INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Recent Trends of BIM Research to Enhance Construction Waste  
Management  
M. Sabri*, KN. Ali, Ahmad Faiz Azizi. A Fauzi  
Faculty of Built Environment & Surveying, UTM, 81310 Johor, Malaysia.  
DOI : https://doi.org/10.51583/IJLTEMAS.2025.1411000123  
Received: 04 December 2025; Accepted: 11 December 2025; Published: 25 December 2025  
ABSTRACT  
In recent times, the rapid growth in construction waste generation has raised significant environmental and  
economic concerns in recent times. However, Building Information Modelling (BIM) has emerged as a  
promising solution for managing construction waste and promoting sustainability. BIM offers advanced  
capabilities for visualization, simulation, and data-driven decision-making, making it a valuable tool for  
optimizing waste reduction strategies in construction projects. This paper offers a thorough and in-depth review  
that examines the present and prospective trends of BIM research and its implications in the realm of construction  
waste management (CWM). Through a Bibliometric analysis, a total of 637 publications were collected from  
the "Web of Science" core database. Employing VOSviewer for analysis and visualization, co-occurrence, co-  
word analysis, cluster analysis, and co-citation analyses were conducted to explore influential authors and  
journals, high-frequency keywords, recent research trends, and potential future research directions in the field.  
The findings shed light on crucial topics in BIM for CWM, such as circular economy, recycling, waste  
estimation, and waste reduction. The study systematically analyzes and categorizes the existing literature,  
mapping the knowledge landscape, and highlights the main future trends in academic research on the integration  
of BIM and CWM. Looking ahead, future research is anticipated to focus on integrating BIM with Internet of  
Things (IoT) models, incorporating circular economy BIM systems, exploring green building using BIM models,  
implementing BIM-based design for deconstruction, and adopting multi-dimensional BIM frameworks. This  
comprehensive review provides innovative insights into the unique contributions of BIM for CWM,  
differentiating it from prior research and enhancing the paper's scholarly impact.  
Keywords: Building Information Modelling, BIM, Construction Waste Management, CWM, Sustainability,  
Construction Waste.  
INTRODUCTION  
Over the past few years, Building Information Modeling (BIM) has transformed the construction industry by  
enhancing how projects are conceptualized, designed, and executed. Simultaneously, the escalating generation  
of construction waste has raised critical environmental and economic concerns. The construction industry is a  
major contributor to waste accumulation, which results in resource depletion, land consumption, and water  
contamination [1]. In many regions, particularly developing countries, construction waste is still predominantly  
disposed of in landfills with minimal recycling efforts [2]. Consequently, the need for sustainable and efficient  
Construction Waste Management (CWM) strategies has become increasingly urgent. Despite increasing global  
commitments to sustainable construction, the sector continues to face critical challenges in managing waste  
efficiently. BIM offers theoretical promise, yet its practical implementation in CWM remains uneven and under-  
analysed across regions and project scales.  
One of the most promising solutions in this domain is BIM-driven CWM, which enables construction  
professionals to optimize waste reduction, improve material efficiency, and integrate real-time waste monitoring  
into project workflows. BIM facilitates precise waste estimation, clash detection, and simulation-based design  
modifications, ensuring that construction processes generate minimal waste. Notably, researchers have  
demonstrated how BIM can assist in rebar waste reduction through simulation-based design optimizations [6]  
and in developing waste estimation systems using BIM models [7]. Furthermore, BIM enables the automatic  
www.ijltemas.in  
Page 1314  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
extraction of key data—including object size, volume, and location—improving waste quantification accuracy  
compared to manual processes [8]. These advancements underscore BIM’s growing significance in  
revolutionizing waste management practices in the construction sector.  
RESEARCH METHODOLOGY  
A systematic review is a quantitative method for analysing scientific research progress [13]. Utilising  
bibliometric tools, the review provides an evidence-based analysis intended to inform future research directions  
and practical implementation [14]. The review employed a systematic approach to gather relevant literature from  
the Web of Science (WOS) database [10]. The choice of WOS database for this study is grounded in its  
comprehensive and reliable nature, making it a preferred resource for conducting bibliometric analyses in the  
field of Building Information Modelling (BIM) and Construction Waste Management (CWM). With access to  
over 18,000 journals and an extensive collection of cited references, WOS offers a robust platform for tracking  
the latest scholarly developments [1]. Its reputation for indexing high-quality, peer-reviewed articles ensures  
that the data used in this review is both credible and representative of current academic trends [11]. In contrast  
to other databases, such as Scopus, IEEE Xplore, or Google Scholar, WOS stands out for its superior citation  
metrics, impact factor tracking, and interdisciplinary reach, which are essential for a study that spans multiple  
domains, including civil engineering, sustainability, and environmental sciences. While Scopus similarly  
provides broad coverage, WOS is favoured for its more rigorous approach to citation tracking and its refined  
filtering mechanisms, which ensure the inclusion of high-impact research. IEEE Xplore, though a valuable  
resource for technological studies, is more focused on engineering disciplines and thus offers a narrower scope  
for the integrative and interdisciplinary focus required by this research. Moreover, Google Scholar, while  
expansive, lacks the same level of academic filtering, potentially introducing variability in citation counts and  
journal rankings, making it less reliable for bibliometric analysis. Therefore, WOS was deemed the most suitable  
database for this review [10], offering a comprehensive and consistent dataset necessary for a thorough  
investigation of the evolving role of BIM in CWM.VOSviewer software was selected for bibliometric analysis  
due to its capacity to manage extensive datasets and generate visual representations of scholarly networks [15].  
The analysis comprised four principal components: keyword co-occurrence to identify central research themes;  
author co-citation to reveal influential scholars; journal co-citation to determine key publication venues; and  
document co-citation to uncover foundational texts in the field [16]. A total of 637 publications were retrieved  
using targeted keyword searches [17]. Analysis of subject classifications indicated that 23% of the papers fell  
under Green Sustainable Science and Technology, 17% under Environmental Engineering, and 16% under Civil  
Engineering. A geographical analysis revealed that China and Australia are leading contributors, with China  
producing 229 documents and 3,084 citations, and Australia contributing 96 documents with 1,392 citations  
[18]. The dominance of China and Australia may reflect governmental emphasis on digital construction and  
environmental regulation, warranting deeper analysis of national policy influence on academic output. Table 1  
outlines the distribution of documents and citations by country.  
Building Information Modelling (BIM) in construction waste  
Topic  
management (CWM)  
Database:  
Web of Science (WoS)  
Research field: Topic  
Time frame:  
Language:  
past 5 years (2020-2024)  
English  
Scope  
Source type:  
Journal & conference paper  
"Building Information Modeling" OR "Building Information Modelling"  
OR "BIM" (Topic) AND “waste management” OR "construction waste  
management" OR "construction and demolition waste management"  
OR "construction & demolition waste management" OR “C&D waste  
management” OR “demolition waste management" (Topic) OR  
"Construction and demolition waste" OR “Construction waste “OR  
“Construction and demolition (C&D) waste” OR “C&D waste“ (Topic)  
Keywords  
wwwemas.in  
Page 1315  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Data Extracted  
19 August 2024  
n = 8,409  
Keywords BIM “OR” CWM  
Not related to construction,  
not English, or before 2020  
Keywords BIM “OR” CWM  
Keywords BIM “AND” CWM  
Full reading analysis  
Keywords co-occurrence analysis using VOSviewer  
Productive authors &  
Important Journals  
Author co-citation analysis and Journal co-citation analysis  
using VOSviewer software  
Research topic and  
research trends  
Documents co-citation and clustering analysis using  
VOSviewer software  
Figure 1. Flow diagram of the PRISMA search methodology.  
Figure 2. Publications as classified in terms of research area.  
Table 1. Top publications and citation per country.  
Country  
Documents  
Citations  
Total link  
Strength  
China  
229  
96  
3084  
1392  
785  
557  
Australia  
www.ijltemas.in  
Page 1316  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
England  
USA  
74  
46  
37  
37  
29  
29  
22  
21  
20  
15  
755  
761  
277  
394  
289  
401  
299  
264  
194  
108  
295  
262  
146  
177  
101  
107  
136  
80  
India  
Spain  
Italy  
Malaysia  
Canada  
Brazil  
Netherlands  
Egypt  
105  
51  
Keyword co-occurrence analysis  
The resulting network visualizes the relationship between keywords, represented as nodes, in a distance-based  
manner, with closer nodes indicating a stronger relationship between the keywords [19]. From the 1,994  
keywords initially identified, 76 met the threshold for detailed analysis [17]. The keywords were grouped into  
six thematic clusters, with the most prominent themes including circular economy, sustainability, recycling,  
BIM, and waste management. These clusters reflect a growing academic interest in integrating sustainable  
practices with digital innovation [17]. A summary of the most frequently occurring keywords is provided in  
Table 2.  
Table 2. Most frequently used keywords.  
Keyword  
circular economy  
Occurrences  
Total Link Strength  
91  
59  
59  
37  
33  
31  
31  
30  
30  
27  
132  
74  
89  
42  
73  
45  
52  
42  
46  
24  
construction and demolition waste  
Sustainability  
BIM  
waste management  
construction industry  
Recycling  
building information modeling  
life cycle assessment  
building information modeling  
(BIM)  
www.ijltemas.in  
Page 1317  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
construction waste  
26  
22  
21  
17  
17  
15  
11  
35  
30  
31  
35  
22  
19  
11  
Construction  
sustainable development  
built environment  
sustainable construction  
building information modelling  
building information modelling  
(BIM)  
construction projects  
construction waste management  
Reuse  
10  
10  
10  
15  
13  
26  
The six distinct clusters identified offer important insights into the key focus areas and their relationships. Firstly,  
the prominence of the "circular economy" cluster suggests a strong emphasis on exploring circular principles  
and strategies to address construction and demolition waste. This aligns with the growing global movement  
towards a more sustainable and resource-efficient built environment. However, the close associations with  
keywords like "sustainability," "recycling," and "reuse" indicate that researchers are examining the synergies  
between circular economy approaches and construction waste management.  
The "BIM" cluster highlights the increasing role of BIM technology in the context of construction waste  
management. The links to keywords such as "waste management" and "construction projects" suggest that  
researchers are investigating how BIM can be leveraged to enhance waste identification, quantification, and  
optimization throughout the construction lifecycle. This is a promising area of research, as BIM's data-rich  
modelling and visualization capabilities can potentially enable more informed decision-making and waste  
reduction strategies. While, the "recycling" and "waste management" clusters further underscore the importance  
of exploring waste treatment and disposal strategies within the research domain. The emphasis on keywords like  
"construction and demolition waste" and "reuse" indicates a focus on developing practical solutions for the  
management and valorisation of construction waste streams. While “circular economy” frequently co-occurs  
with BIM, few studies operationalise this relationship beyond conceptual alignment, pointing to a disconnect  
between academic discourse and practical application.  
Authors co-citation analysis  
By creating network maps, VOSviewer helps to uncover relationships and connections between various elements  
in the knowledge domain in a systematic manner [21]. The diagram of the author co-citation network, illustrated  
later in Figure 7, visually represents the interconnections among authors whose works are cited together in the  
same documents. This network consists of 102 nodes and 3,539 links, encompassing 22,982 authors who meet  
the minimum citation threshold of 20. To streamline the network and eliminate redundant links, we employed  
network pruning using the pathfinder function [22]. The size of each node corresponds to the frequency of co-  
citations received by a specific author, indicating their prominence within the network. The links between nodes  
signify citation relationships, reflecting the number of citations established between authors. Utilizing  
VOSviewer in this systematic review shows the co-citation patterns and author relationships within the research  
field. As per the statistical analysis conducted using VOSviewer, Figure 5 presents the findings regarding the  
frequency of author publications in BIM for CWM research. Lu WS emerges as the most prominent author with  
36 publications, followed closely by Cheng JCP with 31. Tam VWY has contributed 23 publications, while  
www.ijltemas.in  
Page 1318  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Wang J, Kim S, and Liu Y each have around 21 publications. Other notable contributors include Li H and  
Marzouk M with 20 publications each, and Chong HY with 19. Several authors, including Chan DWM, Liu Z,  
Rahman RA, Wang Q, and Zhang JS, each have 18 publications, while Othman rounds out the list with 17. These  
authors and entities have made significant contributions to the field and their works have garnered substantial  
attention and recognition. However, the concentration of influential works within a narrow author cohort  
suggests potential epistemic centralisation, possibly constraining methodological diversity in BIM-CWM  
research.  
Figure 5. Authors with the strongest citation bursts.  
The analysis of journal co-citation  
Table 4 provides a comprehensive compilation of the main sources, comprising both journals and conference  
proceedings, that have made significant contributions to the academic literature in the realm of BIM-CWM. The  
threshold for selection was set at 5, resulting in a total of 28 source from the initial 190 resource.  
Table 4: Most contributed journals in the BIM-CWM research area.  
Source  
Documents Citations  
Publication %  
Sustainability  
85  
65  
47  
19  
18  
18  
913  
1548  
315  
291  
85  
13  
10  
7
Journal Of Cleaner Production  
Buildings  
Journal Of Building Engineering  
Automation In Construction  
3
3
Engineering Construction and Architectural  
Management  
165  
3
Environmental Science and Pollution Research  
16  
125  
3
www.ijltemas.in  
Page 1319  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Waste Management  
15  
14  
10  
10  
261  
109  
142  
96  
2
2
2
2
Waste Management & Research  
Construction And Building Materials  
Journal Of Construction Engineering and  
Management  
Resources Conservation and Recycling  
Applied Sciences-Basel  
10  
9
359  
55  
37  
57  
70  
37  
83  
2
1
1
1
1
1
1
Sustainable Cities and Society  
9
Building And Environment  
8
International Journal of Construction Management  
Built Environment Project and Asset Management  
8
7
International Journal of Environmental Research and  
Public Health  
7
Recycling  
6
5
5
48  
54  
20  
1
1
1
Energy And Buildings  
International Journal of Building Pathology and  
Adaptation  
Materials  
5
5
5
24  
188  
15  
1
1
1
Renewable & Sustainable Energy Reviews  
Smart And Sustainable Built Environment  
Table 4 showcases the leading sources of academic publications in the context of BIM research related to CWM,  
utilizing data collected from the WOS database. The table displays the document and citation counts for each  
source. Notably, the journal "Sustainability" emerges as the prominent contributor, featuring 85 published  
documents and an impressive 913 citations. On the other hand, the “Journal of Cleaner Production” follows  
closely with 65 documents and 1548 citations. Other notable sources include “Buildings” with 47 documents  
and 315 citations, “Journal of Building Engineering” with 19 documents and 291 citations, and “Automation in  
Construction” with 18 documents and 85 citations. Additionally, “Engineering Construction and Architectural  
Management” has 18 documents and 165 citations, while “Environmental Science and Pollution Research” has  
16 documents and 125 citations. “Waste Management” and “Waste Management & Research” are also  
prominent sources with 15 documents and 261 citations, and 14 documents and 109 citations, respectively. Also,  
Figure 7 illustrates the Journal co-citations network diagram, showcasing the interrelationships and  
collaborations among different journals.  
Documents co-citation analysis  
The document co-citation network is a valuable resource for graphically representing and structuring the research  
field, relying on citation relationships among the selected publications. In this study, we created a document co-  
citation network comprising 197 nodes and 12,806 links, with a minimum of 15 citations per document. Figure  
www.ijltemas.in  
Page 1320  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
6 visually presents this network, with each node representing a specific document, and its size reflecting the  
frequency of co-citations it has received. The connections between nodes illustrate the co-citation relationships  
among the documents.  
VOSviewer utilizes key metrics such as mean silhouette (S) and modularity (Q) to assess the structural properties  
of the network. These metrics provide insights into the degree of cohesion within clusters and the extent of loose  
coupling in the co-citation network, signifying the presence of distinct and interconnected groups of related  
publications within the research field. A value greater than 0.3 suggests that the network exhibits significant  
clustering [23]. On the other hand, the silhouette score measures the heterogeneity of network clustering. A score  
greater than 0.5 indicates a heterogeneous clustering pattern within the network. These metrics provide  
significant insights into the structure and clustering patterns within the document co-citation network.  
Furthermore, the citation analysis was performed to identify the most highly cited documents among the 637  
publications. To ensure precision and relevance, only papers with at least 50 citations were considered. As a  
result, 25 documents met this threshold, as presented in Figure 7.  
Co-authorship Network Analysis  
To evaluate the structural properties of the network, VOSviewer utilizes essential metrics, such as the modularity  
(Q) value, which indicates that the network displays significant clustering [33]. On the other hand, the silhouette  
score measures the heterogeneity of network clustering. A score greater than 0.5 indicates a heterogeneous  
clustering pattern within the network. These measurements offer insightful information about the structure and  
clustering patterns within the document co-citation network.  
Figure 8 displays a co-authorship network that highlights the collaborative relationships among researchers who  
have made significant contributions to the field BIM related to CWM. For inclusion in the network, authors  
needed to have at least two documents and one citation. Among the 2088 authors in the field, 280 authors fulfilled  
these criteria and were represented in the network. The network provides insights into the collaborative patterns  
and connections among these influential authors in the field of BIM related to CWM.  
Figure 6. Journal co-citations network.  
www.ijltemas.in  
Page 1321  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Figure 7. Links visualization of co-citations analysis for the collected data.  
Figure 8. Link visualization among authors.  
www.ijltemas.in  
Page 1322  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
DISCUSSION AND FINDINGS  
The existing literature reveals a gap in recent knowledge mapping analyses at the intersection of BIM and CWM  
practices. While substantial research has been conducted on BIM implementation, there remains a lack of  
comprehensive studies examining its application in CWM across diverse geographic contexts. Addressing this  
gap necessitates a systematic mapping of the current state of BIM research and its integration into CWM  
globally. This approach enables an understanding of key trends, emerging challenges, regional disparities, and  
future research trajectories.  
This study analyzed the global distribution of innovation in BIM for CWM research and identified publication  
trends. A total of 637 relevant documents were extracted from the Web of Science (WOS) database, forming the  
foundation for a detailed examination of research progress and focus areas. The findings indicate that Asia is at  
the forefront of BIM-CWM research, followed by Australia, Europe, and North America, while Africa and South  
America remain underrepresented.  
The dominance of Asian countries, particularly China, in BIM-CWM research can be attributed to strong  
government policies, substantial investments in technological innovations, and an increasing emphasis on  
sustainable construction practices. In contrast, Africa and South America face significant challenges, including  
limited access to resources, inadequate infrastructure, and insufficient research funding. Additionally, socio-  
economic constraints, cultural barriers, and a lack of specialized expertise hinder the adoption and  
implementation of BIM for CWM in these regions.  
A deeper analysis of the publication trends over time suggests a sharp increase in BIM-CWM research output  
between 2020 and 2022, reaching its peak in 2022. The growing body of literature in this domain aligns with the  
global shift toward sustainable construction and circular economy principles. However, it is crucial to assess  
whether this research surge has translated into practical applications and policy implementations.  
Figure 9. Documents by year of publication.  
Analysis of Key Themes and Trends in BIM-CWM Research  
1. Keyword Co-occurrence and Research Themes  
The keyword co-occurrence analysis identified dominant themes in the BIM-CWM research landscape. These  
include circular economy, waste estimation, recycling, and sustainable design. In this in-deep analysis, we will  
delve into the clusters that have been identified and explore the most cited documents within each cluster. By  
doing so, we aim to gain insights into the key recent research topics and areas of interest. In conclusion, the  
www.ijltemas.in  
Page 1323  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
study has emphasized the significance of analysing the most relevant research papers, categorized by their  
occurrence frequency in distinct research areas. Through the final screening process, we have successfully  
identified 57 publications, out of the 637 papers analyzed in this study, all 57 articles included in the analysis  
were closely aligned with the research topic and underwent thorough and in-depth reading to conduct trend  
analysis. This rigorous approach has facilitated a thorough exploration and analysis of the current research trends  
and principal focus areas within the domain of BIM for CWM. Nevertheless, the scarcity of published documents  
in this domain emphasizes the pressing necessity for further research in this field, as also acknowledged in a  
previous study by [36].  
The field of BIM for CWM exhibits research trends and primary focus areas categorized into three main groups:  
reviews, practical applications, and innovative models. In the forthcoming section, we will present and examine  
recent research trends by analysing relevant publications. These trends will be categorized according to the  
frequency of published documents in each research area. This analysis offers significant insights into the current  
advancements and focal points within the domain of BIM for CWM. Figure 11. displays the three primary  
categories and their respective subordinate clusters, providing a visual representation of the relationships and  
connections within the research trends of the study.  
Figure 10. The framework of BIM-CWM research clusters.  
The clustering analysis further classified the literature into three main categories:  
I) Reviews:  
Among the documents selected for analysis, twelve review articles were identified [37–40, 88–91], each offering  
a unique perspective on the intersection of BIM-CWM. These review articles encompassed diverse themes, such  
as the scientific mapping of CWM [41, 42, 91], reviewing BIM research for CWM [88] exploration of  
information technologies related to CWM [38, 42, 43], the examination of BIM-specific challenges in the context  
of CWM [44, 45], or other related topics [89, 90]. By conducting thorough literature syntheses, these reviews  
have offered valuable insights into the current state of knowledge, shedding light on essential areas for future  
research. Moreover, they have deepened our understanding of the interdependent relationship between BIM and  
CWM. However, the completed reviews have not yet adequately covered crucial practical areas, and they also  
lack a country-specific focus, which is essential to obtain practical results and assist stakeholders in  
implementing sustainable solutions, especially in developing countries.  
www.ijltemas.in  
Page 1324  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
II) Practical Applications:  
The literature's third section delves into the practical implementation of BIM in the context of CWM practices  
and techniques. Utilizing clustering analysis and thorough reading, [92] for example, four primary clusters have  
been identified in recent research publications:  
Circular Economy: Recent research trends emphasize sustainability in developed countries [29, 41, 54–56].  
BIM applications facilitate intelligent waste recycling and resource management throughout construction  
projects [57]. Integrating tools like life cycle assessment (LCA), waste management plans (WMP), and BIM  
reduces greenhouse gas emissions [37]. Holistic approaches involving all stakeholders throughout the  
construction lifecycle are crucial for waste reduction and environmental impact minimization [39].  
Recycling: Implementing the 3R strategy (reduce, recycle, reuse) in CWM is vital for sustainability. BIM  
frameworks support efficient waste recovery and recycling during construction [60]. Tools within BIM enable  
environmental assessments and informed recycling decisions [61, 62]. Sustainable urban mining practices are  
enhanced through data capture and visualization [63]. These efforts guide eco-conscious CWM, promoting  
resource efficiency and environmental preservation [64].  
BIM-based Waste Estimation: Innovative waste management practices necessitate accurate estimation of  
construction waste. Studies [60, 65, 66] use BIM to automate waste quantification and integrate it with models  
like LCA and GIS for better accuracy and decision-making. Precise databases and regional considerations are  
essential for effective estimation [43].  
BIM-based Waste Reduction: BIM aids in waste reduction by enabling methodologies like BIM-LCA for  
quantitative assessments. Studies [61, 67] demonstrate BIM's role in minimizing waste during design and  
construction phases. Approaches like automated BIM-based systems [71, 72] and predictive models [73]  
contribute to sustainable construction practices. However, research gaps in BIM implementation, project  
management, and cost studies highlight the need for further exploration.  
III) Innovative Models:  
Among the innovative BIM models aimed at enhancing CWM, scholars have explored various approaches to  
advance the field. Some researchers, for example, have concentrated on using BIM for fostering green building,  
as noted in [50, 51]. A key study by Schamne [97] presents a conceptual BIM model using Industry Foundation  
Classes (IFC) standards, addressing CDW management through improved resource efficiency and  
environmental analysis. Traditional green building rating systems often use a building-centric evaluation, while  
BIM has enabled an execution platform [50]. Adopting a user-centric approach, however, allows for a more  
detailed assessment of sustainability, paving the way for customized evaluation systems. Recent work also  
highlights the integration of the Internet of Things (IoT) within BIM, enhancing CWM practices [36, 52, 53].  
Additional frameworks have been developed, such as the Waste Management Process Flow Model (WMPFM),  
which utilizes an Android application for CWM [54]. Other studies address the economic potential of  
construction waste audits [47] and the development of multi-dimensional BIM frameworks for CWM [8]. The  
incorporation of BIM-based Design for Deconstruction (DfD) as a sustainable strategy has also gained traction,  
despite [48] indicating higher costs of deconstruction and maintenance over conventional methods. This  
emphasizes the need for a BIM-integrated, cost-effective approach. Likewise, the assessment of End-of-Life  
(EOL) and Life-Cycle Assessment (LCA) within BIM frameworks underscores the importance of evaluating  
environmental impacts across the building lifecycle [49].  
2. Influence of Leading Researchers and Journals  
The citation analysis revealed that influential scholars such as Lu, Jin, Yuan, Tam, and Ajayi have significantly  
contributed to advancing knowledge in BIM-CWM. Their research has shaped key debates on the role of BIM  
in sustainable construction waste management. Leading journals in this field include Sustainability, Journal of  
Cleaner Production, and Buildings, which provide critical insights into the evolving research landscape.  
www.ijltemas.in  
Page 1325  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Implications of Research Trends  
1. Circular Economy and BIM for CWM  
One of the most significant emerging trends is the integration of BIM into circular economy strategies. Studies  
have highlighted how BIM can facilitate intelligent waste recycling management, optimize resource utilization,  
and promote material reuse. However, a critical analysis of these studies reveals a gap in holistic approaches that  
encompass all stages of construction, from design and procurement to demolition and deconstruction. The  
existing research primarily focuses on specific components, lacking a comprehensive framework that integrates  
all stakeholders, including policymakers, contractors, and waste management authorities.  
2. BIM for Waste Estimation and Reduction  
Accurate waste estimation is crucial for effective CWM, and BIM has emerged as a promising tool in this regard.  
Several studies have introduced BIM-integrated estimation models, incorporating LCA and GIS to enhance  
precision. However, a key limitation is the reliance on regional databases for waste quantification indices, which  
can lead to inaccuracies when applied to different geographical contexts. Future research should focus on  
developing standardized, globally applicable waste estimation models that account for regional variations in  
construction practices and material use.  
BIM's role in waste reduction is another critical area of research, with studies demonstrating its ability to  
streamline planning and minimize material waste. Nevertheless, a gap remains in assessing the economic  
feasibility of these strategies. While BIM-based Design for Deconstruction (DfD) has gained traction, its  
adoption is hindered by the higher costs associated with deconstruction compared to conventional demolition.  
There is a pressing need for further research on cost-benefit analyses to support the wider implementation of  
BIM-driven waste reduction strategies.  
3. Integration of IoT and AI in BIM for CWM  
Recent studies have explored the integration of IoT and AI with BIM to enhance construction waste  
management. The potential benefits include real-time tracking of waste generation, predictive analytics for waste  
minimization, and automated decision-making processes. However, the practical implementation of these  
technologies remains limited due to technical challenges, high costs, and the lack of industry-wide adoption  
frameworks. Future research should investigate scalable and cost-effective solutions for integrating IoT and AI  
into BIM for sustainable CWM.  
FUTURE RESEARCH TRENDS ON BIM FOR CWM  
After exploring the current key topics in the BIM and CWM field, the subsequent section will investigate future  
research trends derived from a systematic analysis of the reviewed literature, identification of recurring research  
gaps, keyword co-occurrence analysis, and thematic clustering. The key research avenues include:  
1) Future research should explore the integration of green building systems with BIM models, leveraging BIM's  
capabilities in sustainable construction [74–77]. This opens up new possibilities to develop innovative  
frameworks aimed at enhancing CWM practices towards achieving sustainability.  
2) Exploring the possibilities of recycling and reducing construction waste to achieve a circular economy, in  
comprehensive approach, through BIM models opens up numerous promising avenues for future research [78,  
79].  
3) IoT integrated BIM models for CWM enhancement enhancement [60, 80–82]: The rising enthusiasm for  
combining IoT solutions with BIM platforms has resulted in a unified perspective of extensive building  
information merged with real-time sensor data. These distinct capabilities present valuable opportunities for  
enhancing CWM practices.  
www.ijltemas.in  
Page 1326  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
4) GIS and BIM integration for CWM [83, 84, 95]: BIM and GIS have become key technologies in construction  
elements [14]. Their integration offers improved building planning efficiency, rationality, and standardization,  
providing valuable avenues for enhancing CWM practices.  
5) BIM novel system for deconstruction and BIM for Deconstruction (BIMfD) [45, 52, 85, 86]: while BIM can  
effectively contribute to reducing construction waste through EOL scenario selection, the analysis identifies  
research gaps in the entire lifecycle of materials, from deconstruction to material/component banks, and back to  
deconstruction.  
6) EOL and LCA BIM integrated frameworks [45, 87]: The BIM-LCA framework shows significant promise in  
evaluating the environmental consequences of diverse disposal approaches during the EOL phase, presenting  
valuable practical solutions for CWM.  
The analysis presented in this study is the outcome of an exhaustive and comprehensive reading of the carefully  
curated set of publications closely aligned with the research topic of BIM for CWM. The objective of this  
analysis is to offer guidance for future investigations in this field.  
Potential Research Directions and Methodological Approaches for Advancing BIM-Enabled CWM  
The integration of BIM within circular economy frameworks has emerged as a dominant trend, aimed at  
improving resource efficiency and reducing waste in construction [14]. However, these approaches often fail to  
consider the full lifecycle of construction processes or involve all relevant stakeholders in the decision-making  
process [14]. While BIM has shown potential in areas like waste estimation and reduction, there remains a  
pressing need for standardised frameworks that can be tailored to specific regional contexts and construction  
practices [16]. Emerging technologies such as IoT and GIS offer promising potential for enhanced waste tracking  
and planning, yet their implementation is often hindered by high costs, technical challenges, and infrastructure  
limitations [17]. These challenges suggest that while BIM’s role in CWM is progressing, its practical application  
in diverse contexts is far from straightforward.  
One key area for investigation is the integration of green building systems within BIM models. By leveraging  
BIM's versatile modelling capabilities, researchers could develop innovative frameworks to seamlessly  
incorporate sustainable design elements and assess their impact on CWM practices, ultimately contributing to  
the broader goal of enhancing environmental performance in the construction industry. Furthermore, the  
possibilities of utilising BIM to enable circular economy approaches in construction warrant scholarly scrutiny.  
Exploring how BIM can support the recycling and reuse of materials, as well as the establishment of material  
banks, presents a compelling research agenda with the potential to drive meaningful progress towards waste  
reduction and material circularity.  
The integration of emerging technologies, such as the IoT, with BIM platforms also merits academic inquiry.  
Investigating how the fusion of real-time sensor data and comprehensive building information can elevate CWM  
practices could yield valuable insights and practical solutions for the industry. Equally important is the  
exploration of the synergies between BIM and GIS in the context of CWM. Integrating these complementary  
technologies offers the promise of enhanced planning, monitoring, and optimisation of construction waste  
management activities, representing a fertile ground for scholarly exploration. Additionally, the development of  
BIM-based frameworks for deconstruction planning and material/component bank management holds  
significant promise. Addressing the research gaps in this area could contribute to a more holistic understanding  
of the entire lifecycle of construction materials, from deconstruction to reuse and recycling. Finally, the  
integration of BIM and Life Cycle Assessment (LCA) techniques emerges as a valuable research direction, with  
the potential to inform decision-making processes around end-of-life scenarios and their environmental  
implications. Pursuing such an integrated approach could yield practical solutions for sustainable CWM  
practices.  
Collectively, these research avenues underscore the evolving potential of BIM in addressing the pressing  
challenges of CWM, with the ultimate goal of enhancing sustainability in the built environment. However,  
despite technical advancements, BIM adoption for CWM is frequently hampered by fragmented stakeholder  
www.ijltemas.in  
Page 1327  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
communication, insufficient training, and resistance to process change at the site level. Future studies should  
integrate behavioural science to understand resistance to BIM adoption at the organisational level, and  
collaborate with policy researchers to shape adaptive regulatory frameworks.  
CONCLUSIONS  
This systematic review provides a thorough analysis of the applications of BIM in construction waste  
management, categorising the literature into theoretical frameworks, practical applications, and innovative  
modelling approaches. Despite significant progress in research output, there remains a notable gap in terms of  
practical adoption and regional adaptation of BIM for CWM. To bridge these gaps, collaborative efforts between  
academics, practitioners, and policymakers are essential, with a focus on developing flexible, region-specific  
BIM frameworks that can drive sustainable construction practices and contribute to the global transition towards  
a circular economy. Several key areas for future research have been identified. These include: the integration of  
BIM with green building certification systems to promote sustainable construction; the development of  
regionally adaptable waste estimation models to address specific local challenges; the further incorporation of  
IoT and GIS into BIM to improve waste tracking and planning capabilities; the development of BIM-based  
frameworks for deconstruction and material reuse; and the expansion of comprehensive lifecycle and end-of-life  
assessment frameworks within BIM platforms [14][18]. Future studies should also explore the potential of  
artificial intelligence (AI) and machine learning (ML) to optimise waste management strategies through BIM,  
offering the prospect of more dynamic, responsive, and data-driven approaches to CWM.  
The study contributes to a deeper theoretical understanding of BIM’s evolving role for CWM, highlighting its  
growing application in enhancing efficiency and sustainability. However, it acknowledges limitations due to  
reliance on a single database, suggesting that future research should incorporate broader sources. The findings  
of this study underscore the growing prominence of BIM in the field of CWM. While research output has  
increased substantially, critical gaps remain in terms of in-depth analyses, practical implementation, and policy  
integration. Addressing these gaps requires a concerted effort among researchers, industry stakeholders, and  
policymakers to develop comprehensive, scalable, and regionally adaptable BIM-CWM frameworks. By doing  
so, the construction industry can achieve more effective and sustainable waste management practices,  
contributing to global sustainability goals and the circular economy transition. This review highlights the need  
to reorient BIM-CWM research toward context-specific, stakeholder-inclusive frameworks. Without bridging  
the policy-practice-research divide, the full potential of BIM in addressing construction waste will remain  
unrealised.  
Credit Authorship Contribution Statement  
M. Sabri, KN. Ali Investigation, Formal analysis Methodology and Writing original draft; M. Sabri, KN. Ali  
Conceptualization, Validation, Writing - reviewing & editing, Supervision and Resources; KN. Ali, Ahmad Faiz  
Azizi. A Fauzi Supervision, reviewing and editing.  
DECLARATION OF COMPETING INTEREST  
The authors declare that the work reported in this study was not affected by any conflicting financial interests or  
personal connections.  
ACKNOWLEDGEMENTS  
(Research grant number Q.J130000.3852.31J16)  
The authors would like to thank FABU, UTM for funding this work under an internal grant  
NO.Q.J130000.3852.31J16.  
www.ijltemas.in  
Page 1328  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
REFERENCES  
1.  
2.  
3.  
4.  
5.  
6.  
7.  
8.  
Wang Q. Distribution features and intellectual structures of digital humanities: A bibliometric analysis.  
Journal of Documentation. 2018;74(1):223–46.  
Duan H, Hu J, Tan Q, Liu L, Wang Y, Li J. Systematic characterization of generation and management of  
e-waste in China. Environmental Science and Pollution Research. 2016;23:1929–43.  
Succar B. Building information modelling framework: A research and delivery foundation for industry  
stakeholders. Autom Constr. 2009;18(3):357–75.  
Bryde D, Broquetas M, Volm JM. The project benefits of building information modelling (BIM).  
International journal of project management. 2013;31(7):971–80.  
Abazid M, Gökçekuş H, Çelik T. Implementation of TQM and the Integration of BIM in the Construction  
Management Sector in Saudi Arabia. Advances in Materials Science and Engineering. 2021;2021:1–9.  
Lu Y, Wu Z, Chang R, Li Y. Building Information Modeling (BIM) for green buildings: A critical review  
and future directions. Autom Constr. 2017;83:134–48.  
Cheng JCP, Ma LYH. A BIM-based system for demolition and renovation waste estimation and planning.  
Waste management. 2013;33(6):1539–51.  
Bakchan A, Faust KM, Leite F. Seven-dimensional automated construction waste quantification and  
management framework: Integration with project and site planning. Resour Conserv Recycl.  
2019;146:462–74.  
9.  
Bankar RS, Lihitkar SR. Journal of Advancements in Library Sciences Science Mapping and Visualization  
Tools Used for Bibliometric and Scientometric Studies: A Comparative Study. 2019;382–94. Available  
from: www.stmjournals.com  
10. Bakkalbasi N, Bauer K, Glover J, Wang L. Three options for citation tracking: Google Scholar, Scopus and  
Web of Science. Biomed Digit Libr. 2006 Jun 29;3.  
11. Aghaei Chadegani A, Salehi H, Md Yunus MM, Farhadi H, Fooladi M, Farhadi M, et al. A comparison  
between two main academic literature collections: Web of science and scopus databases. Asian Soc Sci.  
2013 Apr 27;9(5):18–26.  
12. Mongeon P, Paul-Hus A. The journal coverage of Web of Science and Scopus: a comparative analysis.  
Scientometrics. 2016 Jan 1;106(1):213–28.  
13. Yalcinkaya M, Singh V. Patterns and trends in Building Information Modeling (BIM) research: A Latent  
Semantic Analysis. Autom Constr. 2015 Nov 5;59:68–80.  
14. Su HN, Lee PC. Mapping knowledge structure by keyword co-occurrence: A first look at journal papers in  
Technology Foresight. Scientometrics. 2010;85(1):65–79.  
15. null S, Kumar SS. Scientometric Analysis of Natural Disaster Management Research. Nat Hazards Rev  
[Internet]. 2021 May 1;22(2):04021008. Available from: https://doi.org/10.1061/(ASCE)NH.1527-  
6996.0000447  
16. Babalola A, Musa S, Akinlolu MT, Haupt TC. A bibliometric review of advances in building information  
modeling (BIM) research. Journal of Engineering, Design and Technology [Internet]. 2023 Jan  
1;21(3):690–710. Available from: https://doi.org/10.1108/JEDT-01-2021-0013  
17. Boyack KW, van Eck NJ, Colavizza G, Waltman L. Characterizing in-text citations in scientific articles:  
A large-scale analysis. J Informetr. 2018 Feb 1;12(1):59–73.  
18. Martins J, Gonçalves R, Branco F. A bibliometric analysis and visualization of e-learning adoption using  
VOSviewer. Univers Access Inf Soc. 2022;  
19. Perianes-Rodriguez A, Waltman L, van Eck NJ. Constructing bibliometric networks: A comparison  
between full and fractional counting. J Informetr. 2016;10(4):1178–95.  
20. Van Eck NJ, Waltman L. Manual for VOSviewer version 1.6. 8. CWTS meaningful metrics Universiteit  
Leiden. 2018;  
21. Jiang W, Martek I, Hosseini MR, Chen C. Political risk management of foreign direct investment in  
infrastructure projects: Bibliometric-qualitative analyses of research in developing countries. Engineering,  
Construction and Architectural Management. 2021;28(1):125–53.  
22. Chen C, Morris S. Visualizing Evolving Networks: Minimum Spanning Trees versus Pathfinder Networks.  
2003.  
23. Kouhizadeh M, Sarkis J. Blockchain practices, potentials, and perspectives in greening supply chains.  
Sustainability. 2018;10(10):3652.  
www.ijltemas.in  
Page 1329  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
24. Kabirifar K, Mojtahedi M, Wang C, Tam VWY. Construction and demolition waste management  
contributing factors coupled with reduce, reuse, and recycle strategies for effective waste management: A  
review.  
J
Clean  
Prod  
[Internet].  
2020;263:121265.  
Available  
from:  
https://www.sciencedirect.com/science/article/pii/S0959652620313123  
25. López Ruiz LA, Roca Ramón X, Gassó Domingo S. The circular economy in the construction and  
demolition waste sector – A review and an integrative model approach. J Clean Prod [Internet].  
2020;248:119238.  
Available  
from:  
https://www.sciencedirect.com/science/article/pii/S0959652619341083  
26. Tang Q, Ma Z, Wu H, Wang W. The utilization of eco-friendly recycled powder from concrete and brick  
waste in new concrete: A critical review. Cem Concr Compos [Internet]. 2020;114:103807. Available from:  
https://www.sciencedirect.com/science/article/pii/S0958946520303139  
27. Aslam MS, Huang B, Cui L. Review of construction and demolition waste management in China and USA.  
J
Environ  
Manage  
[Internet].  
2020;264:110445.  
Available  
from:  
https://www.sciencedirect.com/science/article/pii/S0301479720303790  
28. Razzaq A, Sharif A, Najmi A, Tseng ML, Lim MK. Dynamic and causality interrelationships from  
municipal solid waste recycling to economic growth, carbon emissions and energy efficiency using a novel  
bootstrapping autoregressive distributed lag. Resour Conserv Recycl [Internet]. 2021;166:105372.  
Available from: https://www.sciencedirect.com/science/article/pii/S092134492030687X  
29. Khan SAR, Razzaq A, Yu Z, Miller S. Industry 4.0 and circular economy practices: A new era business  
strategies for environmental sustainability. Bus Strategy Environ. 2021;30(8):4001–14.  
30. Hossain MdU, Ng ST, Antwi-Afari P, Amor B. Circular economy and the construction industry: Existing  
trends, challenges and prospective framework for sustainable construction. Renewable and Sustainable  
Energy  
Reviews  
[Internet].  
2020;130:109948.  
Available  
from:  
https://www.sciencedirect.com/science/article/pii/S1364032120302392  
31. Munaro MR, Tavares SF, Bragança L. Towards circular and more sustainable buildings: A systematic  
literature review on the circular economy in the built environment. J Clean Prod [Internet].  
2020;260:121134.  
Available  
from:  
https://www.sciencedirect.com/science/article/pii/S0959652620311811  
32. Wang M, Wang CC, Sepasgozar S, Zlatanova S. A systematic review of digital technology adoption in off-  
site construction: Current status and future direction towards industry 4.0. Buildings. 2020;10(11):204.  
33. Newman MEJ. Modularity and community structure in networks. Proceedings of the National Academy of  
Sciences  
[Internet].  
2006  
Jun  
6;103(23):8577–82.  
Available  
from:  
https://doi.org/10.1073/pnas.0601602103  
34. Olawumi TO, Chan DWM, Wong JKW, Chan APC. Barriers to the integration of BIM and sustainability  
practices in construction projects: A Delphi survey of international experts. Journal of Building  
Engineering. 2018 Jul;20:60–71.  
35. Saka AB, Chan DWM. Knowledge, skills and functionalities requirements for quantity surveyors in  
building information modelling (BIM) work environment: an international Delphi study. Architectural  
Engineering and Design Management. 2020;16(3):227–46.  
36. Ali KN, Alhajlah HH, Kassem MA. Collaboration and Risk in Building Information Modelling (BIM): A  
Systematic Literature Review. Buildings. 2022;12(5):571.  
37. Caldas LR, Silva M V, Silva VP, Carvalho MTM, Toledo RD. How Different Tools Contribute to Climate  
Change Mitigation in a Circular Building Environment?-A Systematic Literature Review. Sustainability.  
2022;14(7).  
38. Sepasgozar SME, Mair DF, Tahmasebinia F, Shirowzhan S, Li H, Richter A, et al. Waste management and  
possible directions of utilising digital technologies in the construction context. J Clean Prod. 2021;324.  
39. Soyinka OA, Wadu MJ, Hewage U, Oladinrin TO. Scientometric review of construction demolition waste  
management: a global sustainability perspective. Environ Dev Sustain. 2022;  
40. Zhu SY, Li DZ, Zhu J, Feng HB. Towards a Data-Rich Era: A Bibliometric Analysis of Construction  
Management from 2000 to 2020. BUILDINGS. 2022;12(12).  
41. Jin RY, Yuan HP, Chen Q. Science mapping approach to assisting the review of construction and  
demolition waste management research published between 2009 and 2018. Resour Conserv Recycl.  
2019;140:175–88.  
www.ijltemas.in  
Page 1330  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
42. Nawaz A, Chen J, Su X. Exploring the trends in construction and demolition waste (C&DW) research: A  
scientometric analysis approach. SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS.  
2023;55.  
43. Li CZD, Zhao YY, Xiao B, Yu B, Tam VWY, Chen Z, et al. Research trend of the application of  
information technologies in construction and demolition waste management. J Clean Prod. 2020;263.  
44. Liao LH, Zhou KX, Fan C, Ma YY. Evaluation of Complexity Issues in Building Information Modeling  
Diffusion Research. Sustainability. 2022;14(5).  
45. Akbarieh A, Jayasinghe LB, Waldmann D, Teferle FN. BIM-Based End-of-Lifecycle Decision Making and  
Digital Deconstruction: Literature Review. Sustainability. 2020;12(7).  
46. Salehabadi ZM, Ruparathna R. User-centric sustainability assessment of single family detached homes  
(SFDH): A BIM-based methodological framework. JOURNAL OF BUILDING ENGINEERING.  
2022;50.  
47. Shukra ZA, Zhou Y. Holistic green BIM: a scientometrics and mixed review. ENGINEERING  
CONSTRUCTION AND ARCHITECTURAL MANAGEMENT. 2021;28(9):2273–99.  
48. Huang T, Kou SC, Liu DY, Li DW, Xing F. A BIM-GIS-IoT-Based System for Excavated Soil Recycling.  
BUILDINGS. 2022;12(4).  
49. Kang K, Besklubova S, Dai YQ, Zhong RY. Building demolition waste management through smart BIM:  
A case study in Hong Kong. WASTE MANAGEMENT. 2022;143:69–83.  
50. Hu XY, Zhou Y, Vanhullebusch S, Mestdagh R, Cui ZY, Li JB. Smart building demolition and waste  
management frame with image-to-BIM. JOURNAL OF BUILDING ENGINEERING. 2022;49.  
51. Spisakova M, Mesaros P, Mandicak T. Construction Waste Audit in the Framework of Sustainable Waste  
Management in Construction Projects-Case Study. BUILDINGS. 2021;11(2).  
52. Aziminezhad M, Taherkhani R. BIM for deconstruction: A review and bibliometric analysis. Journal of  
Building  
Engineering  
[Internet].  
2023;73:106683.  
Available  
from:  
https://www.sciencedirect.com/science/article/pii/S2352710223008628  
53. Zoghi M, Kim S. Dynamic modeling for life cycle cost analysis of BIM-based construction waste  
management. Sustainability. 2020;12(6):2483.  
54. Wang JJ, Wei JJ, Liu ZS, Huang C, Du XL. Life cycle assessment of building demolition waste based on  
building information modeling. Resour Conserv Recycl. 2022;178.  
55. Xue K, Hossain MU, Liu M, Ma M, Zhang Y, Hu M, et al. BIM integrated LCA for promoting circular  
economy towards sustainable construction: An analytical review. Sustainability. 2021;13(3):1310.  
56. AlJaber A, Alasmari E, Martinez-Vazquez P, Baniotopoulos C. Life Cycle Cost in Circular Economy of  
Buildings by Applying Building Information Modeling (BIM): A State of the Art. Buildings.  
2023;13(7):1858.  
57. Charef R. The use of Building Information Modelling in the circular economy context: Several models and  
a new dimension of BIM (8D). Clean Eng Technol. 2022;7:100414.  
58. Bin Ismail ZA. A critical study of the existing issues in circular economy practices during movement  
control order: can BIM fill the gap? ENGINEERING CONSTRUCTION AND ARCHITECTURAL  
MANAGEMENT. 2022;  
59. Shashi, Centobelli P, Cerchione R, Ertz M, Oropallo E. What we learn is what we earn from sustainable  
and circular construction. J Clean Prod. 2023;382.  
60. Jayasinghe LB, Waldmann D. Development of a BIM-Based Web Tool as a Material and Component Bank  
for a Sustainable Construction Industry. Sustainability. 2020;12(5).  
61. Guerra BC, Leite F, Faust KM. 4D-BIM to enhance construction waste reuse and recycle planning: Case  
studies on concrete and drywall waste streams. WASTE MANAGEMENT. 2020;116:79–90.  
62. Llatas C, Quinones R, Bizcocho N. Environmental Impact Assessment of Construction Waste Recycling  
versus Disposal Scenarios Using an LCA-BIM Tool during the Design Stage. RECYCLING. 2022;7(6).  
63. Miatto A, Sartori C, Bianchi M, Borin P, Giordano A, Saxe S, et al. Tracking the material cycle of Italian  
bricks with the aid of building information modeling. J Ind Ecol. 2022;26(2):609–26.  
64. Raskovic M, Ragossnig AM, Kondracki K, Ragossnig-Angst M. Clean construction and demolition waste  
material cycles through optimised pre-demolition waste audit documentation: A review on building  
material assessment tools. WASTE MANAGEMENT & RESEARCH. 2020;38(9):923–41.  
www.ijltemas.in  
Page 1331  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
65. Cai GC, Waldmann D. A material and component bank to facilitate material recycling and component reuse  
for a sustainable construction: concept and preliminary study. Clean Technol Environ Policy.  
2019;21(10):2015–32.  
66. Quinones R, Llatas C, Montes M V, Cortes I. Quantification of Construction Waste in Early Design Stages  
Using Bim-Based Tool. RECYCLING. 2022;7(5).  
67. Su S, Li SM, Ju JY, Wang Q, Xu Z. A building information modeling-based tool for estimating building  
demolition waste and evaluating its environmental impacts. WASTE MANAGEMENT. 2021;134:159–69.  
68. Pellegrini L, Locatelli M, Meschini S, Pattini G, Seghezzi E, Tagliabue LC, et al. Information Modelling  
Management and Green Public Procurement for Waste Management and Environmental Renovation of  
Brownfields. Sustainability. 2021;13(15).  
69. Shafiq MM, Al-Mekhlafi AA, Al-Fakih A, Zawawi NA, Mohamed AM, Khallaf R, et al. Beneficial Effects  
of 3D BIM for Pre-Empting Waste during the Planning and Design Stage of Building and Waste Reduction  
Strategies. Sustainability. 2022;14(6).  
70. Hosny S, Ibrahim AH, Nabil Y. REDUCING REINFORCED CONCRETE MATERIALS WASTE IN  
CONSTRUCTION PROJECTS USING BUILDING INFORMATION MODELING IN EGYPT.  
JOURNAL OF INFORMATION TECHNOLOGY IN CONSTRUCTION. 2023;28:332–45.  
71. Vasudevan G. Study on adoption of building information modelling in reducing construction waste in  
Malaysia. In: IOP Conference Series: Earth and Environmental Science. IOP Publishing; 2019. p. 042002.  
72. Wang WJ. Automatic System Design of Assembly Building Components for Sustainable Building Projects  
Based on BIM Technology. Math Probl Eng. 2022;2022.  
73. Liu HX, Sydora C, Altaf MS, Han S, Al-Hussein M. Towards sustainable construction: BIM-enabled  
design and planning of roof sheathing installation for prefabricated buildings. J Clean Prod.  
2019;235:1189–201.  
74. Negendahl K, Barholm-Hansen A, Andersen R. Parametric Stock Flow Modelling of Historical Building  
Typologies. BUILDINGS. 2022;12(9).  
75. Ismaeel WSE. Drawing the operating mechanisms of green building rating systems. J Clean Prod.  
2019;213:599–609.  
76. Guo K, Li Q, Zhang L, Wu X. BIM-based green building evaluation and optimization: A case study. J  
Clean Prod. 2021;320:128824.  
77. Veselka J, Nehasilová M, Dvořáková K, Ryklová P, Volf M, Růžička J, et al. Recommendations for  
Developing a BIM for the Purpose of LCA in Green Building Certifications. Sustainability.  
2020;12(15):6151.  
78. Uddin MN, Wei HH, Chi HL, Ni M, Elumalai P. Building information modeling (BIM) incorporated green  
building analysis: An application of local construction materials and sustainable practice in the built  
environment. Journal of building pathology and rehabilitation. 2021;6:1–25.  
79. Behún M, Behúnová A. Advanced Innovation Technology of BIM in a Circular Economy. Applied  
Sciences. 2023;13(13):7989.  
80. Takyi-Annan GE, Hong Z. Assessing the impact of overcoming BIM implementation barriers on BIM  
Usage Frequency and circular economy in the Project lifecycle using Partial Least Squares Structural  
Equation Modelling (PLS-SEM) analysis. Energy Build. 2023;113329.  
81. Liu Z, Wu T, Wang F, Osmani M, Demian P. Blockchain Enhanced Construction Waste Information  
Management: A Conceptual Framework. Sustainability (Switzerland). 2022 Oct 1;14(19).  
82. Altaf M, Alaloul WS, Musarat MA, Bukhari H, Saad S, Ammad S. BIM implication of life cycle cost  
analysis in construction project: a systematic review. In: 2020 Second International Sustainability and  
Resilience Conference: Technology and Innovation in Building Designs (51154). IEEE; 2020. p. 1–7.  
83. Sivashanmugam S, Rodriguez S, Rahimian FP, Elghaish F, Dawood N. Enhancing information standards  
for automated construction waste quantification and classification. Autom Constr. 2023;152:104898.  
84. Ismail ER, El-Mahdy GM, Ibrahim AH, Daoud AO. Towards automated construction for safe disposal of  
materials waste in the Egyptian construction industry. In: E3S Web of Conferences. EDP Sciences; 2022.  
p. 02010.  
85. Basta A, Serror MH, Marzouk M. A BIM-based framework for quantitative assessment of steel structure  
deconstructability. Autom Constr. 2020;111:103064.  
86. Sanchez B, Rausch C, Haas C, Hartmann T. A framework for BIM-based disassembly models to support  
reuse of building components. Resour Conserv Recycl. 2021;175:105825.  
www.ijltemas.in  
Page 1332  
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
87. Ismaeel WSE, Kassim N. An environmental management plan for construction waste management. Ain  
Shams Engineering Journal. 2023;102244.  
88. Aftab U, Jaleel F, Aslam M, et al. Building Information Modeling (BIM) Application in Construction  
Waste Quantification—A Review. Engineering Proceedings 2024; 75: 8.  
89. Eze EC, Sofolahan O, Uzoma CN, et al. Impediments to building information modelling-enabled  
construction waste management in Nigeria. Built Environment Project and Asset Management.  
90. Akbari S, Sheikhkhoshkar M, Rahimian FP, et al. Sustainability and building information modelling:  
Integration, research gaps, and future directions. Autom Constr 2024; 163: 105420.  
91. Rayhan DSA, Bhuiyan IU. Review of construction and demolition waste management tools and  
frameworks with the classification, causes, and impacts of the waste. Waste Dispos Sustain Energy 2024;  
6: 95–121.  
92. Viswalekshmi BR, Bendi D. A comprehensive model for quantifying construction waste in high-rise  
buildings in India. Waste Management & Research 2024; 42: 111–125.  
93. Han D, Recycling AR-, 2024 undefined. Improving the Decision-Making for Sustainable Demolition Waste  
Management by Combining a Building Information Modelling-Based Life Cycle. mdpi.com,  
https://www.mdpi.com/2313-4321/9/4/70 (accessed 29 September 2024).  
94. Mcneil-Ayuk N, Engineering AJ-OJ of C, 2024 undefined. Building Information Modeling (BIM) and  
Circular Economy (CE) Model for the Management of Construction and Deconstruction Waste Based on  
Construction …. scirp.org, https://www.scirp.org/journal/paperinformation?paperid=134036 (accessed 29  
September 2024).  
95. Zubair M, Ali M, Khan M, et al. BIM-and GIS-Based Life-Cycle-Assessment Framework for Enhancing  
Eco Efficiency and Sustainability in the Construction Sector. mdpi.com. Epub ahead of print 2024. DOI:  
10.3390/su16072980.  
96. Andriyani N, Adi TJW, Suprobo P, et al. The role of Building Information Modelling (BIM) in waste  
management deconstruction plan via 3D reconstruction model. In: AIP Conference Proceedings. AIP  
Publishing, 2024.  
97. Schamne AN, Nagalli A, Soeiro AAV, Poças Martins JP da S. BIM in construction waste management: A  
conceptual model based on the industry foundation classes standard. Autom Constr. 2024 Mar.  
www.ijltemas.in  
Page 1333