Construction Engineering And Management Research Articles

Multi-Agent Decision-Making in Construction Engineering and Management: A Systematic Review

Construction engineering and management (CEM) involves multiple stakeholders, complex interest relationships, and conflicts. All stakeholders must comprehensively consider the interests relating to a project to make decisions. Appropriate multi-agent decision-making can effectively coordinate and integrate the needs or expectations of all stakeholders, which can reduce conflicts, improve the success probability of the project, maximize the overall returns on interest, and contribute to the project’s sustainability. Existing studies have begun to explore the associated theoretical framework and practical methods for multi-agent decision-making. However, early studies mainly focused on the conceptual theories of decision-making models and processes, such as stakeholder analysis, decision evaluation, and risk management. In recent years, increasing research has concerned the application of multi-agent decision-making in CEM. This paper is the first to use a comprehensive review approach to analyze multi-agent decision-making in CEM, providing an overall perspective. In this paper, 105 journal papers are identified and classified into four categories: (1) main concerns regarding multi-agent decision-making in CEM; (2) tools and methods of multi-agent decision-making in practice; (3) research tools and methods of multi-agent decision-making in CEM; (4) critical points on how to solve multi-agent decision-making problems. The findings of this study offer references for future trends in four regards, namely (1) knowledge management, (2) decision resilience, (3) the fusion of many techniques, and (4) technologies for future research.

Construction Engineering and Management: Review of Research from Australia-Based Academics

Construction Engineering and Management (CEM) is a critically important discipline that provides a scientific and management-oriented perspective for building and construction projects. Owing to the contingent nature of this industry, CEM research is highly context-specific and is governed by socio-economic needs, environmental challenges, and industry-specific issues. Australia is home to several universities engaged in CEM-related research and training. In terms of the CEM research volume, Australia occupies fourth place, globally. Considering the importance of Australia-based CEM research, the aim of this study was to investigate how CEM research in Australia has developed temporally and across different institutions, how research collaborations in this area materialized, and which topics and research domains are typically being explored. Accordingly, this study conducted a systematic review of 4318 publications from 158 Australia-based CEM academics, primarily based in eight Australian universities. Based on Scientometric and critical review techniques, this study provides insights into research topics, research growth, publication volume, and collaboration in the CEM research discipline in Australia. Similar to global CEM research, Australia-based CEM research places a high emphasis on topics such as risk, sustainability, decision-making, cost, design, and BIM. However, unlike global research trends, Australia-based CEM research places a much higher emphasis on safety and stakeholder management. Australian institutions have high collaboration among themselves and with Chinese and Hong Kong-based institutions. Recommendations for research development in Australia are provided to facilitate a discussion on how Australian institutions can set the future agenda for CEM research.

Forecasting Future Research Trends in the Construction Engineering and Management Domain Using Machine Learning and Social Network Analysis

Construction Engineering and Management (CEM) is a broad domain with publications covering interrelated subdisciplines and considered a key source of knowledge sharing. Previous studies used scientometric methods to assess the current impact of CEM publications; however, there is a need to predict future citations of CEM publications to identify the expected high-impact trends in the future and guide new research efforts. To tackle this gap in the literature, the authors conducted a study using Machine Learning (ML) algorithms and Social Network Analysis (SNA) to predict CEM-related citation metrics. Using a dataset of 93,868 publications, the authors trained and tested two machine learning classification algorithms: Random Forest and XGBoost. Validation of the RF and XGBoost resulted in a balanced accuracy of 79.1% and 79.5%, respectively. Accordingly, XGBoost was selected. Testing of the XGBoost model revealed a balanced accuracy of 80.71%. Using SNA, it was found that while the top CEM subdisciplines in terms of the number of predicted impactful papers are “Project planning and design”, “Organizational issues”, and “Information technologies, robotics, and automation”; the lowest was “Legal and contractual issues”. This paper contributes to the body of knowledge by studying the citation level, strength, and interconnectivity between CEM subdisciplines as well as identifying areas more likely to result in highly cited publications.

Long-term Trends in Construction Engineering and Management Research in Korea

This bibliographic study presents a historical perspective on Korea's construction engineering and management (CEM) research and reports a 27-year analysis of papers written by Korean CEM researchers between 1993 and 2019. Frequency analysis of the collected papers was performed according to three main perspectives: the knowledge area, research topics, and methods. Knowledge area analysis shows that research fields have become more diversified and subdivided. Construction technology, cost management, and planning and schedule management have consistently maintained the top three positions for the past three decades. In addition, quality management, resource management, and risk management were also ranked high in the 2000s. In the 2010s, safety management, environmental management, quality management, and construction industry and business were ranked high. These changes reveal how Korean society's and industry's demands have changed over the years. Furthermore, the findings from keyword frequency analysis revealed that the focus of CEM research was mostly on cost and scheduling in the 1990s and on scheduling, risk, cost, and construction automation in the 2000s. The advent of Building Information Modeling (BIM) in the 2010s was an epochal change. This study found that the research methods frequently used by CEM researchers were simulation, optimization, regression analysis, computer vision and image processing, 3D modeling, case-based reasoning, genetic algorithm, case study, economic analysis, and artificial neural network.

Employing Technology to Enable Remote Research Charrettes as a Method for Engaging Industry and Uncovering Best Practices: A Novel Approach for a Post-COVID-19 World

Methods to collect data in construction engineering and management (CEM) research are evolving, informed by recent technological advancements. One such method is research charrettes that allow effective interactions and knowledge sharing between expert industry practitioners and academic researchers, all colocated in a single venue, enabling rich data collection and live communication. A pivot point in technological evolution occurred with the COVID-19 pandemic, forcing a global shift to remote work. Hence, planned in-person research charrettes had to shift to remote sessions, relying on virtual conferencing platforms and online data collection mechanisms. Technology-enabled charrettes have allowed the authors to collect significantly richer data sets and ensure a more diverse representation of participants, while saving tremendous amounts of time. With the continuing emergence of technological applications, the world might not go back to functioning fully in person. The authors believe remote research charrettes (RRCs) will still be used in a post-COVID-19 world because of their superior performance. This paper builds on a previous publication that described traditional research charrettes as a method to enhance CEM research a decade ago; it offers a significantly updated and improved RRC method based on the knowledge gained from transitioning a dozen in-person charrettes into RRCs. It also presents performance comparisons between RRCs and traditional charrettes by quantifying metrics indicating how RRCs are more time-efficient and cost-saving, harness more participants from more diverse locations, and enable the collection of richer data sets and four times more industry comments and expert feedback. This paper also provides guidance on the integration of technology with traditional research charrettes, hence contributing to the CEM body of knowledge.

Methodology for Extended Reality–Enabled Experimental Research in Construction Engineering and Management

Extended reality (XR) technologies are increasingly being used as a novel research instrument to facilitate scientific inquires in the construction engineering and management (CEM) domain. By allowing humans to interact with immersive environments in controlled and monitored experimental settings, XR technologies have opened new opportunities for researchers to conduct CEM research involving human participants or concerning human behavior. Yet, XR-enabled research, as an independent, rigorous methodology for the CEM domain, is still underexplored. This paper serves as an effort to build an organized knowledge base and workflow for using XR technologies in various CEM research areas and methodological contexts. The paper first investigates the status quo of XR-enabled CEM research, by identifying current research areas in the CEM domain where XR technologies are considered the preferred or recommended methodological solutions. A process model for XR-enabled research is then proposed, with actionable recommendations about how XR-enabled research should be planned, designed, implemented, analyzed, verified, and validated. This process model is demonstrated with two illustrative case studies. Last, the paper discusses the philosophical, methodological, and technological roots of the evolution of XR-enabled CEM research and describes our vision of more enabling, adoptable, and value-adding XR-enabled research in CEM in the near future.

Incorporating BIM into the upper-division curriculum of construction engineering and management

ABSTRACT This pedagogical study aimed to demonstrate an updated Building Information Modelling (BIM) educational activity in CEM (i.e., construction engineering and management) students’ final semester project. It investigated students’ perceptions of BIM and the project. Student feedback provided insights for linking education to practice, for example, what caused differences between manual estimates and BIM-generated quantity take-off. Four different project deliverable options demonstrated how educational theories could be embedded in BIM education. The novelty of this study lies in two aspects: firstly, this pedagogical research views the CEM education at the curriculum level by linking earlier years’ core CEM courses into the final project work; secondly, by designing four different options of BIM-related deliverables, subgroup analyses test how different factors, such as teamwork verse individual work, and BIM application level, could affect students’ learning outcomes. The current study also led to more future explorations in research-informed teaching in the CEM curriculum.

Comparing Qualitative Analysis Techniques for Construction Engineering and Management Research: The Case of Arctic Water Infrastructure

Construction is a dynamic sociotechnical process, consisting of ongoing interdependencies between people and the built environment. Accordingly, finding solutions to construction challenges when they arise requires understanding the interactions between social and technical factors. Over the past three decades, qualitative methods have been increasingly applied in construction engineering and management (CEM) research to understand challenges within this industry. However, there remains a lack of resources in the CEM literature on qualitative method selection and implementation specifically applicable to this domain. Without such guidance, it can be challenging to choose the most appropriate research methods, which can limit theoretical and practical contributions. To begin to address this gap, this paper offers an overview and comparison of three qualitative data analysis techniques—ranging in their use of induction, prevalence in CEM research, and ability to answer different types of research questions. These analysis techniques are applied to the same semi-structured interview data drawn from a case study on water infrastructure in rural Alaska. Insights gained from each method are compared to illustrate the utility of each technique. To the authors’ knowledge, this study is the first qualitative method-comparison paper published for a CEM audience. Based on the comparison findings, choosing a deductive content analysis can allow for full characterization and quantification of a data set and discussion of results in relation to a predefined framework, such as a framework based on design and construction standards. A hybrid content analysis can expose new, detailed insights for an existing framework by allowing emergent themes to arise and be quantified. Conversely, a constant comparative analysis can reveal emergent trends and uncover the reasons why these trends occur based on connections between prominent themes, which can help CEM researchers develop new theories. Overall, this study helps advance the sociotechnical side of CEM research by enabling the discipline to better address the industry’s complex challenges.

Hybrid GA-MANFIS Model for Organizational Competencies and Performance in Construction

The majority of competency and performance modeling methods available in the literature are deterministic conceptual, statistical, and/or regression models that cannot capture the subjective uncertainty, complex, and nonlinear relationships inherent in construction, which makes accurate prediction difficult. Past studies utilized neuro-fuzzy system (NFS) models, such as adaptive neuro-fuzzy inference system (ANFIS), that combine the learning power of artificial neural networks and functionality of fuzzy systems to develop accurate predictive models. ANFIS is robust, fast, and effective in solving complex problems for a range of real-world construction engineering and management (CEM) applications. NFS models such as ANFIS have some limitations in handling multiple outputs common in construction industry problems, such as being prone to early convergence due to local minima entrapment. To address these limitations, this paper proposes a hybrid NFS combining the evolutionary optimization technique of a genetic algorithm (GA) with a multi-output adaptive neuro-fuzzy inference system (MANFIS) that can handle multi-input multi-output (MIMO) problems for CEM applications. The proposed modeling approach is demonstrated using a case study that showed good results in predicting multiple organizational performance metrics using organizational competencies. The contributions of this paper are threefold: It (1) proposes a novel methodology of integrating different computing techniques for developing a GA-based multi-output adaptive neuro-fuzzy inference system (GA-MANFIS) model that can handle complex and nonlinear MIMO problems inherent in construction processes and practices; (2) relates organizational competencies to performance and predicts multiple organizational performance metrics; and (3) provides a GA-based feature selection approach that reduces data dimensionality, enabling identification of organizational competencies that significantly influence organizational performance. By uniquely integrating these techniques, this model enables construction organizations to evaluate their competencies and predict multiple organizational performance metrics simultaneously, and researchers can adapt it for a variety of construction contexts.

The gold standard: developing a maturity model to assess collaborative scheduling

PurposeThe overall contribution of this work is to provide a usable maturity model for collaborative scheduling (CS) that extends the literature, identifies inconsistencies in schedule development, and improves collaboration in the construction industry.Design/methodology/approachVia subject matter expert elicitation and focus groups, the maturity model establishes five pillars of collaboration—scheduling significance, planners and schedulers, scheduling representation, goal alignment with owner, and communication. The maturity model is then validated through iterative feedback and chi-squared statistical analysis of data obtained from a survey. The five pillars are tied to the literature and previous work in CS.FindingsThe analysis shows that current industry projects are not consistent in collaboration practice implementation, and the maturity model identifies areas for collaboration improvement. The study's contributions to the body of knowledge are (1) developing a maturity model-based approach to define and measure the current level of collaboration and (2) discovering the level of consistency in scheduling collaboration practice implementation.Practical implicationsThe findings provide a benchmark for self-evaluation and peer-to-peer comparison for project managers. The model is also useful for project managers to develop effective strategies for improvement on targeted dimensions and metrics.Originality/valueThe construction engineering and management (CEM) literature does not contain targeted models for scheduling collaboration in the context of maturity and, broadly speaking, neither does the literature at large. The literature also lacks actionable items as presented for the maturity model for collaborative scheduling (MMCS).

Offsite Manufacturing Research: A Systematic Review of Methodologies Used

Debates regarding research methodologies in construction, engineering and management (CEM) literature are long-standing. However, in the growing literature on offsite manufacturing (OSM), such debates are lacking and some studies conflate different components of research methodologies such as research design, methods, data sources, data types, and analytical techniques. This study examines the components of research methodologies reported in the OSM literature and how they compare with the established relationships between the key components of research methodologies. We analyse 74 articles on OSM sampled from 26 journals and find that quantitative methods, case studies, primary data, bibliometric database and modelling are the most preferred methodological approaches. The methodological components reported also cohere with established relationships between components of research methodology, other than the relationship between research methods and data sources. The findings reveal a growing hybridisation of research designs, data sources and analytical techniques, which suggests that methodological plurality is emerging in the OSM literature. This re-echoes concerns regarding the dominance of quantitative methods and the limited use of theory in CEM research, and consequently highlights the need for diversity in methodologies to expand knowledge boundaries.

Applications of fuzzy hybrid techniques in construction engineering and management research

Construction engineering and management (CEM) becomes more complex with increasing project size and complexity. Various fuzzy hybrid techniques have been implemented to handle subjective uncertainty and vagueness in CEM problems. The objective of this paper is to investigate applications of fuzzy hybrid techniques across different CEM applications (e.g., prediction, decision making, optimization) through a systematic review of 255 journal articles published from 2004 to 2021. A checklist of selection criteria for choosing an appropriate fuzzy hybrid technique to solve a specific CEM problem was also established. This study contributes to the body of knowledge by providing a state-of-the-art review of existing fuzzy hybrid techniques utilized in CEM to (1) demonstrate their capabilities to overcome limitations of some standard techniques in solving complex construction problems, (2) determine selection criteria for their applications, and (3) examine the applicability of each fuzzy hybrid technique’s category to given practical construction problems.

A Scientometric Review of Smart Construction Site in Construction Engineering and Management: Analysis and Visualization

With the extensive development and application of information technologies in construction engineering and management (CEM), the construction site is experiencing a rapid digital revolution and transformation. Since smart construction site has become the current research trend and one of the most hot topics, thus this study adopted an integrated bibliometric approach and quantitative analysis to explore the global research on smart construction site. As it is indicated in the content, the bibliometric and scientometric method-based literature review was carried out in this study. To be specific, the co-citation analysis in terms of author, document, and journal; the collaboration analysis in terms of authorship, institutions, and country/region; and category analysis, as well as cluster analysis and burst analysis were conducted based on 2206 peer-reviewed academic papers, which were published from January 2000 to February 2021. It is found that there has been an explosion of relevant publications especially in the past 10 years along with the changing of keywords from flexibility approach to information technologies, 3D reconstruction, IoT technologies, virtual reality, and others. Moreover, the results indicated that the collaborations and cooperation among different institutions, countries, and authors are not close enough, and the most significant research and development in smart construction occurred primarily in the USA, China, and England. Additionally, the smart construction site’s relevant research in terms of publication of quantity was doubled every five years. In addition, the smart construction site relevant research has gradually changed from the traditional project performance associated indicators to smart simulation applications and scenes. Lastly, implementation and management-related concerns about smart construction sites are discussed with seven topics. This study provides researchers and practitioners not merely with an in-depth understanding of the characters and also the trend of smart construction site research in the construction engineering and management field.

Identifying and Controlling Biases in Expert-Opinion Research: Guidelines for Variations of Delphi, Nominal Group Technique, and Focus Groups

In construction engineering and management (CEM) research, conducting field studies often is infeasible because of resource constraints, limited access to sites, practicality, confounding factors, and ethical limitations. Thus, researchers rely on the collection and analysis of expert opinions as an alternative method. Delphi, the nominal group technique, and focus groups often are used to solicit opinions through different processes and controls. Controls implemented during data collection and analysis techniques such as anonymity, multiple rounds, and controlled feedback are used to decrease cognitive and social biases that threaten the validity and reliability of the results. Although there are standard processes for these methods, researchers commonly make modifications to balance research constraints with the study objectives, and it often is unclear how specific modifications promote or degrade the validity and reliability of the results. This paper comprehensively reviewed the existing literature on expert opinion–based studies and argues that seemingly innocuous changes to the traditional methodological frameworks can introduce cognitive biases. A novel conceptual decision-making framework is presented to assist the research community with the development of rigorous experimental designs and transparent interpretation of results when various permutations of key controls are included or omitted in the execution of expert-opinion studies.

Neuro-fuzzy systems in construction engineering and management research

Neuro-fuzzy systems (NFS) can explicitly represent and model the input–output relationships of complex problems and non-linear systems, like those inherent in real-world construction engineering and management (CEM) problems. This paper contributes three things previously lacking in CEM literature: a systematic review and content analysis of published articles related to NFS topics in CEM research; identification of criteria to evaluate different NFS; and recommendations to researchers and industry practitioners in choosing a suitable subset of NFS techniques for solving different types of CEM problems. The literature review reveals that NFS classification methods are based on NFS architecture, learning algorithm, fuzzy method, and application area. This paper systematically categorizes CEM application domains (decision making, prediction/forecasting, evaluation/assessment, system modeling and analysis, simulation, and optimization) and maps them to NFS based on their suitability, which is determined using the performance evaluation criteria of convergence speed, computational complexity, interpretability, accuracy, and local minima trapping.

AN INTEGRATED SCIENTOMETRIC AND SNA APPROACH TO EXPLORE THE CLASSICS IN CEM RESEARCH

This study explores the classics that significantly contribute to the research of construction engineering and management (CEM). Previous studies usually simply applied the number of citation to identify the classics, causing some flaws. To overcome the flaws, an advanced approach is developed by integrating scientometric methods (G-index and co-citation analysis) and a social network analysis (SNA) technique (modularity optimization algorithm), thus providing more precise and persuasive results that denote what academic works have made significant inspirations and illuminations on CEM research. This study retrieves 13,273 CEM literature and extracts 336,129 bibliographies from these literature. Based on the G-index, a total of 67 publications are identified as CEM classics. Moreover, this paper measures and maps the structure of the classics by using co-citation analysis and modularity optimization algorithm. The results provide a basic source of academic information representing the foundation of CEM and draw a big picture of CEM to show the underlying associations between the identified classics. This can help researchers recognize the key scientific contributions for improving the academy progress.

Methodological Pluralism: Investigation into Construction Engineering and Management Research Methods

The quantitative methodological biased debate in the 1990s in Construction Engineering and Management (CEM) Research resulted in researchers considering alternative methodologies. However, a follow up study in 2007 established that CEM remained dominated by quantitative research with only 8.4% of the studies surveyed exclusively using qualitative methods. A decade on, this remains a challenge and an update is overdue. Hence, an investigation to establish the current position regarding the methodological pluralism within CEM research was conducted. A total number of 4,166 articles spanning from 2000 to 2017 were examined from three reputable journals and tier 1 conference. The articles were categorised by the research method(s) used. Overwhelmingly, it was found there are acceptable multi-epistemologies within CEM research and there is a shifted from a dominance of quantitative to an increased utilization of qualitative methodologies and the use of mixed methodologies have shown hopeful progression. The demography of the data was also analysed and discussed. It is concluded that there is an increasing acceptance of methodological pluralism and CEM and its industry are on the verge of experiencing a competitive advantage, which could result in improved performances with utilization of balanced research methodologies (if applied appropriately).

Unpacking Ontological Perspectives in CEM Research: Everything Is Biased

AbstractMethodological debates are nothing new in construction engineering and management (CEM) research. However, when the consequences, and at times even the content, of such debates are consider...

Analytic Overview of Citation Metrics in the Civil Engineering Domain with Focus on Construction Engineering and Management Specialty Area and Its Subdisciplines

Several data-based metrics have been developed to evaluate the quality of research output, including h-index, impact factor, and others. Considerable debates have focused on whether the aforementioned metrics represent effective and efficient indications of research impact or just provide an imperfect reflection. Because the academic community is witnessing a growing trend where most of the tangible rewards are related to publications and their quality, there is a dire necessity to obtain a more realistic and holistic understanding of such evaluation indicators. As such, the goal of this paper is to investigate the parameters associated with the citation metrics used to assess the quality and impact of research publications in the broad civil engineering (CE) domain with a focus on the construction engineering and management (CEM) specialty area and its subdisciplines. To this end, the authors (1) analyzed the different CE research areas—including CEM—with respect to the number of publications, community size, and potential ties with other interdisciplinary fields; (2) studied the citation metrics of the most-cited as well as award-winning peer-reviewed publications in both CE and CEM while examining the effect of the availability of research funds as well as the nature of the research—quantitative or qualitative—on the average number of citations for most-cited publications across the different CE specialty areas; and (3) investigated the impact of multiple factors on the citation metrics. Based on a thorough survey and analysis of 67,800 journal publications, it was found that both number of publications and citation metrics for the CEM specialty area is significantly lower compared with other CE specialty areas. Along the same vein, the citations across the various CEM subdisciplines are all different, where labor and personnel (306 average citations per paper) and contracting (266 average citations per paper) are the most cited, but cost and schedule (47 average citations per paper) and legal and contractual (23 average citations per paper) are the least cited. Also, with the exception of aerospace engineering as well as engineering education and practices, CEM was the least funded, had the highest percentage of qualitative research, and the least average number of citations for funded/unfunded projects as well as qualitative/quantitative research. Further, it was revealed that award-winning papers—which supposedly represent the highest quality—are not highly cited and in fact have way below average citation numbers. Ultimately, it was found that several factors such as research community size, trendiness of research field, amount of research output, connection with other interdisciplinary fields, characteristics and attributes of coauthors, timing of checking an h-index, publication access type, and the criteria adopted by the various archiving databases collectively affect the citation metrics for papers and authors. As such, citation metrics like h-index should not be used solely to assess the quality and impact of an author but rather be utilized as a single piece of information within a more holistic and broader context. This study furnishes various parameters and considerations that should be normalized before attempting to compare citations of papers and/or authors across the CE domain.

Scientometric analysis of BIM-based research in construction engineering and management

PurposeThe purpose of this paper is to summarize the latest research of BIM adoption in construction engineering and management (CEM) and propose research directions for future scholarly work. During the recent decade, building information modeling (BIM) has gained increasing applications and research interest in the construction industry. Although there have been review-based studies that summarized BIM-based research in the overall architecture, engineering and construction (AEC) area, there is limited review that evaluates the current stage of BIM-based research specifically in the CEM sub-area.Design/methodology/approachCEM falls into the scope of AEC. It involves construction-related tasks, activities and processes (e.g. scheduling and cost estimates), issues (e.g. constructability), as well as human factors (e.g. collaboration). This study adopted a holistic literature review approach that incorporates bibliometric search and scientometric analysis. A total of 276 articles related to BIM applied in CEM were selected from Scopus as the literature sample for the scientometric analysis.FindingsSome key CEM research areas (e.g. CEM pedagogy, integrated project delivery, lean and off-site construction) were identified and evaluated. Research trends in these areas were identified, and analyses were carried out with regard to how they could be integrated with BIM. For example, BIM, as a data repository for ACE facilities, has substantial potential to be integrated with a variety of other digital technologies, project delivery methods and innovative construction techniques throughout the whole process of CEM.Practical implicationsAs BIM is one of the key technologies and digital platforms to improve the construction productivity and collaboration, it is important for industry practitioners to be updated of the latest movement and progress of the academic research. The industry, academics and governmental authorities should work with joint effort to fill the gap by first recognizing the current needs, limitations and trends of applying BIM in the construction industry. For example, it needs more understanding about how to address technical interoperability issues and how to introduce the integrated design and construction delivery approach for BIM implementation under the UK BIM Level 2/3 framework.Originality/valueThis study contributed to the body of knowledge in BIM by proposing a framework leading to research directions including the differences of BIM effects between design-bid-build and other fast-track project delivery methods; the integration of BIM with off-site construction; and BIM pedagogy in CEM. It also addressed the need to investigate the similarities and differences between academia and industry toward perceiving the movement of BIM in construction field work.