. The resulting

Table 6. Top 25 BIM implementation articles with the highest citation.

No	Autor	Title	Year	Citations	Source Title
1	Eadie [32]	“BIM implementation throughout the UK construction project lifecycle: An analysis”	2013	482	Automation in Construction
2	Arayici [35]	“Technology adoption in the BIM implementation for lean architectural practice”	2011	374	Automation in Construction
3	Miettinen [37]	“Beyond the BIM utopia: Approaches to the development and implementation of building information modeling”	2014	314	Automation in Construction
4	Jung [48]	“Building information modelling (BIM) framework for practical implementation”	2011	279	Automation in Construction
5	Succar [43]	“Macro-BIM adoption: Conceptual structures”	2015	221	Automation in Construction
6	Tan [44]	“Barriers to Building Information Modeling (BIM) implementation in China’s prefabricated construction: An interpretive structural modeling (ISM) approach”	2019	211	Journal of Cleaner Production
7	Eastman [53]	“Exchange model and exchange object concepts for implementation of national BIM standards”	2010	190	Journal of Computing in Civil Engineering
8	Chen [54]	“Perceived benefits of and barriers to Building Information Modelling (BIM) implementation in construction: The case of Hong Kong”	2019	187	Journal of Building Engineering
9	Arayici [55]	“BIM adoption and implementation for architectural practices”	2011	186	Structural Survey
10	Son [56]	“What drives the adoption of building information modeling in design organizations? An empirical investigation of the antecedents affecting architects’ behavioral intentions”	2015	162	Automation in Construction
11	Elmualim [57]	“BIM: Innovation in design management, influence and challenges of implementation”	2014	154	Architectural Engineering and Design Management
12	Al-Ashmori [58]	“BIM benefits and its influence on the BIM implementation in Malaysia”	2020	142	Ain Shams Engineering Journal
13	Ding [59]	“Key factors for the BIM adoption by architects: A China study”	2015	135	Engineering, Construction and Architectural Management
14	Cao [60]	“Identifying and contextualising the motivations for BIM implementation in construction projects: An empirical study in China”	2017	133	International Journal of Project Management
15	Linderoth [61]	“Understanding adoption and use of BIM as the creation of actor networks”	2010	131	Automation in Construction
16	Davies [62]	“Implementing ‘site BIM’: A case study of ICT innovation on a large hospital project”	2013	128	Automation in Construction
17	Shou [63]	“A Comparative Review of Building Information Modelling Implementation in Building and Infrastructure Industries”	2015	108	Archives of Computational Methods in Engineering
18	Biagini [64]	“Towards the BIM implementation for historical building restoration sites”	2016	105	Automation in Construction
19	Sackey [65]	“Sociotechnical systems approach to BIM implementation in a multidisciplinary construction context”	2014	101	Journal of Management in Engineering
20	Ciribini [66]	“Implementation of an interoperable process to optimise design and construction phases of a residential building: A BIM Pilot Project”	2016	97	Automation in Construction
21	Manning [67]	“Case studies in BIM implementation for programming of healthcare facilities”	2008	97	Electronic Journal of Information Technology in Construction
22	Ahn [68]	“Contractors’ Transformation Strategies for Adopting Building Information Modeling”	2016	94	Journal of Management in Engineering
23	Lu [69]	“Cost-benefit analysis of Building Information Modeling implementation in building projects through demystification of time-effort distribution curves”	2014	93	Building and Environment
24	Charef [70]	“Building Information Modelling adoption in the European Union: An overview”	2019	92	Journal of Building Engineering
25	Hong [71]	“BIM adoption model for small and medium construction organisations in Australia”	2019	90	Engineering, Construction and Architectural Management

showcases the top 25 BIM implementation articles with the highest citation counts. This table includes essential details such as author names, article titles, publication years, citation counts, and the respective journal names. Each article is also accompanied by a reference link, providing a valuable resource for researchers in the field of BIM implementation.

The top five most cited articles are affiliated with the Automation in Construction journal. Notably, Eadie’s work [32], “BIM implementation throughout the UK construction project lifecycle: An analysis,” holds the highest citations of 482, while Succar’s [43] contribution, “Macro-BIM adoption: Conceptual structures,” as the fifth highest citations of 221.

A noteworthy observation is the geographic distribution of highly cited articles, with a concentration in the UK, Europe, China, Hong Kong, Australia, and Malaysia. This trend underscores the heightened activity in BIM implementation research within developed countries.

4. Conclusions

In this study, scientometric analysis was conducted using bibliometric mapping techniques to review the literature on BIM implementation published between 2004 and 2023. A visual bibliometric analysis was performed on 1349 publications, incorporating co-author, co-word, and co-citation analyses The following conclusions are derived from these analyses.

(1)

The analysis indicates a steady increase in BIM implementation research output over the past two decades. The growth in publication volume reflects the expanding academic and industry interest in digital construction technologies and information management practices associated with BIM. Rather than identifying distinct developmental stages, the scientometric results highlight a continuous expansion of scholarly activity in this research domain.

(2)

The results of the journal co-citation analysis indicate that Automation in Construction is the most frequently cited and influential outlet within the bibliometric dataset analysed in this study. Its prominence can be attributed to the consistent publication of high-impact research on digital construction technologies, information modelling, and innovation management, which has positioned the journal at the core of the BIM research network. Following closely are influential journals such as the Journal of Construction Engineering and Management, Engineering Construction and Architectural Management, Journal of Management in Engineering, Architectural Engineering and Design Management, and Advanced Engineering Informatics.

(3)

The geographic distribution of publications shows that BIM implementation research is produced by authors affiliated with institutions across multiple regions, with strong contributions from countries such as the United Kingdom, China, and the United States. The collaboration network analysis further indicates that several countries play important intermediary roles in connecting international research communities through co-authored publications.

(4)

The keyword co-occurrence analysis highlights several frequently occurring themes within the BIM implementation literature, including BIM adoption and implementation practices, construction project management, information management, and interoperability-related topics. Additional keywords associated with technologies such as GIS, IoT, and digital construction tools appear within the network, indicating their connection to BIM research within the analysed dataset.

(5)

From the overall dataset, 364 publications explicitly addressing BIM implementation were identified. The increasing number of studies focusing on implementation-related topics reflects the growing research attention dedicated to understanding the practical application, adoption challenges, and organisational integration of BIM within the construction industry.

Overall, this study provides a scientometric overview of BIM implementation research by mapping publication patterns, collaboration networks, influential journals, and thematic structures derived from keyword co-occurrence analysis. While scientometric analysis relies primarily on bibliographic metadata rather than full-text content, the results offer a structured perspective on how BIM implementation research is organised within the academic literature. The findings provide a useful knowledge base for researchers and practitioners seeking to understand the structure of the field and identify areas for further investigation.

5. Implications and Future Research Directions

The findings of this scientometric analysis provide several implications for both research and practice in the field of BIM implementation. From a theoretical perspective, the mapping of publication patterns, collaboration networks, and keyword clusters helps clarify the intellectual structure of BIM implementation research and highlights the main thematic areas explored in the literature. The results indicate that research has concentrated primarily on BIM adoption, implementation barriers, information interoperability, and digital construction technologies.

From a practical perspective, the analysis highlights the increasing importance of integrating BIM with emerging digital technologies such as GIS, digital twins, and immersive visualisation tools. These developments suggest that future industry applications will increasingly rely on integrated digital platforms supporting collaborative project delivery and information management across the lifecycle of built assets.

Based on the thematic patterns identified through the keyword co-occurrence analysis, several potential directions for future research can be identified:

(1)

Developing standardised frameworks for evaluating BIM implementation maturity and organisational capability.

(2)

Exploring interoperability challenges and data exchange mechanisms between BIM and other digital platforms such as GIS and digital twin environments.

(3)

Investigating the integration of BIM with emerging technologies such as artificial intelligence, internet of things, and immersive virtual environments.

(4)

Examining organisational and managerial factors influencing BIM adoption in different regional and regulatory contexts.

These directions highlight opportunities for advancing both the theoretical understanding and practical implementation of BIM within the architecture, engineering, and construction industry.

6. Limitations of the Study

A limitation of this study is that the bibliographic dataset was extracted in November 2023. Although BIM research continues to grow rapidly, the objective of this study was to examine long-term structural trends in BIM implementation research rather than short-term publication dynamics. Previous bibliometric studies indicate that core knowledge structures, influential journals, and dominant research themes remain relatively stable over time. Future studies may extend this work by updating the dataset to capture subsequent developments and assess the continuity of emerging trends.