The Role of BIM in Managing Risks in Sustainability of Bridge Projects: A Systematic Review with Meta-Analysis

Abstract

With the significant and rapid growth observed in bridge projects worldwide, the associated environmental, economic, and social concerns are on the rise. A systematic review of bridge sustainability with meta-analysis according to the PRISMA guidelines was performed, aiming to improve understanding of the importance of using building information modeling (BIM) in bridge projects by investigating the role of proper implementation of this technology to avoid and mitigate risks and improve sustainability. The relevant international literature was collected and scrutinized. The findings demonstrated that the accurate implementation of BIM significantly enhances the efficient management of risks in bridge projects. Consequently, this has a positive effect on improving the three essential (environmental, economic, and social) aspects of sustainability. The impact mentioned is especially apparent in enhancing the management of information throughout the entire lifespan of a bridge. This, in turn, facilitates precise decision-making during the design phase, aligns with assessments of environmental impact, enables real-time monitoring during execution, effectively manages the maintenance of the structure, facilitates efficient allocation and utilization of resources, and improves design practices by providing designers with accurate information. Delving into the nuances of this review has shed light on the transformative potential of BIM in shaping sustainable bridge projects, laying the groundwork for future advancements in this critical field.

1. Introduction

Nowadays, bridges are critical for transportation infrastructure networks in countries worldwide, serving as essential conduits for the movement of passengers and goods over obstacles without interrupting roadways. Their development has surged in recent years due to significant economic growth and urbanization [1,2,3,4,5,6]. However, bridges, despite their undeniable utility, pose environmental, economic, and societal challenges. They contribute significantly to the emission of greenhouse gases (GHGs) and exhibit diverse life scenarios and complex characteristics. Over their extended lifetimes, they consume substantial materials and energy, often exacerbated by reworks during the construction due to design phase errors and other factors [7,8,9,10,11]. Furthermore, the imminent need for significant bridge rehabilitation, reconstruction, and new construction, coupled with evolving infrastructure demands and the preservation of aging structures, presents an imperative to understand and mitigate potential risks associated with these projects [9,12].

To address these challenges, it is crucial to study potential risks in bridge projects comprehensively and to employ effective tools and technologies for their proper management and mitigation. Building information modeling (BIM) has emerged as a pivotal technology garnering attention from corporations and organizations due to its high number of benefits for project stakeholders, including cost reduction, enhanced productivity, and reduced greenhouse gas emissions [8,13,14]. BIM, as defined by Autodesk, represents a holistic process for creating and managing information related to building assets. It integrates multidisciplinary data to provide a digital representation of an asset throughout its lifecycle, from planning and design to construction and operation [15]. Although BIM is relatively new to the bridge construction industry, it possesses the potential to significantly elevate design quality by improving drawing accuracy, collaboration, and constructability through 3D models that precisely represent design outcomes [16,17,18]. Scholars have conducted comprehensive inquiries into many aspects of building information modeling (BIM) applications, intending to transform the field of bridge construction. This all-encompassing strategy includes a wide range of crucial components, each contributing to the overall improvement of bridge project management. Researchers have examined the complexities of material quality assurance, aiming to ensure that BIM not only enhances design and construction processes but also ensures the use of high-quality materials. Furthermore, the inquiry encompasses the interoperability of lifecycle processes, with BIM playing a vital role in facilitating smooth collaboration and data interchange over the full lifespan of the bridge. The integration of BIM with bridge management systems (BMS) is a key focus, highlighting how it increases the efficiency and effectiveness of bridge management procedures. Time and cost management are essential aspects of these academic investigations, acknowledging the potential of BIM to reduce project delays and cost overruns while ensuring efficient resource allocation. The simultaneous focus on design and construction efficiency highlights the versatility of BIM in improving the entire project delivery process. Ensuring precision in asset management is of the highest priority, and BIM provides strong solutions for maintaining an accurate inventory and assessing the health of bridge assets. Researchers utilize BIM technology to conduct thorough studies and monitoring of bridges, ensuring their structural integrity and safety, which is an important aspect of structural evaluation. One important aspect is the incorporation of building information modeling (BIM) with geographic information systems (GIS) to improve the effectiveness of building management systems (BMS). This combination promotes a comprehensive approach by integrating geographical data, geographic mapping, and information management, thus enhancing the effectiveness and knowledge of bridge management strategies [2,3,14,16,19,20,21,22,23,24,25,26,27,28,29]. Moreover, some studies have investigated the application of building information modeling (BIM) in the field of risk management for bridge construction. These studies have a specific focus on the management of risk information and its integration with the building information modeling (BIM) model. The purpose of this integration is to improve the effectiveness of recognizing and analyzing hazards in bridge construction [30,31]. Despite these efforts, the full extent to which BIM can enhance bridge construction and mitigate associated risks to help in achieving a higher level of sustainability is not yet understood. Thus, further research is imperative to establish a comprehensive understanding of this technology and its potential contributions to sustainable industry development and risk reduction in bridge projects.

Given the significance of bridge projects and the scantiness of research on BIM’s role in mitigating bridge project risks across various dimensions, this paper aims to evaluate BIM’s effectiveness as a risk management tool in sustainable bridge construction projects. Specifically, it seeks to synthesize existing information and data to address the following crucial question:

• How does building information modeling (BIM) contribute to better risk management outcomes in sustainable bridge projects, specifically in avoiding potential risks and achieving greater sustainability?

By answering this question, it is feasible to gain valuable insights into the subject of sustainable bridge construction and risk management through thorough investigation and evaluation, ultimately enhancing the understanding of BIM’s role in promoting sustainability and resilience for one of the main components of infrastructure networks, which can be applied to the other parts of these networks.

2. Methodology

To answer the study’s major objectives and fulfill the main goal of evaluating the effectiveness of employing building information modeling (BIM) as a risk management tool for sustainable bridge projects, the following protocol shown in Table 1 was used.

Table 1. Research protocol.

Main Section	Subsection
2.1 Study tools:	2.1.1 Systematic Review and Meta-Analysis:
	2.1.2 Meta-Analysis in Systematic Review
	2.1.3 Adherence to PRISMA Guidelines:
2.2 Databases search strategies	2.2.1 Selection of Databases:
	2.2.2 Search strings and keywords
2.3 Inclusion and Exclusion Criteria	------------
2.4 Eligibility Criteria	------------
2.5 Risk of Bias	------------
2.6 Data Extraction and Evaluation of Study Quality	------------
2.7 Protocol registration:	------------

2.1. Study Tools

2.1.1. Systematic Review and Meta-Analysis

The research presented in this paper adopts a systematic review as its foundational approach to comprehensively examine prior studies related to the topic and assess the quality of the available evidence. A systematic review is a robust method for gathering scientific evidence transparently, avoiding redundancy in research efforts, and ensuring unbiased selection and honest appraisal of research quality. It stands as the most reliable source of evidence for addressing research questions [13,32,33,34,35,36,37,38,39]. To effectively address the research question, this study employs a systematic review with meta-analysis.

2.1.2. Meta-Analysis in Systematic Review

Within the systematic review, meta-analysis is employed as a research procedure and quantitative technique that employs statistical tools to compute an overall or “absolute” effect by synthesizing findings from individual, independent studies. This approach utilizes specific measurements to quantify the strength of correlations between variables under investigation. In recent years, meta-analysis has found applications in diverse fields such as biomedicine, healthcare, government initiatives, business operations, and academic disciplines. Its utility extends to evaluating clearly defined subjects, making it relevant to engineering, environmental studies, economics, and more [32,34,35,37,38,40,41,42,43].

2.1.3. Adherence to PRISMA Guidelines

This review and analysis strictly adhere to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, which were developed by a committee of experts to enhance the transparency, quality, completeness, and frequency of documented systematic reviews and meta-analyses. PRISMA provides a comprehensive framework for empirically supported publishing, involving keyword searches to identify relevant scientific literature in extensive academic databases, the application of well-defined inclusion and exclusion criteria, and a meticulous review of relevant materials to analyze research data. The PRISMA 2020 version, comprising a 27-item checklist (see Supplementary Materials) and a flow diagram, encompasses critical components of a systematic review report, spanning the introduction, methods, results, and discussion sections. While PRISMA was primarily designed to enhance reporting in reviews assessing the efficacy of interventions, it is versatile and applicable to systematic reviews with diverse objectives, including those in the built environment and BIM-related studies [13,39,44].

2.2. Databases Search Strategies

2.2.1. Selection of Databases

Although there are numerous specialized databases for scientific publications and research available today, there are still significant gaps in their coverage, particularly for recent content. Given the study’s specific focus and objectives, as well as the scarcity of papers and research on the subject, it was determined that it would be beneficial to include a variety of databases spanning various disciplines associated with sustainable bridge projects, building information modeling (BIM), and risk management. Upon investigating several databases, it became clear that the best ones start with the first main source, SCOPUS, which is the largest abstract and citation database of peer-reviewed literature and high-quality web sources in the world. It offers innovative features for tracking, analyzing, and visualizing research. It also provides a variety of search strategies, including Boolean search, phrase matching, wildcards, and truncation, to assist scientists in quickly and accurately retrieving the information they seek. Notably, SCOPUS has a larger selection of indexed articles than PubMed, Web of Science (WOS), and Google Scholar [13,45,46,47]. Moreover, ScienceDirect, which is Elsevier’s comprehensive full-text platform, offers users access to an extensive collection of journals. It serves as an exceptional bibliographic and comprehensive full-text electronic repository that primarily focuses on science, technology, and medicine. It enables a thorough examination of the limitations and capabilities it provides [48,49]. Additionally, IEEE Xplore, which contains abstract and citation information for all IEEE and IEE journals, transactions, magazines, and conference proceedings published since 1988, proves valuable. While its primary concentration is on electrical engineering, electronics, and computer science, it also includes papers and research on infrastructure engineering, namely the use of BIM in bridge projects [50,51].

2.2.2. Search Strings and Keywords

To navigate through the chosen databases, the search strings listed in Table 2 were employed. These search strings were selected in accordance with the research questions.

Table 2. The systematic review process’s search string.

Data Sources	Search Strings
The first source of data: Scopus	Article Title, Abstract and Keywords Adaption, citation (“BIM” AND “Bridge” OR “Sustainability”) (“BIM” OR “Building Information Modeling”) AND (“Risk” OR “Risk Management” OR “Risk Assessment” OR “Risk Mitigation” OR “Risk Analysis”) AND (“Sustainable Bridge Projects” OR “Bridge Project” OR “Bridge Design” OR “Bridge Maintenance”). (“BIM” OR “Building Information Modeling”) AND (“Risk Management” OR “Risk Assessment” OR “Risk Mitigation” OR “Risk Analysis”) AND (“Sustainable Bridge” OR “Sustainable Infrastructure” OR “Sustainability in Bridge Project”).
The second source of data: ScienceDirect	Article Title, Abstract and Keywords Adaption, citation ((“BIM” AND “Bridge”) OR (“BIM” AND “Sustainable bridge”)). (“BIM” OR “Building Information Modeling”) AND (“Risk” OR “Risk Management” OR “Risk Assessment” OR “Risk Mitigation”) AND (“Sustainable Bridge Projects” OR “Bridge Project”) (“BIM” OR “Building Information Modeling”) AND (“Risk Management” OR “Risk Assessment” OR “Risk Mitigation” OR “Risk Analysis”) AND (“Sustainable Bridge” OR “Sustainable Infrastructure”)
The third source of data: IEEE Xplore	(“BIM” OR “Building Information Modeling”) AND (“Risk” OR “Risk Management” OR “Risk Assessment” OR “Risk Mitigation” OR “Risk Analysis”) AND (“Sustainable Bridge Projects” OR “Bridge Project” OR “Bridge Design” OR “Bridge Maintenance”). (“BIM” OR “Building Information Modeling”) AND (“Risk Management” OR “Risk Assessment” OR “Risk Mitigation” OR “Risk Analysis”) AND (“Sustainable Bridge” OR “Sustainable Infrastructure” OR “Sustainability in Bridge Project”).

In addition, a secondary search was conducted using the keywords and phrases given in Table 3 to ensure that as many articles relating to the issue as possible were found to cover all the required concepts in this research.

Table 3. Search keywords and phrases.

Process	Field
BIM	Sustainable Bridge Project
Building Information Modeling	Environmental Sustainability
BIM Technology	Economic Sustainability
Digital Twin	Social Sustainability
Risk Mitigation Strategies	Environmental Risks
Risk Analysis	Economic Risks
Bridge Design	Social Risks
Bridge Rehabilitation	Bridge Characteristics
Bridge Maintenance	Green Infrastructure

Table 4 shows the total number of papers from all sources after applying the research strings with the keywords and phrases and based on the foregoing.

Table 4. The number of papers from all sources.

Database	Number of Publications	Total Number
Scopus	171	248
Science direct	66
IEEE Xplore	11

2.3. Inclusion and Exclusion Criteria

To identify the most pertinent publications related to the research topic, a set of inclusion and exclusion criteria aligned with the PRISMA 2020 guidelines was established. These criteria are detailed in Table 5. The first criterion, “Relevance to the Topic,” requires that studies address the use of building information modeling (BIM) as a risk management tool in sustainable bridge projects. Considering the lack of research in this field, particularly in the first two databases, this criterion was expanded to incorporate the three points listed below: (1) the use of BIM in risk management for sustainable bridge projects; (2) the use of BIM for sustainable bridge projects; and (3) risk management approaches for sustainable bridge projects. The second criterion addresses “Publication Type.” In accordance with this criterion, selected papers must be peer-reviewed journal articles, while all other forms of publication are to be excluded. Furthermore, the selected articles are required to be in the English language to ensure accuracy and prevent information transmission and translation errors. Additionally, the publication dates of these articles should fall within the timeframe of 2010 to 2024.

Table 5. The inclusion and exclusion criteria.

Criteria	Inclusion	Exclusion
Relevance to the Topic	Using BIM to manage risks in bridge projects. The use of BIM in sustainable bridge projects The risk management approach in sustainable bridge projects	--------
Publication Type	Peer-reviewed journal articles	Non-peer-reviewed sources, conference papers, review papers, and academic reports
Language	English	Non-English
Time Frame	Between 2010 and 2024	Before 2010
Study Type	Both quantitative and qualitative research	--------
Geographical Scope	From any geographical region	--------
Dissertations and Theses	--------	Dissertations, theses, and unpublished works
Non-Accessibility	Accessible through the selected databases	--------
Open access	Published in open-access journals or open-access versions of articles within subscription-based journals	--------

2.4. Eligibility Criteria

After an Excel spreadsheet with 248 articles was imported into Mendeley, the purpose was to remove any duplicate entries. Following this, each study was evaluated to determine its relevance to the field of infrastructure engineering. As a result, 153 papers were retained. After the criteria for inclusion and exclusion were applied and eligibility screening was conducted, it was found that 78 articles did not meet the specified criteria, and another 49 articles were not relevant to the use of BIM in risk management for the purpose of achieving more sustainable bridge construction, as depicted in Figure 1. Ultimately, a total of 26 papers were considered suitable for inclusion in the analysis following a comprehensive evaluation of their full texts.

Figure 1. PRISMA 2020 flowchart: paper selection process.

2.5. Risk of Bias

To guarantee the suitability of the studies chosen for this review and to prevent any form of bias, the ROBINS-I (Risk of Bias in Non-randomized Studies—of Interventions) tool was employed. This tool is a rigorous quality assessment instrument specifically created for evaluating bias in non-randomized studies. The evaluation of bias in this study thoroughly assessed various sources in several areas, including confounding, selection bias, classification of interventions, deviations from intended interventions, missing data, measurement of outcomes, and selection of the reported result. The evaluation was conducted based on the steps presented in Table 6. Implementing ROBINS-I is considered an essential method for guaranteeing the accuracy and dependability of the results in the context of this study, which includes non-randomized studies [52].

Table 6. ROBINS-I to assess the studies’ bias.

ROBINS-I Sections	Adapted Question
Bias Due to Confounding	Is the study designed to explicitly address the role of building information modeling (BIM) in managing risks in sustainable bridge projects, considering potential confounding factors?
Selection Bias	Does the study focus on the avoidance of potential risks and achieving greater sustainability in bridge projects through BIM, while addressing selection bias in participant or case selection?
Bias in Classification of Interventions	Is the study design appropriate for addressing the research question about BIM’s role in risk management and sustainability in bridge projects, considering potential biases in classifying interventions?
Bias Due to Deviations from Intended Interventions	Does the study use rigorous and transparent methodologies for data collection and analysis, minimizing biases resulting from deviations from intended BIM interventions?
Missing Data Bias	Does the study provide clear details on the implementation of BIM in the context of risk management in sustainable bridge projects, minimizing potential bias from missing data?
Bias in Measurement of Outcomes	Is there information on the level of BIM integration and utilization in the study, considering potential biases in the measurement of outcomes related to risk management and sustainability?
Bias in Selection of the Reported Result	Does the study define and measure risk management outcomes related to BIM in bridge projects, while addressing biases in the selection and reporting of results?
Overall Risk of Bias	Is there clear identification and assessment of sustainability outcomes linked to BIM implementation in the study, accounting for potential biases across multiple domains?
Risk of Bias in Data Sources	Are the data sources reliable and credible, minimizing the risk of bias associated with the quality of data?
Risk of Bias in Measurement Tools	Does the study use valid measures and indicators for assessing BIM’s impact on risk management and sustainability in bridge projects, minimizing bias in measurement tools?
Risk of Bias in Sample Representativeness	Is the study sample representative of sustainable bridge projects utilizing BIM, addressing potential biases in the selection of participants or cases?
Risk of Bias in Statistical Methods	If applicable, does the study employ appropriate statistical methods, considering the complexity of the data and the research question and minimizing biases in statistical analysis?
Risk of Bias in Publication Quality	Are the study’s findings presented clearly, and is the methodology well-described, minimizing biases in publication quality?

2.6. Data Extraction and Evaluation of Study Quality

To analyze the remaining articles that are shown in Table 7, thematic analysis was used, which involves a systematic procedure to identify and analyze patterns or themes in a dataset. This methodology entails a methodical procedure that can be delineated into numerous pivotal stages. At first, researchers acquaint themselves with the data, developing a profound comprehension through multiple readings. Subsequently, they produce preliminary codes to discover and categorize significant characteristics within the dataset. Afterwards, these codes are categorized into prospective themes, which are broad patterns that encompass significant components of the content. The themes are subjected to meticulous examination and fine-tuning to guarantee their logical consistency and pertinence to the study query. After being formed, every theme is precisely delineated and given a name that encapsulates its fundamental nature. The last stage entails composing a coherent report, wherein the findings are presented in a narrative structure, substantiated by pertinent examples derived from the data. During this procedure, researchers demonstrate reflexivity by recognizing and dealing with possible biases. Thematic analysis provides researchers with the ability to modify the phases according to the distinct attributes of their study and data, hence offering flexibility [53,54,55]. According to this analysis, the main and sub-themes that connect to the role and importance of BIM in managing and reducing risks in bridge projects with the aim of achieving higher levels of sustainability are defined.

Table 7. The selected studies that satisfy the required criteria.

Authors	Date	Journal	Country
Zhang et al. [56]	2023	High-speed Railway	China
Mohammadi et al. [57]	2023	Computers in Industry	The Netherlands
Celik et al. [58]	2023	Computers in Industry	The Netherlands
Salzano et al. [59]	2022	Materials Today: Proceedings	United Kingdom
Wang et al. [60]	2022	Automation in Construction	The Netherlands
Ariza-López et al. [61]	2022	Automation in Construction	The Netherlands
Scianna et al. [62]	2022	ISPRS International Journal of Geo-Information	Switzerland
Kaewunruen et al. [63]	2023	Sensors	Switzerland
Celik et al. [64]	2022	Computers in Industry	The Netherlands
Jiang et al. [65]	2022	Automation in Construction	The Netherlands
Sabah Jarallah & Mahjoob [66]	2022	Engineering, Technology and Applied Science Research (ETASR)	Greece
Ershadi et al. [67]	2022	International Journal of Information Systems and Project Management	Portugal
Previtali et al. [68]	2022	Applied Geomatics	Germany
Hamdan et al. [69]	2020	Automation in Construction	The Netherlands
Ciccone et al. [27]	2021	Sustainability	Switzerland
Bono et al. [70]	2021	Remote Sensing	Switzerland
Van Eldik et al. [71]	2020	Automation in Construction	The Netherlands
Kaewunruen et al. [72]	2021	Sustainability	Switzerland
Bui [73]	2021	The Electronic Journal of Information Systems in Developing Countries	Germany
Lu & Brilakis [74]	2019	Automation in Construction	The Netherlands
Kaewunruen et al. [8]	2020	Sustainability	Switzerland
Liu et al. [75]	2018	Advances in Civil Engineering	United States
Kang et al. [76]	2016	Automation in Construction	The Netherlands
Marzouk & Hisham [21]	2014	KSCE Journal of Civil Engineering	Germany
Akula et al. [77]	2013	Automation in Construction	The Netherlands
Moon et al. [78]	2013	Advanced Engineering Informatics	United Kingdom

2.7. Protocol Registration

To ensure transparency and avoid redundancy, the protocol for this systematic review was registered on PROSPERO (International Prospective Register of Systematic Reviews) after the research procedure was completed. Although it is preferable to register at an early stage, we assured the thorough documentation of our study by completing the PROSPERO registration after the research was conducted.

3. Results and Discussion

While conventional meta-analyses use statistical techniques for numerical data, there are situations where a qualitative synthesis is suitable for analyzing narrative or qualitative findings. This methodology enables a thorough comprehension of the qualitative data from many investigations, even when there are no numerical findings available. The qualitative analysis of the papers that satisfied the criteria of this systematic review produced the findings reported in Table 7. The analysis identified three primary themes: environmental risk management, economic risk management, and social risk management. The selection of the three main themes was predicated on the overarching objective of enhancing sustainability in bridge projects. Hence, it was imperative to select the three main pillars of sustainability, namely environment, economy, and society. Given the emphasis on the risk management process in this specific improvement, the study focuses on the role of building information modeling in enhancing sustainability by examining its impact on environmental, economic, and social risk management. Each main theme is associated with a set of sub-themes (six sub-themes for environmental risks, ten for economic risks, and six for social risks). The sub-themes connected with each main theme were chosen through analysis of the research papers contained in this review. There are common sub-themes that are shared across the themes, which are important for studying the role of BIM in managing and mitigating risks in bridge projects to enhance sustainability, as is shown in Figure 2.

Figure 2. The role of BIM in improving bridge sustainability through risk management.

Table 8 indicates that eleven articles employ the qualitative method, eleven articles utilize the mixed method, and only four articles employ the quantitative method. Researchers choose qualitative methodologies to explore unexplored areas, gain contextual understanding, examine subjective perspectives, prioritize flexibility, and address small sample sizes. Qualitative methodologies are particularly efficient in providing a thorough and deep comprehension of subtle and complex phenomena. On the other hand, mixed-methods research is preferred for attaining comprehensive understanding, validation, and confirmation of findings. It is highly beneficial for addressing complex research questions, employing systematic analysis, and generating findings that have practical implications. Researchers may opt to utilize mixed methods to overcome limitations and capitalize on the benefits of both qualitative and quantitative methodologies.

Table 8. Summary of results.

Authors	Research Design			The Role of BIM in Managing Risks to Achieve More Sustainable Bridge Projects
	QL	QN	MM	Environmental Risk Management	Economic Risk Management	Social Risk Management
Zhang et al., 2023 [56]		√		√	√	√
Mohammadi et al., 2023 [57]			√	√	√	√
Celik et al., 2023 [58]	√			√	√
Salzano et al., 2022 [59]		√		√	√	√
Wang et al., 2022 [60]			√	√	√	√
Ariza-López et al., 2022 [61]			√		√
Scianna et al., 2022 [62]			√	√	√	√
Kaewunruen et al., 2023 [63]	√			√	√	√
Celik et al., 2022 [64]			√		√
Jiang et al., 2022 [65]			√	√	√	√
Sabah Jarallah & Mahjoob, 2022 [66]		√		√	√
Ershadi et al., 2022 [67]	√			√	√	√
Previtali et al., 2022 [68]	√			√	√	√
Hamdan et al., 2021 [69]			√		√	√
Ciccone et al., 2021 [27]	√			√	√	√
Bono et al., 2021 [70]			√	√	√	√
Van Eldik et al., 2020 [71]			√	√	√
Kaewunruen et al., 2021 [72]	√			√	√	√
Bui, 2020 [73]	√				√
Lu & Brilakis, 2019 [74]		√		√	√	√
Kaewunruen et al., 2020 [8]	√			√	√
Liu et al., 2018 [75]	√			√	√	√
Kang et al., 2016 [76]			√		√
Marzouk & Hisham, 2014 [21]	√			√	√	√
Akula et al., 2013 [77]	√			√	√	√
Moon et al., 2013 [78]			√		√	√
Total	11	4	11	20	26	18

Note: QL = Qualitative, QN = Quantitative, MM = Mixed Methods.

The Role of BIM in Managing Risks to Achieve More Sustainable Bridge Projects

• Environmental risk management using BIM

There are a total of 20 studies specifically focused on investigating the application of BIM to effectively manage environmental risks. Table 9 illustrates the categorization of environmental themes that will be improved through the utilization of BIM in a bridge project.

Table 9. Environmental themes.

Environmental Themes	Related Studies
Enhancement of information management and document automation processes through the bridge project’s lifespan	Zhang et al. (2023) [9], Wang et al. (2022) [60], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Jiang et al. (2022) [65], Previtali et al. (2022) [68], Ershadi et al.(2022) [67], Marzouk & Hisham(2014) [21], Liu et al. (2018) [75]
Improvement of structural maintenance process to optimize efficiency, quality, and speed	Salzano et al. (2022) [59], Wang et al. (2022) [60], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Scianna et al. (2022) [62], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Bono et al. (2021) [70], Jiang et al. (2022) [65], Previtali et al. (2022) [68], Liu et al. (2018) [75]
Efficient allocation and utilization of resources	Zhang et al. (2023) [9], Ariza-López et al. (2022) [61], Lu & Brilakis (2019) [74], Akula et al. (2013) [77], Scianna et al. (2022) [62], Kaewunruen et al. (2021) [72], Celik et al. (2023) [58], Sabah Jarallah & Mahjoob (2022) [66]
Improving design practices through providing designers with accurate information	Van Eldik et al. (2020) [71], Moon et al. (2013) [78], Scianna et al. (2022) [62], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Celik et al. (2022) [58], Sabah Jarallah & Mahjoob (2022 [66]), Ershadi et al. (2022) [67], Liu et al. (2018) [75]
Selecting the most environmentally friendly materials suitable for the climate and surrounding ecosystem	Wang et al. (2022) [60], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2021) [72], Kaewunruen et al. (2023) [63]
Evaluating carbon footprint throughout the duration of the project and mitigating the release of greenhouse emissions	Kaewunruen et al. (2021) [72], Kaewunruen et al. (2020) [8]

Regarding environmental risk management, only four studies addressed the theme of selecting the most environmentally friendly materials that are suitable for the climate and surrounding ecosystem and two studies for examining the carbon footprint throughout the duration of the project and mitigating the release of greenhouse emissions, despite its major importance. This is despite the fact that bridge projects, as a crucial component of transportation infrastructure networks, significantly contribute to the production of greenhouse gases over their entire life cycle, including the manufacturing of materials, execution, and regular maintenance.

• Economic risk management using BIM

All the studies primarily examined—even in an indirect manner—the application of building information modeling (BIM) to manage economic risks. Table 10 categorizes the economic themes that BIM will improve in the bridge project.

Table 10. Economic risk management themes.

Economic Themes	Related Studies
Enhancement of information management and document automation processes through the bridge project’s lifespan	Zhang et al. (2023) [9], Wang et al. (2022) [60], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Jiang et al. (2022) [65], Previtali et al. (2022) [68], Ershadi et al. (2022) [67], Marzouk & Hisham (2014) [21], Liu et al. (2018) [75]
Improvement of structural maintenance process to optimize efficiency, quality, and speed	Salzano et al. (2022) [59], Wang et al. (2022) [60], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Scianna et al. (2022) [62], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Bono et al. (2021) [70], Jiang et al. (2022) [65], Previtali et al. (2022) [68], Liu et al. (2018) [75]
Efficient allocation and utilization of resources	Zhang et al. (2023) [9], Ariza-López et al. (2022) [61], Moon et al. (2013) [78], Lu & Brilakis (2019) [74], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Scianna et al. (2022) [62], Kaewunruen et al. (2021) [72], Celik et al. (2023 [58]), Sabah Jarallah & Mahjoob (2022) [66], Liu et al. (2018) [75]
Improving design practices through providing designers with accurate information	Van Eldik et al. (2020) [71], Moon et al. (2013) [78], Scianna et al. (2022) [62], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63] Celik et al. (2022) [64], Sabah Jarallah & Mahjoob (2022) [66], Ershadi et al. (2022) [67], Liu et al. (2018) [75]
Effective communication among stakeholders in the project and the capacity to exchange information with dependability and clarity	Zhang et al. (2023) [9], Lu & Brilakis (2019) [74], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2021) [72], Kaewunruen et al. (2023) [63], Celik et al. (2022) [64], Celik et al. (2023) [58], Previtali et al. (2022) [68], Bui (2020) [73], Liu et al. (2018) [75]
Precise planning of costs and schedules for the project to prevent any claims and delays and achieve the required level of quality	Zhang et al. (2023) [9], Ariza-López et al. (2022) [61], Kang et al. (2016) [76], Moon et al. (2013) [78], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Scianna et al. (2022) [62], Kaewunruen et al. (2021) [72], Kaewunruen et al. (2020) [8], Celik et al. (2022) [64], Sabah Jarallah & Mahjoob (2022) [66], Previtali et al. (2022) [68], Ershadi et al. (2022 [67]), Bui (2020) [73], Marzouk & Hisham (2014) [21], Liu et al. (2018) [75]
Enabling real-time tracking and monitoring to guarantee the precision of the execution and handle any recently arising modifications	Wang et al. (2022) [60], Kang et al. (2016) [76], Akula et al. (2013) [77], Hamdan et al. (2021) [69], Scianna et al. (2022) [62], Kaewunruen et al. (2020) [8], Celik et al. (2022) [64], Celik et al. (2023) [58], Previtali et al. (2022) [68]
Increasing the possibility of avoiding clashes and reworks during different phases of the bridge’s lifespan	Kang et al. (2016) [76], Lu & Brilakis (2019) [74], Hamdan et al. (2021) [69], Jiang et al. (2022) [65], Bui (2020) [73], Liu et al. (2018) [75]
Raising productivity and meticulous organization of the required work teams	Kaewunruen et al. (2020) [8], Celik et al. (2022) [64], Celik et al. (2023) [58], Bono et al. (2021) [70], Ershadi et al. (2022) [67], Marzouk & Hisham (2014) [21]
Optimizing the efficiency of the supply chain process and facilitating the selection of an appropriate supplier by providing accurate information	Sabah Jarallah & Mahjoob (2022) [66], Ershadi et al. (2022) [67]

Considering economic risk management, the primary emphasis was placed on planning costs and schedules for the project to prevent any claims and delays and to achieve the required level of quality through 18 comprehensive studies. This is of greatest significance for the bridge project, as cost, time, and quality are the primary goals that must be prioritized to foster a more sustainable outcome. However, there was a lack of emphasis on optimizing the efficiency of the supply chain process and facilitating the selection of an appropriate supplier by providing accurate information in two studies, which is a critical aspect of these projects and has adverse effects on various processes within the project. Any mistakes or delays in the supply of materials will have a negative impact on the construction process, leading to disruptions and potential claims.

• Social risk management using BIM

There are a total of 18 articles that expressly discuss social risk management and its reduction through the implementation of BIM in bridge projects. Table 11 presents the classification of the social themes that BIM will improve in the bridge project.

Table 11. Social risk management themes.

Social Themes	Related Studies
Enhancement of information management and document automation processes through the bridge project’s lifespan	Zhang et al. (2023) [9], Wang et al. (2022) [60], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Jiang et al. (2022) [65], Previtali et al. (2022) [68], Ershadi et al. (2022) [67], Marzouk & Hisham (2014) [21], Liu et al. (2018) [75]
Improvement of structural maintenance process to optimize efficiency, quality, and speed	Salzano et al. (2022) [59], Wang et al. (2022) [60], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27], Scianna et al. (2022) [62], Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Bono et al. (2021) [70], Jiang et al. (2022) [65], Previtali et al. (2022) [68], Liu et al. (2018) [75]
Developing the process for evaluating safety in all of its different procedures	Zhang et al. (2023) [9], Moon et al. (2013) [78], Lu & Brilakis (2019) [74], Hamdan et al. (2021) [69], Ciccone et al. (2021) [27], Scianna et al. (2022) [62], Kaewunruen et al. (2020) [8]
Improving community satisfaction with the work site	Lu & Brilakis (2019) [74], Akula et al. (2013) [77], Hamdan et al. (2021) [69], Ciccone et al. (2021) [27], Scianna et al. (2022) [62], Ershadi et al. (2022) [67]
Community Engagement	Zhang et al. (2023) [9], Lu & Brilakis (2019) [74], Mohammadi et al. (2023) [57], Akula et al. (2013) [77], Ciccone et al. (2021) [27]
Meticulous organization of the required work teams	Kaewunruen et al. (2020) [8], Kaewunruen et al. (2023) [63], Bono et al. (2021) [70], Ershadi et al. (2022) [67], Marzouk & Hisham (2014) [21]

Within the realm of social risk management, significant emphasis was placed on the enhancement of information management and document automation processes through the bridge project lifespan and the improvement of the structural maintenance process to optimize efficiency, quality, and speed, with an average of 13 studies conducted for each improvement. The issue of least interest was community engagement and meticulous organization of the required work teams, each consisting of five studies.

By reviewing the information presented in Table 9, Table 10 and Table 11, certain sub-themes are shared among the three main themes, and most of the studies focused on these themes. One of these sub-themes is the enhancement of information management and document automation processes, which significantly influences the entire life cycle of the bridge project, from the initial design phase to the ongoing maintenance phase. Furthermore, there is a focus on the improvement of the structural maintenance process to optimize efficiency, quality, and speed. This is achieved by establishing control and monitoring strategies to determine the maintenance protocols necessary for maintaining an acceptable level of safety and ensuring appropriate functional performance. These strategies also aim to minimize maintenance operations, thereby managing resource consumption and saving time. Consequently, this helps to reduce the duration of work area closures and minimize their impact on the surrounding community.

• BIM tools utilized in previous studies

Multiple software tools are commonly employed for construction and infrastructure projects within the BIM environment. Upon analyzation of the study papers for this review, it became evident that most of them heavily relied on Revit 2021 software to acquire a 3D BIM model that aligned with the specific needs of the work at hand. Revit is a comprehensive BIM software that facilitates 3D modeling for architecture, engineering, and construction. It enables collaborative design, automates documentation, and supports the entire building lifecycle. With parametric modeling, Revit enhances efficiency in project coordination and design iterations. Furthermore, many studies frequently used Revit in tandem with Dynamo, an open-source visual programming extension designed for Autodesk Revit. Only two studies, conducted by Bui (2019) [73] and Marzok et al. (2014) [21], specifically examined the utilization of Tekla Structure, a specialized BIM software designed for structural engineering. This software allows for intricate 3D modeling with support for various materials. It simplifies the process of providing detailed information, makes cooperation easier, and seamlessly interacts with analysis tools, thereby making construction management more efficient. By providing an open API, it enables customization to fulfill individual project needs. Navisworks was employed in the research conducted by Jiang (2022) [65] and Kaewunruen et al. (2021) [72]. It is a robust tool for project review and collaboration within the BIM framework, facilitating the consolidation of 3D models, clash detection, and the simulation of construction procedures. This program promotes collaboration and assists in identifying and resolving potential problems throughout the project.

4. Limitations

Bridge projects, characterized by their complex design and construction intricacies, pose significant challenges to the traditional application of building information modeling (BIM). The continuous requirement for developments in BIM technology customized specifically for bridge construction highlights the inherent complexity. An important constraint, as determined in this analysis of the relevant literature, is the requirement to incorporate BIM with diverse tools such as blockchain, enterprise resource planning (ERP), life cycle assessment (LCA), and the Internet of Things (IoT). Although this integration is a determined and calculated solution to address certain difficulties, it also brings attention to a possible disadvantage. The reliance on several technologies can introduce intricacies and increase the amount of time and effort required for project stakeholders to become proficient. Although BIM’s ability to link with many tools and technologies is smooth, this interoperability can also present hurdles, failing to achieve the necessary level of data consistency and causing potential coordination problems among stakeholders. Looking ahead, while upcoming BIM breakthroughs have the potential to enhance operational efficiency, it is crucial to recognize that certain projects may be constrained by the need to keep up with these advancements. The complex intricacy of bridge construction necessitates a meticulous balance between embracing novel technologies and tackling the accompanying difficulties. The advancement of BIM raises concerns about its efficiency in bridge construction, highlighting the necessity for a flexible and sophisticated strategy.

5. Conclusions

Despite the significance of bridge projects, the full utilization of the potential offered by information modeling, which can significantly enhance these projects, has not been realized yet. The extensive exploration into the intersection of sustainable bridge projects and building information modeling (BIM) has revealed profound insights. It highlights the underutilization of information modeling in bridge projects and, more importantly, demonstrates its transformative potential. This systematic review and meta-analysis have uncovered that BIM plays a crucial role in risk management, going beyond procedural aspects and addressing the core issue of sustainability. The precise execution of BIM not only serves as a procedural improvement but also acts as a catalyst for beneficial environmental, economic, and social effects. This study reveals the detailed ways in which building information modeling (BIM) contributes to the whole lifespan of a bridge, including exact planning to prevent claims and delays as well as the careful selection of ecologically friendly materials. While strides made in information management, decision-making, and structural maintenance are accentuated by this work, themes requiring heightened attention in future research are also illuminated. Pivotal areas demanding deeper exploration, such as the selection of eco-friendly materials, carbon footprint examination, supply chain optimization, and supplier selection, are brought to the forefront due to their lasting impact on a bridge’s lifecycle. In essence, the transformative power of BIM in fostering sustainability is unveiled, urging the scholarly community to delve deeper into nuanced aspects for future advancements. This imperative extends beyond a mere recapitulation of processes; it underscores the importance of following up on the general steps outlined and thoroughly studying each process and sub-theme to achieve the greatest improvement.