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In civil and construction engineering education research, a focus has been on using 3D models to support students' design comprehension. Despite this trend, the predominant mode of design communication in the industry relies on 2D plans and specifications, which typically supersede other modes of communication. Rather than focusing on the presentation of less common 3D content as an input to support students' understanding of a design, this paper explores more common 2D inputs, but compares different visualization formats of student output in two educational interventions. In the first intervention, students document a construction sequence for wood-framed elements in a 2D worksheet format. In the second, students work with the same wood-framed design, but document their sequence through an augmented reality (AR) format where their physical interactions move full-scale virtual elements as if they were physically constructing the wood frame. Student approaches and performance were analyzed using qualitative attribute coding of video, audio, and written documentation of the student experience. Overall, results showed that the 2D worksheet format was simple to implement and was not mentally demanding to complete, but often corresponded with a lack of critical checks and a lack of mistake recognition from the students. The AR approach challenged students more in terms of cognitive load and completion rates but showed the potential for facilitating mistake recognition and self-remediation through visualization. These results suggest that when students are tasked with conceptualizing construction sequences from 2D documentation, the cognitive challenges associated with documenting a sequence in AR may support their recognition of their own mistakes in ways that may not be effectively supported through 2D documentation as an output for documenting and planning a construction sequence. The results presented in this paper provide insights on student tendencies, behaviors, and perceptions related to defining construction sequences from 2D documentation in order for educators to make informed decisions regarding the use of similar learning activities to prepare their students for understanding the 2D design documents used in industry.

The Journal of Construction Engineering & Management has announced the recipients of the 2023 Best Paper Award. The winning paper, titled "Deep Learning Image Captioning in Construction Management: A Feasibility Study," explores the automation of deep learning for image captioning in the construction management field. The authors present a systematic approach that includes developing a linguistic schema, creating a dataset of manually captioned images, and evaluating six deep-learning methods using eight metrics. The paper concludes that a method combining two advanced deep learning processes performed the best, and that automatic captioning in construction management is feasible. The article provides valuable insights and suggestions for future development in this area. [Extracted from the article]

The process of new construction and reconstruction projects in the petrochemical industry is complicated, and the construction accidents have a domino effect. Construction permit-to-work management is an important part of petrochemical engineering, mainly to ensure the identity of workers entering the construction area and permit-to-work qualification. The previous research on permit-to-work management mainly focused on the standardization of the permit-to-work issuing process and the precision of the implementation process rather than specific and implementable technological means. However, with the increase of new construction and reconstruction projects in the petrochemical industry, the traditional and paper-based work permit management model cannot effectively prevent people without working qualifications from entering the construction site at the source, and these solutions do not take into account the compliance, feasibility, and timeliness of the use of qualified permit-to-work. Therefore, from the perspective of brand-new management theory, this study organizes the elements of petrochemical construction permit-to-work management into three levels of product, organization, and process (POP). Then the permit-to-work management system of petrochemical construction based on the POP model is proposed. The face recognition technology is used to realize the real-time dynamic control of the system. The results show that the validity of the petrochemical construction permit-to-work management system based on the POP model in the actual project can realize the transformation permitto-work from paper to electronic. In addition, it can effectively and quickly verify the permit-to-work qualification of the entry personnel and prevent the retired personnel from returning to the site. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The construction industry is characterized by its complex and dynamic nature, requiring efficient resource management practices for successful project execution. This systematic literature review aims to comprehensively analyze and synthesize existing research on resource management practices within the construction sector. By examining a wide array of scholarly articles, conference papers, and industry reports, this review identifies and evaluates the various methodologies, strategies, and tools employed for effective resource management in construction projects. The review encompasses an extensive analysis of key themes, including but not limited to labor management, equipment utilization, material procurement, and technological advancements in resource optimization. It delves into the challenges faced by the construction industry concerning resource allocation, skill shortages, cost control, sustainability concerns, and the impact of unforeseen disruptions. Furthermore, this review critically assesses the implications of resource management practices on project performance, encompassing aspects such as project timelines, budget adherence, quality control, and stakeholder satisfaction. The findings from this systematic review provide a comprehensive understanding of the current state of resource management practices in the construction industry. Additionally, it identifies gaps in the literature and suggests areas for future research, emphasizing the need for innovative approaches and adaptive strategies to address the evolving demands and complexities within construction project management. [ABSTRACT FROM AUTHOR]

Students pursuing applied degrees often express their desire for learning experiences that help them transition from academic to professional settings. The Teaching with Industry (TWI) model is a course design that combines videoconferencing technologies with best practices in online instruction to support greater industry presence during class sessions. The following paper describes TWI design iterations that were used in an undergraduate course on construction management safety practices. The designs featured industry practitioners as co-instructors but used different classroom setups and configurations of videoconferencing technologies to support their activities. Configurations, as well as challenges and affordances of the TWI designs are described; implications for future TWI designs and practices are discussed.

This paper reflects on the work-integrated learning (WIL) program in an undergraduate Construction Engineering and Management (CEM) department in Indonesia. Given the industrial revolution that has transformed the construction industry into Construction 4.0, concrete steps are needed to bridge the needs of industry for professional workers who are aware of Construction 4.0 concepts. This study aims to develop a WIL model adjusting to Construction 4.0 concepts. A case study of the internship experience that has been conducted for four consecutive years was used to develop the model. This observation was reinforced by a questionnaire survey aimed at students, workplace supervisors and lecturers to evaluate the effectiveness of the internship program in achieving the learning outcomes. The results of this analysis coupled with the findings from the integrative literature review were used to develop a Construction 4.0 WIL model.

Construction detail (CD) knowledge is one of the leading learning components in architectural technology (AT) study. The traditional pedagogical method adopts a series of two-dimensional drawings to explain three-dimensional objects. The interactive and immersive features of virtual reality (VR) technology attract attention from the educational sector. While architectural design education has begun exploring integrating VR tools in the classroom, especially in the early design stage, AT is one of the very few subjects that have experimented with VR. This research, undertaken from within a larger, ongoing project, aimed to explore if VR could assist in teaching AT knowledge, especially CD. The project has two phases: phase 1 created several VR lessons that explained specific AT knowledge, using a VR technology currently available for educational purposes; phase 2 adopted a mixed method approach to investigate learners' experience with the VR lessons created. This paper focuses on the experience in building up a VR learning environment in phase 1. The initial findings after phase 1 showed that the VR technology adopted in this project was not a perfect tool in creating a VR experience in the CD field but could still offer students degrees of virtual reality learning experience.

Social interaction between students is a crucial but under-researched part of the education realm. Understanding how connections form in university classes and their effects on learning outcomes may provide extraordinary knowledge for researchers, educators, and policy-makers. This paper collected data from the questionnaire survey and then processed them with Gephi software to produce visualization and measurement. Initial results seem to indicate a significant correlation between students' connectedness and academic performance in one class. However, in another class, the results show a contrasting situation as there is no evidence that social network attributes impact learning performance. Taken together, these results would seem to suggest that the characteristics of the network should be judged on a case-by-case basis, and large-scale SNA analyses have been rarely reported. This present study provides a springboard for a new way to shed some light on classmates' interconnection. Using a similar approach to this article, it is believed that there is ample opportunity to study the association between classmate connectedness and career success. Research techniques and approaches around Social Network Analysis are expected to evolve further in the foreseeable future.

Buildings are complex structures composed of heterogeneous elements; these require building management systems (BMSs) to dynamically adapt them to occupants' needs and leverage building resources. The fast growth of information and communication technologies (ICTs) has transformed the BMS field into a multidisciplinary one. Consequently, this has caused several research papers on data-driven solutions to require examination and classification. This paper provides a broad overview of BMS by conducting a systematic literature review (SLR) summarizing current trends in this field. Unlike similar reviews, this SLR provides a rigorous methodology to review current research from a computer science perspective. Therefore, our goal is four-fold: (i) Identify the main topics in the field of building; (ii) Identify the recent data-driven methods; (iii) Understand the BMS's underlying computing architecture (iv) Understand the features of BMS that contribute to the smartization of buildings. The result synthesizes our findings and provides research directions for further research. [ABSTRACT FROM AUTHOR]

When deciding which project to fund, the comparison of project-required resources and monetary or financial benefits is relatively straightforward (as these can be presented in dollar values). In contrast, comparing the nonmonetary benefits of projects can be challenging. The literature often overlooks this problem and only provides high-level approaches (e.g., comparing a project's contributions to the organization's strategic goals). Such approaches are inefficient as they are highly subjective and may be impacted by decision-makers' bias. To this point in time, the literature has not effectively addressed this problem. This literature gap and the practical importance of the problem motivate the development of detailed step-by-step methodological processes to reduce subjectivity and enable a quantitative comparison of the nonmonetary benefits of projects. This paper develops such a novel straightforward methodology and illustrates its application through a case study where nonmonetary benefits of a railway construction project are compared against a hospital expansion project. In addition to this methodological contribution, this paper also contributes to the current literature on construction engineering and management by showing how to perform an effective comparison of the nonmonetary benefits in the project investment decision. The paper also sheds light on how the reasoning structures of different project decision makers may be impacted by their degree of optimism. Practical Applications: Construction projects may deliver a range of dissimilar benefits. Unlike monetary values (such as required resources and financial or monetary benefits), the comparison of nonmonetary benefits (e.g., social values) of different proposals can be challenging. This paper provides a two-phased methodology to facilitate this comparison. In the first phase, two straightforward questions are asked to draw benefit satisfaction graphs, and in the second phase, different future scenarios are integrated to make the comparison process more reliable. Ultimately, a methodology is developed to show how the nonmonetary benefits of different projects can be compared. It is then illustrated on a case from the Australian government where the nonmonetary benefits of a railway construction project are compared against those of a hospital expansion project to assist with the decision as to which project should be given a higher priority to be funded. [ABSTRACT FROM AUTHOR]

Effective safety management is crucial in the construction industry. The growing interest in employing Knowledge Graphs (KGs) for safety management in construction is driven by the need for efficient computing-aided safety practices. This paper systematically reviews the literature related to automating safety management processes through knowledge base systems, focusing on the creation and utilization of KGs for construction safety. It captures current methodologies for developing and using KGs in construction safety management, outlining the techniques for each phase of KG development, including scope identification, integration of external data, ontological modeling, data extraction, and KG completion. This provides structured guidance on building a KG for safety management. Moreover, this paper discusses the challenges and limitations that hinder the wider adoption of KGs in construction safety management, leading to the identification of goals and considerations for future research. [ABSTRACT FROM AUTHOR]

In recent years, the topic of climate change has been increasingly noticed by the public, and carbon emission reduction is one of the primary targets for various industries worldwide. The construction industry has a profound influence in this field, so it is significant to consider what kind of efforts can be made in building projects. Many scholars agree to promote prefabrication technology for construction, but its application still faces several challenges. By undertaking desk research, this paper explores the motivation and barriers to adopting modular techniques in construction projects under the lifecycle analysis. The preliminary information of the literature review is collated from dozens of peer-reviewed academic papers. Under the whole lifecycle thought, the PEST analysis tools also present the analytical results. This research finds that the top five barriers are the attitudinal resistance to using modular constructions, lack of sufficient modular expertise and practice, increasing costs and risks on supply chain management, insufficient government support and policy making, and high design and planning requirements. Moreover, the lifecycle analysis can divide the collated barriers into each stage, and adequate government support can assist in promoting the prefabrication in building projects in financial, legal, and technical aspects. The current findings can facilitate the broader use of prefabrication in building projects, improving the environmental sustainability of stakeholders. The process of proposed desk research can also be considered a referenced pattern for other related studies. More first-hand data should be collected and evaluated in further research to improve accuracy and adapt to the newest research field and industrial situations. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Objective, accurate and fair development of research and effective performance prediction methodology for the construction of the talent team is the current needs of the new era of innovation and reform and development of university management, as well as the need to improve the quality of scientific research and teaching level of the talent team. OBJCTIVES: To address the problems of irrational principle of indicator selection, incomplete system and imprecise methodology in the current research on performance prediction of talent team building. METHODS: This paper proposes a talent team construction performance prediction method based on intelligent optimization algorithm improving neural network with integrated learning as the framework. First of all, through the analysis of the current talent team construction performance prediction influencing factors selection principles, analyze the talent team construction performance management process, select the talent team construction performance prediction influencing factors, and construct the talent team construction performance analysis system; then, with the integrated learning as a framework, improve the neural network through the internal search optimization algorithm to construct the talent team construction performance prediction model; finally, through the simulation experiments to analyze and verify the effectiveness and superiority of the proposed method. The effective type and superiority of the proposed method are verified. RESULTS: The results show that the proposed method satisfies the real-time requirements while improving the prediction accuracy. CONCLUSION: This paper addresses the lack of precision in forecasting the performance of the talent pipeline and the lack of a sound analytical system. [ABSTRACT FROM AUTHOR]

With the rapid advancement of Unmanned Aerial Vehicle (UAV) technologies in recent years, their uses have been increasingly adopted in the architecture, engineering, and construction industries. To satisfy the needs of various types of construction projects, a considerable amount of research work has been performed to implement and refine the operations, safety, and accuracy of UAVs. This paper presents the findings of a comprehensive literature review that focuses on UAV research in construction management during the timeframe of 2016 to 2021. A total of 95 papers were identified and collected from a list of 21 relevant journals and conference proceedings, and were then categorized by their research topic, sensor types, and targeted structures. The results of 47 exemplary studies were reported in two categories, namely UAV uses and construction uses. The research topics identified for UAV uses include algorithm, applications, operations, framework, and training, while research topics identified for construction use include inspection, surveying, safety, and monitoring. The connection between the research topics, sensor types, targeted structures, and other advanced technologies were also discussed. This paper summarizes the current results of UAV research in construction management, reviews the methodology, benefits, and limitations of the reviewed literature, and provides valuable knowledge for the future trend of UAV applications in the civil, infrastructure, and construction industries. [ABSTRACT FROM AUTHOR]

Sustainable development is essential for the survival of the planet. The massive increase in GHG emissions due to human activities has put the world in unrest. The Indian construction industry is emerging and evolving at a rapid rate and has understood the grave situation, and for saving the environment has come up with innovative solutions for developing green buildings or sustainable construction. In this paper, the two different (the GRIHA Rating System and the IGBC Green New Building Rating System) of India were studied. The sample size was 40 construction professionals working on green building projects. An interview schedule was used for data collection. The data was subjected to a suitable analysis and the AHP method was applied. Based on the research findings, strategies to go green has been suggested for the IGBC and GRIHA rating system which may serve as a ready reckoner for enhancing the effectiveness and efficiency of the construction management process. Therefore, keeping in mind the above view this research paper "Review of Indian Green Building Rating Systems by Using Analytical Hierarchy Process (AHP) on Various Parameters" becomes indispensable. Hence, this research study can be considered an effort to empower construction professionals to create an extensive analysis of green building concepts and develop sustainably in India. [ABSTRACT FROM AUTHOR]

This paper addresses three research questions: (1) According to the pertinent literature, what are the main causes of the current gender gap in the construction industry, particularly for management and leadership roles? (2) Is there a significant difference between male and female high-school-age students regarding their level of knowledge of the construction industry? (3) Is there a significant difference between male and female high-school-age students in their perception of the construction industry and factors impacting their career choice? These research questions are addressed by a review of the literature followed by a discussion of precamp survey results from two consecutive years of a two-week high school summer camp, which is focused on construction science and management. The literature review reveals that the issues are deep-routed and complex but can in general be categorized into two groups: the recruitment and retention of women in construction management and related careers. While the literature review summary in this paper addresses both categories, the focus of the paper remains recruitment, particularly through a study of high school students' level of knowledge and perceptions of construction management. The pre-camp surveys assessed the participants' baseline knowledge and perceptions of construction management as a career. The results showed that the knowledge of construction management as a career is very low, with no statistically significant difference between genders. It must be noted here that the participants are biased positively toward the construction management and related careers, as they chose to attend the camp for a variety of reasons, from wanting an experience on the campus of this university to parents' encouragement. Despite this baseline interest, however, the data show that the participants lacked clarity on what this career really entails. It is suggested, therefore that the general knowledge of this career path across larger and more randomized samples across U.S. will be even lower. The perceptions of the construction industry differed slightly between genders, with females perceiving it as more physically challenging and prioritizing family friendliness when considering career options. In conclusion, both the literature review and the survey data analysis show that the lack of knowledge of this career path, exacerbated by the negative perceptions of the construction industry, contribute to the problem of women not choosing to study construction management. The construction industry continues to make significant improvements in their diversity and inclusion efforts, and there are a variety of paths within the industry for graduates of construction science and management degrees. As such, significant work remains for both the industry and academia to overcome the lack of knowledge and negative perceptions of the industry through increased outreach to better inform high school students, parents, and counselors. [ABSTRACT FROM AUTHOR]

Determining whether to invest in a project is a complex and challenging decision. This project investment decision relies heavily on its promised strategic goals (i.e., target benefits) stated in its business case and which are expected to be realized following project completion. However, in many cases, the proposed project benefits are far greater than those that the project realistically can achieve, leading to the risk of projects being funded erroneously. The construction management literature has offered approaches such as reference class forecasting (RCF) to rectify unrealistic project estimates. This paper identifies weaknesses in the current approaches, exposes their inefficiency, and proposes a step-by-step stratified approach as an effective alternative to detect, measure, and rectify unrealistic estimates of project benefits, and utilizes the proposed approach on a light rail construction project. The contribution of this approach is that each project benefit target can be rectified differently, based on the measurable levels of deviation from more-realistic estimates. This paper advances the construction management literature by enabling managers to set realistic project goals in the project front end, increase the reliability of estimates in the project business case, and improve the quality of project investment decisions. The decision to fund a construction project is impacted by information included in business cases and proposals, such as the estimated project cost and expected goals. However, such information often is unrealistic or exaggerated (to make the project more attractive for funding), which negatively impacts investment decisions made by senior executives. As a result, projects can be funded erroneously, causing a waste of resources and potential failure to achieve its unrealistic expectations. Because the existing literature offers little guidance for how to ensure that project goals are realistic, this paper developed and illustrates a step-by-step process for measuring and rectifying the gap between proposed and realistic project goals to alert senior executives when a proposed project is unlikely to meet its proposed goals. [ABSTRACT FROM AUTHOR]

Blockchain–Interplanetary File System (IPFS) integration has attracted increasing attention in construction management for addressing storage limitations and improving efficiency. However, a comprehensive evaluation of such integration is lacking. Whether it is practically available remains unclear. In addition, the lack of information encryption mechanism in current blockchain-IPFS solutions may cause security risks. Thus, its wide acceptance is hindered. To address this insufficiency, this paper proposes a hybrid blockchain-IPFS system to improve normativeness, security, and the efficiency of information sharing in precast supply chain management (PSCM). Firstly, consideration analysis of system development was conducted based on user-centered design philosophy, identifying practical needs of information sharing in PSCM and comprehensively evaluating current solutions. Based on identified insufficiencies, a hybrid blockchain-IPFS system is proposed with formalization, security, and efficiency considerations. Specifically, an Omniclass-based classification system is proposed for formalizing information sharing in PSCM, in which multiple channels are introduced to improve security. Furthermore, a two-step lightweight asymmetric encryption scheme is established to protect data privacy. Finally, an off-chain data storage scheme is constructed combining IPFS with cloud-based object storage service. The feasibility of our proposed system was validated by a focus group in a real-world case. This research contributes to the body of knowledge by improving information sharing in PSCM with improved security and advancing its standardization process. This is one of the first studies that conducted both technical and practical evaluation of blockchain-IPFS in practical projects, providing valuable reference for future endeavors in its implementation. Both theoretical and practical implications are discussed to suggest future research directions and ways to improve its adoption practices. [ABSTRACT FROM AUTHOR]

In papers published in Journal of Civil Engineering and Management, many applications of fuzzy logic can be found. To commemorate the contributions of the fuzzy set theory proposed by Professor Lotfi Zadeh to the fields of civil engineering and construction management, seven papers were selected for this special issue. These papers combined fuzzy set theory with appropriate methods to solve specialized problems in the fields of civil engineering and construction management, and provided good insights for the applications of fuzzy technology in solving problems related to civil engineering and construction management. [ABSTRACT FROM AUTHOR]

As construction projects become increasingly complex, modular integrated construction (MiC) has emerged as a pivotal solution, driving integrated development in complex projects. However, the reliance on prefabricated modules underscores the crucial role of supply chain management (SCM) in MiC, necessitating strategic planning and operational control. This study aimed to use bibliometric analysis to map the SCM knowledge domain within MiC. Through the use of keywords related to "supply chain" and "MiC", 196 relevant papers were extracted from the Web of Science database. These papers were subjected to co-citation analysis, keyword co-occurrence analysis, and time span analysis to elucidate the historical evolution, multidisciplinary domains, and future directions in planning and control within SCM-MiC. The research identified two milestones in SCM-MiC's historical trajectory, enhancing our understanding of its foundations. Moreover, 11 clusters were identified, illustrating the multidisciplinary nature of SCM-MiC. Dividing the literature into seven stages of the supply chain, the research outlined four research directions aligned with project complexity and technological development, highlighting current hotspots and gaps of the strategic planning and control. These directions bridge the construction management and information technology domains, guiding future SCM-MiC research within complex project management. [ABSTRACT FROM AUTHOR]

In the Architecture, Engineering and Construction (AEC) industry claims arise frequently, often resulting in disputes. Claim management should be efficient to prevent claims from escalating into disputes, and if disputes are still unavoidable, they should be resolved without delay for the construction process to resume. First, by conducting a bibliometric review, this paper attempts to investigate the literature on construction claims and dispute resolution practices by employing the Scopus database and VOSviewer to retrieve and analyze related sources. The overall trend of research by country, source, and authors is detected, and the emergence of novel technologies such as BIM, blockchain, and smart contracts appearing after 2020 concerning the investigation into construction claim management and dispute resolution was identified. Second, a content analysis on the most recent publications published between 2020 and 2022 was undertaken, indicating six main research themes that represent current research trends. The employment of novel technologies to enhance claim management and dispute resolution practices in the AEC sector is identified, as well. Finally, in order to assist construction professionals and researchers in their work to address construction claims and disputes more efficiently, potential research directions are proposed. [ABSTRACT FROM AUTHOR]

Crane-lift planning is critical but challenging to ensure construction safety and efficiency for the installation of heavy components. It engages a group decision-making process that involves various stakeholders to exchange knowledge of crane capabilities, site characteristics, and operational feasibility. However, conventional planning methods based on drawings, animations, and standalone virtual prototypes are inefficient in enabling collaborative decision-making due to rigid visualization and inflexible interactions among different stakeholders. This paper aims to develop a collaborative heavy lift planning (Co-HeLP) system that engages crane suppliers, site managers, and crane operators in an immersive and shared environment for crane layout optimization and lifting simulation. Specifically, the system incorporates a multiuser networking unit to enable stakeholders to design crane-lift layouts concurrently and synchronize changes in real time for facilitating information-sharing and collaborative planning. In addition, a cross-platform virtual reality (VR) unit is developed to provide stakeholders with role-tailored interactions of crane allocation and first-person operation. Automatic feasibility checking is also formulated to assist stakeholders in appraising jib reach limits and loading capacities more efficiently. The system is demonstrated using a real-life modular building project that involves the installation of multiple bulky modules. To evaluate the system, two groups of industry practitioners from crane suppliers and main contractors conducted heavy lift planning using Co-HeLP, where their responses were collected using questionnaire-based surveys and interviews. Results show that the system is rated highly on automatability (0.77/1), collectiveness (0.81/1), and applicability (0.85/1), with the advantages of full-scale visualization and multirole interactions. This paper opens up new possibilities for stakeholders to jointly manage crane-lift constraints and build consensus on layout plans through a mutually interactive and role-independent shared environment. More broadly, the paper derives a generic multiuser VR mechanism to address fragmented coordination and inefficient knowledge transfer, thereby facilitating collective planning and management in construction. [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0, marked by the integration of digitization, automation, and data synthesis, emerging technologies play a vital role in mitigating ergonomic hazards within construction work environments. This study investigates the research trends encompassing the adoption of three categories of emerging technologies—(1) wearable sensors; (2) extended reality, which combines virtual reality (VR), augmented reality (AR), and mixed reality (MR); and (3) exoskeletons and robotics—as the means to mitigate the risk of occupational nonfatal injuries in the construction industry. Employing bibliometric and scientometric analyses, a quantitative examination of the relationship in the literature is performed. From the Scopus database, 347 papers were selected from a pool of 1603 publications from 2018 to 2022. The conducted scientometric analyses encompass annual publication trends, keyword co-occurrence analysis, journal-source analysis, author analysis, and country analysis using VOSviewer (version 1.6.19) and bibliometrix software (version 4.1.3). The findings highlight the crucial role of advanced technologies in enhancing safety and health management in the construction industry. Wearable sensors, for example, offer promising capabilities for real-time monitoring, potentially reducing the risk of onsite injuries by alerting workers to hazards. Extended reality, especially VR, can enhance the effectiveness of safety-training education by simulating realistic scenarios while minimizing exposures to hazardous conditions that workers may face onsite challenges. Furthermore, the integration of exoskeletons and robotics has the potential to reduce physical strain and injury risks among workers, particularly in physically demanding tasks. The review paper identifies current research trends in applying emerging technologies to occupational safety and health within the construction industry, while also suggesting future research directions in this dynamic field. [ABSTRACT FROM AUTHOR]

Despite the significance of resource levelling, project managers lack various ways to smooth resource usage fluctuation of a repetitive construction project besides changing resource usage. Tolerating interruptions is an effective way to provide flexibility for a schedule but is ignored when solving resource levelling problems. Therefore, this paper investigates the impacts of interruptions on resource usage fluctuation and develops an integrated approach that simultaneously integrates two scheduling adjusting processes: changing resource usage and tolerating interruptions. In this paper, two interruption conditions are proposed to identify which activities are suitable to be interrupted for smoothing resource usage fluctuation. The traditional resource levelling model is modified to a new scheduling model by incorporating interruptions. A two-stage GA-based scheduling algorithm is developed by integrating changing resource usage and tolerating interruptions. A commonly used pipeline project is adopted to illustrate the steps of the proposed approach and demonstrate its effectiveness and superiority through comparison with previous studies. A large-scale project further verifies the usability of the proposed approach. The results confirmed the feasibility to smooth resource usage fluctuation by interruptions, and the integrated approach can achieve a more competitive resource levelling result. [ABSTRACT FROM AUTHOR]

Previous studies revealed that Building Information Modeling (BIM) has the potential to reduce project uncertainties, design errors, change orders, and delays, which might facilitate achieving effective dispute management in the construction industry. However, research into the adoption of BIM to holistically enhance effective dispute management is limited compared with the plentiful BIM research in the construction management field. This study explored whether and how BIM adoption can help minimize the chronic problem of dispute in the industry. A structured critical literature review method was employed in this study which involved 102 papers in the fields of BIM and construction disputes. Nine main common causes of disputes (e.g., change order, design error, site problem, contractual problem, payment problem, and delay) and eight primary benefits of BIM application (e.g., improved visual management, design optimization, improved information management, and enhanced collaboration) were identified. A conceptual framework was developed illustrating the mechanism of adopting BIM to facilitate dispute management in the overall life cycle of construction projects. The framework indicates that design error, delay, and change order can be reduced most significantly by most of the BIM benefits, whereas improved visual management, improved information management, and enhanced collaboration are three of the most frequently adopted BIM benefits that can settle the majority of dispute causes. This study contributes to dispute management with a more holistic view of adopting BIM in the life cycle of construction projects, as illustrated in the conceptual framework. In addition, the identified common causes of disputes and primary benefits of BIM application are valuable for on future research in these two areas. The research findings are valuable for practitioners to obtain a holistic understanding of the two topics of dispute causes and BIM benefits, both independently and integrally. First, the identified common causes of disputes can be used by project managers to develop more-targeted strategies for reducing potential disputes in their projects. Second, the identified BIM benefits provide a comprehensive view of the advantages of BIM application for the clients, which will enable them to use BIM in their projects more proactively. Finally, and more importantly, the research findings indicated that BIM could be used to manage disputes in the global construction industry more effectively. The identified BIM features and other technologies or tools in dispute management present comprehensive results illustrating how to use BIM directly or indirectly for dispute management. In addition, the proposed framework is valuable for practitioners to find better solutions to prevent and control construction disputes via the application of BIM throughout the project life cycle. [ABSTRACT FROM AUTHOR]

Cost overrun has remained a key risk of construction projects that can be prevented by utilizing new technologies. This paper aims to identify the gap in the literature, which can potentially be addressed by using digital tools and technologies, by reviewing the current and state of the art practices. The paper presents the results of a systematic and critical content reviews on cost overruns, to address the question of what factors are affecting the cost overrun. This paper also reviews how building information modeling (BIM) in conjunction with other tools, such as the common tools in the Asia and Asia Pacific regions, are used for cost estimation and monitoring. The paper presents the results of the content review, including their contributions and limitations, which are also used to set key directions for future investigations. A total of 176 papers was identified to develop the construction cost management (CCM) dataset. The method was a mix of systematic reviews, including co-authorship network analyses, co-occurrence analytical map development covering 5671 keywords, and content analysis including theme identification and a critical review of selected papers. The paper critically reviewed 63 selected papers from CCM, which are divided into four clusters based on their scopes: BIM adoption for cost estimation and quantity surveying; BIM implementation for a bill of quantity, risk paths, and cost overruns; cost control and management; and, finally, BIM, virtual design, and value management. A trend analysis using a set of 16 themes (e.g., 3D model, BIM, Decision, Energy, and Life Cycle) for all the papers over the past ten years was developed. The content of each cluster of papers was reviewed based on the frequency of the selected themes in each cluster. The content of each cluster of papers was also reviewed critically and gaps were identified, so a set of directions for future investigations are presented. [ABSTRACT FROM AUTHOR]

In the process of quality inspection of Remote sensing image data results, the reuse of spatial location information of multiple units, multiple projects and multiple sources can not only overcome the problems of long time to obtain control information, high cost and difficulty in obtaining some areas, but also the basis for achieving efficient and high-precision geometric correction. From the perspective of reusability of checkpoints and saving the cost of quality inspection of remote sensing images, this paper discusses the necessity of joint construction of multi-source and multi-resolution image checkpoint database. And put forward the construction principle and management objectives of checkpoint database. At last, this paper briefly introduces and prospects the application of the national multi-source and multi-resolution image checkpoint database. [ABSTRACT FROM AUTHOR]

Urban park green areas are part of territorial space planning, shouldering the mission of providing residents with high-quality ecological products and public space. Using a combination of several measurement models such as the BCG (Boston Consulting Group) matrix, ESDA (Exploratory Spatial Data Analysis), MLR (Machine Learning Regression), GWR (Geographically Weighted Regression), and GeoDetector, this paper presents an empirical study on the changes in Urban Park Green Areas (UPGAs) in the Grand Canal of China. By quantitatively measuring the spatio–temporal evolution patterns of UPGAs, this study reveals the driving mechanisms behind them and proposes policy recommendations for planning and management based on performance evaluation. The spatio–temporal evolution of UPGAs and their performance in China's Grand Canal are characterized by significant spatial heterogeneity and correlation, with diversified development patterns such as HH (High-scale–High-growth), HL (High-scale–Low-growth), LH (Low-scale–High-growth), and LL (Low-scale–Low-growth) emerging. The evolution performance is dominated by positive oversupply and positive equilibrium, where undersupply coexists with oversupply. Therefore, this paper recommends the implementation of a zoning strategy in the future spatial planning of ecological green areas, urban parks, and green infrastructure. It is also recommended to design differentiated construction strategies and management policies for each zoning area, while promoting inter-city mutual cooperation in the joint preparation and implementation of integrated symbiosis planning. Furthermore, the spatio–temporal evolution of the UPGAs in the Grand Canal of China is influenced by many factors with very complex dynamic mechanisms, and there are significant differences in the nature, intensity, spatial effects, and interaction effects between different factors. Therefore, in the future management of ecological green areas, urban parks, and green infrastructure, it is necessary to interconnect policies to enhance their synergies in population, aging, industry and economy, and ecological civilization to maximize the policy performance. [ABSTRACT FROM AUTHOR]

In the ambitiously evolving construction industry of Kuwait, characterised by its vision 2035 and rapid technological integration, there exists a pressing need for advanced analytical frameworks. The pressing need for advanced analytical frameworks in the Kuwait Construction Market arises from the necessity to identify inefficiencies, predict market trends, and enhance decision-making processes. For instance, these frameworks can be used to detect anomalies in investment patterns, forecast the impact of economic changes on project timelines, and optimise resource allocation by analysing labour and material supply data. By leveraging deep learning techniques, such as autoencoder neural networks, stakeholders can gain deeper insights into the market's complexities and improve strategic planning and operational efficiency. This research paper introduces a deep learning approach utilising an autoencoder neural network to analyse the complexities of the Kuwait Construction Market and identify data irregularities. The construction sector's significant investment influx and project expansion make it an ideal candidate for deploying sophisticated analytical techniques to detect anomalous patterns indicating inefficiencies or unveiling potential opportunities. Our approach leverages the capabilities of autoencoder architectures to delve into and understand the prevalent patterns in market behaviours. This analysis involves training the autoencoder on historical market data to learn the normal patterns and subsequently using it to identify deviations from these learned patterns. This allows for the detection of anomalies that may lead to operational or financial consequences. We elucidate the mathematical foundations of autoencoders, highlighting their proficiency in managing the complex, multidimensional data typical of the construction industry. Through training on an extensive dataset—comprising variables like market sizes, investment distributions, and project completions—our model demonstrates its ability to pinpoint subtle yet significant anomalies. The outcomes of this study enhance our understanding of deep learning's pivotal role in construction and building management. Empirically, the model detected anomalies in transaction volumes of lands and houses, highlighting unusual spikes that correlate with specific market activities. These findings demonstrate the autoencoder's effectiveness in anomaly detection, emphasising its importance in enhancing operational efficiency and strategic planning in the construction industry. [ABSTRACT FROM AUTHOR]

In this paper, we propose a comprehensive and optimised workflow for the documentation and the future maintenance and management of a historical building, integrating the state of the art of different techniques, in the challenging context of industrial archaeology. This approach has been applied to the hydraulic work of the "Sostegno del Battiferro" in Bologna, Italy, an example of built industrial heritage whose construction began in 1439 and remains in active use nowadays to control the Navile canal water flow rate. The initial step was the definition of a 3D topographic frame, including geodetic measurements, which served as a reference for the complete 3D survey integrating Terrestrial Laser Scanning (TLS), Structured Light Projection scanning, and the photogrammetric processing of Unmanned Aircraft System (UAS) imagery through a Structure from Motion (SfM) approach. The resulting 3D point cloud has supported as-built parametric modelling (Scan-to-BIM) with the consequent extraction of plans and sections. Finally, the Heritage/Historic Building Information Modelling (HBIM) model generated was rendered and tested for a VR-based immersive experience. Building Information Modelling (BIM) and virtual reality (VR) applications were tested as a support for the management of the building, the maintenance of the hydraulic system, and the training of qualified technicians. In addition, considering the historical value of the surveyed building, the methodology was also applied for dissemination purposes. [ABSTRACT FROM AUTHOR]

The selection of an appropriate construction method stands as a pivotal decision in ensuring the success of any building project. This paper undertakes a comprehensive comparative analysis of cost and timeline implications between the top-down and bottom-up construction methodologies. The research focuses on ten distinct underground structure models, each characterized by varying depths and base areas. Through rigorous design and analysis, the cost and projected duration for each model are meticulously evaluated under the lens of both top-down and bottom-up construction techniques. The findings reveal that while the bottom-up approach emerges as the most cost-effective alternative at a depth of 8 m, the top-down method exhibits superior cost efficiency with increasing depth. Interestingly, alterations in the structure's base area exert a minimal influence on the cost differentials between the two methodologies. Moreover, the top-down construction method consistently outshines its counterpart in terms of project duration across all ten models examined, with the percentage increase in base area yielding insignificant impacts on project timeline discrepancies. This study furnishes construction project managers with invaluable insights to navigate the complexities of method selection. By judiciously considering parameters such as project scale, depth, and base area, managers can strategically optimize both cost and timeline outcomes, thereby facilitating the seamless execution of construction projects. [ABSTRACT FROM AUTHOR]

The traditional project management in the construction industry has the uniqueness of exclusive customization, the irreversibility of the project, the immobility of the project address, the long-term nature of the project, and the dynamic nature of the project. Based on these characteristics, the complexity and difficulty of project management in the construction industry are determined. Modern engineering is no longer satisfied with the traditional basic needs, but develops in a green, environmental friendly and efficient way. On the one hand, the project is required to meet good use requirements and meet the most basic functional requirements. On the other hand, the project construction process is required to meet the requirements of green environmental protection and ecological harmony. Therefore, the maintenance cost and operation cost corresponding to modern projects have become the key to the sustainable and healthy development of the engineering construction industry. Based on this, this paper will take the construction industry as an example to fully analyze the current situation and existing problems faced by the current project cost management. Through the research on the full life-cycle project cost management mode of the construction industry, the random matrix weight algorithm is creatively introduced, and the adaptive full life-cycle project cost management extended target tracking algorithm is proposed, which cuts the corresponding full life-cycle project cost management model into multiple submodels, and the corresponding management subobjectives are constructed from the submodel, and the expansion status of the corresponding subobjectives is described and analyzed in detail using the inverse distribution description, so as to accurately estimate the effect and target weight coefficient required by the management subobjectives, and finally realize the efficient, reasonable and scientific operation of the construction industry's whole life-cycle project cost management, so as to maximize economic benefits. An experimental verification is carried out for a specific construction company. The verification results show that the full life-cycle project cost management scheme based on random matrix weight algorithm proposed in this paper has obvious advantages in management efficiency, cost control, process control, and other aspects compared with the traditional management scheme. [ABSTRACT FROM AUTHOR]

This paper analyzes the limitations of the current public management performance evaluation system, puts forward a public management performance evaluation model based on fuzzy clustering, and expounds on the theoretical framework and principle of this method. In addition, this paper introduces the concept and method of public management performance evaluation into the evaluation content system of government under the rule of law and realizes the combination of government under the rule of law theory and public management performance evaluation methodology. At the same time, through the analysis of the organizational system, technical system, institutional mechanism, result orientation, public satisfaction, and related index content, a public management performance evaluation index system is designed. Through macro and micro, qualitative and quantitative analysis and evaluation, the performance evaluation index system is improved, which provides an objective basis for forecasting and decision-making, control, and adjustment. The research shows that the highest accuracy of this clustering method can reach about 96%, and its accuracy is about 10% higher than that of the ID3 algorithm. It is expected that this research can make some contributions to the research of the public management performance evaluation index system. At the same time, it highlights the importance of research on performance evaluation of government ruled by law. [ABSTRACT FROM AUTHOR]

The global concern regarding the monitoring of construction workers' activities necessitates an efficient means of continuous monitoring for timely action recognition at construction sites. This paper introduces a novel approach—the multi-scale graph strategy—to enhance feature extraction in complex networks. At the core of this strategy lies the multi-feature fusion network (MF-Net), which employs multiple scale graphs in distinct network streams to capture both local and global features of crucial joints. This approach extends beyond local relationships to encompass broader connections, including those between the head and foot, as well as interactions like those involving the head and neck. By integrating diverse scale graphs into distinct network streams, we effectively incorporate physically unrelated information, aiding in the extraction of vital local joint contour features. Furthermore, we introduce velocity and acceleration as temporal features, fusing them with spatial features to enhance informational efficacy and the model's performance. Finally, efficiency-enhancing measures, such as a bottleneck structure and a branch-wise attention block, are implemented to optimize computational resources while enhancing feature discriminability. The significance of this paper lies in improving the management model of the construction industry, ultimately aiming to enhance the health and work efficiency of workers. [ABSTRACT FROM AUTHOR]

With the expansion of the scale of construction projects, the safety situation of construction projects has become more and more severe, and strengthening near-miss event management can effectively improve the safety management level of building construction sites and prevent safety accidents from occurring. However, the traditional monitoring and early warning systems rely on manual supervision, which is heavy and inefficient and cannot detect near-miss events in time. In the context of big data, blockchain technology, which is widely used, has the characteristics of decentralization, distrust, openness, nontamperability, and traceability, which can improve the safety of building construction sites to a certain extent. The primary objective of this study is to automatically monitor and early warn of near-miss events at building construction sites through the use of blockchain technology to effectively avoid the occurrence of building construction site safety accidents and reduce the incidence of safety accidents. To achieve this objective, we first constructed a knowledge base of near-miss events at building construction sites. Then, the near-miss event monitoring and early warning system for building construction sites based on blockchain technology was established. Finally, the near-miss incidents of not wearing safety belts working at height, which exists on the construction site, were used as an example to verify the feasibility and reliability of the monitoring and early warning system. The results show that the monitoring and early warning system has strong feasibility and practicability, and has certain research value. As the primary contribution, this paper developed a method of using blockchain technology for near-miss event monitoring and early warnings at building construction sites, which can realize real-time monitoring and automatic early warning, detect near-miss events in time, help trace the responsibility of events at a later stage, and improve the safety management level of building construction sites. This study suggests that blockchain technology can somewhat improve the safety management level of construction sites. This study developed a method for near-miss event monitoring and early warning at building construction sites by employing blockchain technology. The application of blockchain in the field of construction safety has attracted more and more attention, but the research on construction site safety is still in its infancy. With the continuous development and growth of the construction industry, construction site safety accidents occur frequently, but each accident is preceded by the occurrence of near-miss incidents. If near-miss events can be reduced and the management of near-miss events can be strengthened, the occurrence of safety accidents at building construction sites can be effectively reduced. In this paper, we introduce blockchain technology to secure data transmission and access using hash algorithms, realize timely warnings using smart contracts, verify and store data using blockchain data structures, and generate and update data using distributed nodes. By establishing a monitoring and early warning system for near-miss events at building construction sites based on blockchain technology, the occurrence of near-miss events can be effectively prevented and controlled, and the incidence of safety accidents can be reduced. [ABSTRACT FROM AUTHOR]

The integration of renewable energy systems in buildings leads to a reduction in energy bills for end users and a reduction in the carbon footprint of such buildings, usually referred to as prosumers. In addition, the installation of charging points for the electric vehicles of people working or living in these buildings can further improve the energy efficiency of the whole system if innovative technologies, such as vehicle-to-building (V2B) technologies, are implemented. The aim of this paper is to present an Energy Management System (EMS) based on mathematical programming that has been developed to optimally manage a prosumer building equipped with photovoltaics, a micro wind turbine and several charging points for electric vehicles. Capabilities curves of renewable power plant inverters are modelled within the EMS, as well as the possibility to apply power curtailment and V2B. The use of V2B technology reduces the amount of electricity purchased from the public grid, while the use of smart inverters for the power plants allows zero reactive power to be drawn from the grid. Levelized cost of electricity (LCOE) is used to quantify curtailment costs, while penalties on reactive power absorption from the distribution network are evaluated in accordance with the current regulatory framework. Specifically, the model is applied to a prosumer building owned by the postal service in a large city in Italy. The paper reports the main results of the study and proposes a sensitivity analysis on the number of charging stations and vehicles, as well as on the consideration of different typical days characterized by different load and generation profiles. This paper also investigates how errors in forecasting energy production from renewable sources impact the optimal operation of the whole system. [ABSTRACT FROM AUTHOR]

With the increasing number of construction sites in cities, construction dust, as one of the essential factors affecting the atmospheric environment, urgently needs more attention. Most existing studies have studied construction dust and other particle sources comprehensively. There remains a need for research on large-scale diffusion ultimately aiming at construction dust, especially studies on the diffusion law of dust generated only by construction dust at a large-scale city level where all construction sites within the city working at the same time. To systematically explore the diffusion distribution of construction dust in such a situation, this paper takes Xiamen as the research object and puts forward a large-scale construction dust diffusion research method by integrating emission factors and combining WRF and CALPUFF model. The spatial distribution of PM10 emission during the simultaneous construction of all sites in Xiamen in 2019 was simulated. The diffusion law of dust in large-scale construction in Xiamen is obtained. On this basis, the regional contribution of construction dust PM10 in various districts of Xiamen and the best start month of each district are obtained, which provides valuable suggestions for government construction control. This research method can be effectively applied to cities similar to Xiamen. [ABSTRACT FROM AUTHOR]

Based on the continuous development of Internet technology, the Internet has been fully applied in many fields. How can enterprises effectively use Internet technology to improve production efficiency, optimize the operating environment, and consolidate overall profitability? Combining the actual situation of enterprises with Internet technology has become one of the hot issues in the current society. With the increasing business volume of enterprises, the financial data generated by the data management system of enterprise financial department has become increasingly huge. At the same time, a large amount of financial data plays a vital role in the development of enterprises. In this paper, two data processing technologies, big data technology and data mining technology, are adopted to design and optimize the enterprise financial management model under the framework of Internet. It is very important and urgent to use data mining technology to realize the systematic management of enterprise finance, and it is also of practical value to study huge enterprise financial data based on data mining. In order to maintain sustainable development in the fierce market competition, enterprises must change the existing financial analysis work mode. Based on the theory of enterprise financial management under Internet information, this paper compares the factors affecting the financial management mode. Therefore, it is necessary to design the financial management model of enterprises. [ABSTRACT FROM AUTHOR]

The construction industry is a high-risk industry with many safety accidents. The popularity of Internet information technology has led to an explosion in the amount of data obtained in various engineering fields, and it is of necessary significance to explore the current situation of the application of big data technology in construction safety management. This paper systematically reviews 66 articles closely related to the research topic and objectives, describes the current status of big data application to various construction safety issues from the perspectives of both big data collection and big data analysis for engineering and construction projects, and categorically lists the breakthrough results of big data analysis technology in improving construction safety. Finally, the trends and challenges of big data in the field of construction safety are discussed in three directions: the application of big data to worker behavior, the prospect of integrating big data technologies, and the integration of big data technologies with construction management. The aim of this paper is to demonstrate the current state of research on big data technology fueling construction safety management, providing valuable insight into improving safety at engineering construction sites and providing guidance for future research in this field. [ABSTRACT FROM AUTHOR]

In civil and construction engineering education research, a focus has been on using 3D models to support students' design comprehension. Despite this trend, the predominant mode of design communication in the industry relies on 2D plans and specifications, which typically supersede other modes of communication. Rather than focusing on the presentation of less common 3D content as an input to support students' understanding of a design, this paper explores more common 2D inputs, but compares different visualization formats of student output in two educational interventions. In the first intervention, students document a construction sequence for wood-framed elements in a 2D worksheet format. In the second, students work with the same wood-framed design, but document their sequence through an augmented reality (AR) format where their physical interactions move full-scale virtual elements as if they were physically constructing the wood frame. Student approaches and performance were analyzed using qualitative attribute coding of video, audio, and written documentation of the student experience. Overall, results showed that the 2D worksheet format was simple to implement and was not mentally demanding to complete, but often corresponded with a lack of critical checks and a lack of mistake recognition from the students. The AR approach challenged students more in terms of cognitive load and completion rates but showed the potential for facilitating mistake recognition and self-remediation through visualization. These results suggest that when students are tasked with conceptualizing construction sequences from 2D documentation, the cognitive challenges associated with documenting a sequence in AR may support their recognition of their own mistakes in ways that may not be effectively supported through 2D documentation as an output for documenting and planning a construction sequence. The results presented in this paper provide insights on student tendencies, behaviors, and perceptions related to defining construction sequences from 2D documentation in order for educators to make informed decisions regarding the use of similar learning activities to prepare their students for understanding the 2D design documents used in industry. [ABSTRACT FROM AUTHOR]

The International Journal of Construction Education and Research (IJCER) is an academic peer-reviewed journal supported by the Associated Schools of Construction (ASC), publishing scholarly work associated with construction education and research. The purpose of this paper is to explore the increasing academic impact of the IJCER over the first 15 years of publication. This research included three principal objectives: first, evaluating the state of the IJCER with regard to commonly used academic impact metrics; second, defining the community of scholars IJCER most commonly associates with; and third, evaluating the role that the IJCER serves as a publication resource. This research demonstrated that the IJCER has become more comparable with top tiered construction management related journals based on academic impact metrics. The research further indicated that there is a large body of researchers that regularly contribute to ASC publications, including scholars from both research and non-research based institutions. The journal can continue to strengthen the academic impact by expanding collaborative efforts, establishing more external clustering relationships and visibility outside of the ASC, and ascertaining more of an international presence within the greater community of construction scholars. Ultimately, this research can be used help guide the future of the IJCER. [ABSTRACT FROM AUTHOR]