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Building projects as sub-sect of construction projects are complex and different in design and performance attributes. The prominent classes of building projects are high-rise residential buildings, hospitals, hotels, general offices, retail buildings/malls, educational institutions, and warehouses. In this study, building projects have been classified based on their end use. Complexities vary between construction projects and within various types of building projects, as well as across regions and countries. Understanding the sources of complexity is imperative to strategize their successful development. This research paper attempts to identify the sources of complexities using the design and performance attributes of seven prominent building types. A survey was conducted through experienced architects and construction professionals (the mean years of experience being approximately 13.88 years) over 34 different attributes or parameters under six categories. These attributes have been shortlisted from past research work by various authors, and the pilot study for this project. The Kruskal-Wallis Test was used to calculate the mean ranking and to confirm that the medians of each building type were not the same when compared against each attribute, irrespective of the level of complexity. Using data analysis and the mean ranking scores as a representation of relative complexity, primary sources of complexity in each class of buildings have been identified and listed. The results indicate that hospitals (as a building typology) are relatively the most complex building facilities in terms of design and performance attributes, showing the highest mean ranking towards 16 attributes (with only one shared ranking). Hospitals are followed by retail/malls (10 with one shared ranking), hotels (3), high-rise residential buildings (4), educational institutions (2), general offices (0), and warehouses (0). Strategies to manage these attributes have been proposed for each building typology so that the risks emanating from the complexities of these building projects can be mitigated and effectively managed at the design stage. [ABSTRACT FROM AUTHOR]

The construction industry continues to play a significant role in the economic development of most nations in the world. However, the construction sector still follows the 'linear' 'take–make–dispose' industrial model that, having benefited development, plays a major factor in the depletion of resources, environmental deterioration, and the generation of waste and pollution. In this regard, the adoption of a circular economy (CE) presents a compelling opportunity to address the challenges derived from the traditional linear economic model. This study attempts to scrutinise the critical success factors (CSFs) for implementing a CE via a mixed-method approach that combines both focus groups and an online survey. The adopted approach ensures a comprehensive identification and prioritisation of CSFs for implementing CE principles in building construction projects. The focus groups consisted of 20 key stakeholders drawn from prominent construction firms which included clients, consultants, contractors and designers. The outcomes from these focused groups led to the dentification of 43 CSFs, later categorised across different dimensions. Subsequently, an online survey was conducted to establish a priority list of the identified CSFs, using responses from 82 stakeholders to rate their level of importance. The top five significant CSFs include ensuring the use of standardised and warranted secondary materials, maintaining cost equivalence between a CE and linear approach, maintenance and operation cost minimisation, assessment of life cycle cost (LCC), and the enforcement of robust government regulations and policies that prioritise a CE. The Relative Importance Index (RII) was used to rank the identified CSFs following results obtained using the Statistical Package for Social Sciences (SPSS 27) and Excel for Microsoft 365. The findings of this study can inform the creation of decision support systems that could progress a CE across the construction project life cycle. [ABSTRACT FROM AUTHOR]

Effective waste elimination is critical for the success of construction projects. Although several studies have focused on various aspects of construction waste, limited efforts have yet to investigate the dynamic effect of Making-Do (MD) practices on productivity, rework, defects, and material waste. From a lean construction perspective, this study aims to address MD waste using the Last Planner System (LPS) and BIM. First, the causal structure that can cause MD in construction projects was expressed in a causal loop diagram (CLD), and thematic analysis uncovered the strategies of LPS-BIM to eliminate MD identified by reviewing the literature. Secondly, twenty-five strategies from the LPS and BIM strategies to address MD using structural equation modeling (SEM) were assessed. Subsequently, a system dynamics model (SDM) for investigating LPS-BIM strategies on MD decisions in a construction project was formulated based on the underlying causal loop diagrams and the mathematical relations among the variables. Finally, the model was applied to three projects, and simulations for four LPS-BIM scenarios were carried out. The findings show that dynamic interactions among diverse production planning and control factors are critical in evaluating MD impacts on a construction project. The results demonstrate that the LPS-BIM approach resulted in an average 43.8% reduction in the tasks performed with MD, 45.3% of constraints, 66.5% of construction waste, an increasing 13.7% completion rate, and a 29.3% cost reduction, demonstrating that LPS-BIM is a more efficient solution for MD mitigation and construction planning. This study aims to guide construction planners and policymakers to better manage their production constraints by eliminating negative MD practices from their plans. [ABSTRACT FROM AUTHOR]

With the rapid development of urban rail transportation, people's demand for subways has gradually manifested itself. The inherent complex attributes of subway project construction determine that subway project construction has a relatively high risk, resulting in huge losses. This paper takes the opportunistic behavior of the subway project as the research object, proposes the opportunistic behavior identification process, and constructs the opportunistic behavior identification model based on the BP neural network. Firstly, through the collection and analysis of subway accident cases, the main forms of opportunistic behavior are summarized, and the primary characteristic indicators for opportunistic behavior recognition are extracted using cluster analysis. Secondly, a recognition model based on a BP neural network is designed. The number of neurons in the input layer, hidden layer, and output layer of the model is determined, and the recognition model is subsequently trained and tested to validate its feasibility. Finally, the constructed opportunistic behavior recognition model is applied to an actual subway construction project, revealing that the construction enterprise of the project in question exhibits a high level of opportunistic behavior risk. Overall, the research results of this paper have important theoretical significance and practical value for the management level of subway project construction enterprises under the new situation and the identification and governance of opportunistic behavior of subway project construction enterprises. [ABSTRACT FROM AUTHOR]

This study was carried out to rank and prioritize the aspects that have been shown to have an impact on the improvement of construction project management (CPM) performance based on value engineering. This analysis was carried out with the Iranian construction industry's current situation in mind. The respondents and the Delphi panel were chosen from among Iranian managers and project management professionals with a focus on building projects. These professionals had more than 20 years of experience working on international projects, and in addition to their expertise in project management, they also understood the principles of earned value analysis and value engineering. Thus, the components extracted from the literature review were used as the basis for designing a structured interview based on 39 important effective components previously determined as identified factors. The questionnaires were distributed among the experts, and the returned questionnaires were analysed using the SWARA technique to rank the weight and importance of the factors. Using the SWARA method, the opinions of the expert panel members consisting of 20 engineers and a semi-structured questionnaire was used to gather expertise in project management and managers, with a focus on Iranian CPM. As shown by the results, stakeholder management, time value of money, and worth, allocated the first to the third rank to themselves with respective weights of 0.104, 0.103, and 0.087. The sub-criteria of cost objective, function objective, and value objective were in the 37th to 39th ranks with respective weights of 0.00050, 0.00033, and 0.00021. [ABSTRACT FROM AUTHOR]

Working at construction sites can harm individuals' health and well-being. However, stakeholders often focus on improving health while discounting well-being. Establishing a better workplace environment can improve workplace well-being. Therefore, this study aims to investigate the factors influencing workplace well-being in infrastructure construction projects. To achieve this aim, the study objectives are to (1) identify the critical factors influencing workplace well-being in infrastructure construction projects; (2) develop an interrelationship model between underlying constructs of the factors; and (3) assess the influence of the underlying constructs on workplace well-being in infrastructure construction projects. First, a list of factors influencing workplace well-being was established using data from a systematic literature review and semi-structured interviews. Then, a survey was developed using the list of factors and distributed to infrastructure construction practitioners. In total, 124 responses were retrieved and analyzed using normalized mean analysis, exploratory factor analysis (EFA) and partial least square structural equation modeling (PLS-SEM). The analyses reveal that the critical factors include workload, salary package, the timeline of salary payment, working hours, planning of the project, insurance for construction workers, workers' welfare and project progress. Furthermore, the underlying constructs are physical factors and psychosocial factors. Finally, both physical and psychosocial factors are found to significantly influence workplace well-being in infrastructure construction projects. Focusing solely on physical factors may not sufficiently enhance workplace well-being in construction projects, as there are also non-visible factors, such as psychosocial factors. Thus, exploring the interplay between visible and non-visible factors and their influence on workplace well-being in construction projects is crucial. Nevertheless, the findings have several limitations, including using data from a single country and non-hands-on construction practitioners, as well as the underlying constructs being derived solely using statistical methods. Still, the study is original in its focus on modeling the relationship between the factors influencing workplace well-being within the context of infrastructure construction projects. In other words, this study differs from prior research by specifically modeling the factors that influence well-being in infrastructure construction projects. [ABSTRACT FROM AUTHOR]

The paper investigates and assesses the contract selection procedure used in Kuwait's construction sector. The ideas and insights of engineers involved in significant Kuwaiti construction projects will be extensively considered. In the Kuwaiti building sector, various ways of choosing the contract form will be discussed. In order to gather pertinent data about the country's primary construction projects, questionnaires will be used. This methodology ensures a first-hand account of the challenges and preferences within the industry. This data will be analyzed to determine the best ways to enhance the current system utilized for Kuwaiti building contracts for the choice of contract forms and payment terms that could benefit from the inclusion of measures to guarantee those types of task delivery systems and payment terms in the country's future construction projects. This paper explores the typical contract types and payment mechanisms used in Kuwait, drawing on a thorough analysis of current literature, governmental regulations, and business practices. The Standard Forms of Contract, which offer fixed-priced payments, have become the most popular option. However, when used for extensive and technically challenging projects, this contract form's simplicity presents difficulties. Additionally, the existing system encourages contract awards based on the lowest tender, which raises questions regarding appropriateness and proportionality. The study suggests an arsenal of criteria for improving the deal selection process, with an emphasis on diverse terms of payment inside the task delivery system, in order to allay these worries. It highlights the need for a more comprehensive approach for deal selection that takes project complexity, financial constraints, and long-term project interest into account. The proposed criteria additionally include adaptability to project complexity, ensuring flexibility for challenges in large projects. Financial considerations, aligning with budgetary requirements, are crucial. The emphasis is on long-term project success, and finding a balance between simplicity and adaptability in contracts is key. These comprehensive criteria aim to improve decision-making in selecting standard contract forms for construction projects, addressing challenges in large, technically demanding endeavors in Kuwait. This research contributes to the field by introducing a novel set of criteria for contract selection, tailored to the Kuwaiti construction context. The study's originality lies in its approach to addressing the challenges posed by current practices and its focus on refining the system for future projects. Additionally, the study employs a rigorous questionnaire survey to extract firsthand insights from industry professionals, ensuring a robust and contextually relevant exploration of the contract selection landscape in Kuwait's construction sector. [ABSTRACT FROM AUTHOR]

This study addresses the critical need for standardizing building information modeling (BIM) execution plans (BEPs) in the architecture, engineering, construction, and operations (AECO) sector. Through the analysis of 36 BEP documents from international organizations, we have identified crucial components and put forth a comprehensive framework with the objective of improving digital transformation and collaboration in intricate construction projects. This study utilizes scientometric analysis to chart the development of BEP standards and incorporates empirical data from industry surveys to verify the suggested framework. The results of our research emphasize the advantages of using standardized building execution plans (BEPs) to decrease inefficiencies and enhance project outcomes. This makes a substantial contribution to the field of building information modeling (BIM) implementation. [ABSTRACT FROM AUTHOR]

With the rapid advancement in Building Information Modelling (BIM) technology to strengthen the Building and Construction (B&C) industry, effective methods are required for the analysis and improvement of as-built BIM, which reflects the completed building project and captures all deviations and updates from the initial design. However, most existing studies are focused on as-designed BIM, while the analysis and inspection of as-built BIM rely on labour-intensive visual and manual approaches that overlook interdependent relationships among components. To address these issues, we propose a network analysis-based approach for managing and improving as-built BIM. Networks are generated from geometric attributes extracted from Industry Foundation Classes (IFC) documents, and network analytical techniques are applied to facilitate BIM analysis. In addition, a practical dataset is utilised to verify the feasibility of the proposed approach. The results demonstrate that our method significantly enhances the analysis and comparison of as-built BIM from model analysis and matching. Specifically, the innovative contribution leverages global information and interdependent relations, providing a more comprehensive understanding of the as-built BIM for effective management and optimisation. Our findings suggest that network analysis can serve as a powerful tool for structure and asset management in the B&C industry, offering new perspectives and methodologies for as-built BIM analysis and comparison. Finally, detailed discussion and future suggestions are presented. [ABSTRACT FROM AUTHOR]

Characterized by long spans, low aspect ratios, and intricate construction sequences, super-large cross-section tunnels present substantial construction risks. Therefore, the selection of the optimal excavation method and construction sequence is crucial for ensuring the safety of tunnel construction and minimizing project costs. This paper takes a super large transverse-section highway tunnel as a case study, employing field monitoring data combined with ABAQUS software to analyze the stress and deformation of surrounding rock and support structures under different excavation methods. The findings reveal that the deformation of surrounding rock and support structures excavated by the Double-Side Drift Method is smaller than those caused by the three-benching seven-step method and the CRD excavation method. Nevertheless, the significant stresses of surrounding rock and support structures are released by the Double-Side Drift Method, leading to potential stress concentrations. Thus, it is necessary to ensure the rapid completion of early support and quick sealing of the tunnel. Furthermore, the sixth process achieves smaller deformation (including arch displacement and surface settlement) of the tunnel, a shorter construction period, and lower economic costs when compared to other construction processes. Consequently, it can obviously be concluded that both the Double-Side Drift Method and the sixth construction process stand out as the most appropriate choices for excavating super large cross-section tunnels. The insights obtained from this study provide theoretical guidance for the design and construction of similar tunnel projects. [ABSTRACT FROM AUTHOR]

The accurate distribution of joints on the tunnel face is crucial for assessing the stability and safety of surrounding rock during tunnel construction. This paper introduces the Mask R-CNN image segmentation algorithm, a state-of-the-art deep learning model, to achieve efficient and accurate identification and extraction of joints on tunnel face images. First, digital images of tunnel faces were captured and stitched, resulting in 286 complete images suitable for analysis. Then, the joints on the tunnel face were extracted using traditional image processing algorithms, the commonly used U-net image segmentation model, and the Mask R-CNN image segmentation model introduced in this paper to address the lack of recognition accuracy. Finally, the extraction results obtained by the three methods were compared. The comparison results show that the joint extraction method based on the Mask R-CNN image segmentation deep learning model introduced in this paper achieved the best joint extraction effect with a Dice similarity coefficient of 87.48%, outperforming traditional methods and the U-net model, which scored 60.59% and 75.36%, respectively, realizing accurate and efficient acquisition of tunnel face rock joints. These findings suggest that the Mask R-CNN model can be effectively implemented in real-time monitoring systems for tunnel construction projects. [ABSTRACT FROM AUTHOR]

Geotechnical engineering, being preliminary in any construction project, is of paramount importance for achieving sustainability. One of the important domains of sustainable development in geotechnics is sustainability assessments as it is essential to determine the impact of engineering activities on built environment. An indicator-based sustainability assessment tool called Geotechnical Sustainability Assessment Tool (Geo-SAT) was developed in this regard. The indicators used in Geo-SAT are generic in nature and judged on equal weightages, hence create skewness. Furthermore, the essentiality of these indicators varies across different projects and their life cycle stages. So, the tool requires scale normalization to remove this exaggeration of results. In current research 32 technical indicators are sampled out of 171 indicators of Geo-SAT using Delphi technique. The weightages of these indicators have been then normalized using Multiple Criteria Decision Analysis (MCDA). Multiple Attribute Value Theory (MAVT), a sub-technique under MCDA, is used for analysis as it compares between different criteria (i.e., project life cycle stages, indicators, and expert's opinion) and computes the weighted averages. For this purpose, a questionnaire has been developed and distributed among 52 relevant field experts having a predefined experience criteria set by authors, to record their opinion regarding the importance of indicators across project life cycle stages. 50 responses were accepted based on their reliability and completeness. As a result, the sustainability indices for all indicators are then calculated using MAVT based on weights of importance and relative weights attained from the questionnaires. Furthermore, it is established that the most critical indicators for the dam's sustainability assessment are "quality control during construction", "construction material wastage" and "feasibility reports", with highest weightages of 4.8%, 4.3%, and 4.2%, respectively. It is concluded that inculcating these computed weightages to Geo-SAT will increase the reliability and reduce the skewness in the sustainability assessment of dam projects. The current research is an effort to develop a sustainability assessment tool for dams (as no such assessment tool exists for dams exclusively) by improving Geo-SAT in terms of scale normalization. The normalized version of Geo-SAT, which is based on weighted averages of indicators, is a way forward for future development of certification system. [ABSTRACT FROM AUTHOR]

This review article examines global initiatives in the adoption of building information modeling (BIM) for road infrastructure. It begins with an overview of the distinctions between BIM applications for buildings and infrastructure projects. This study evaluates noteworthy BIM publications (NBPs) from various countries and organizations to understand BIM's transformative impact on roadway infrastructure projects. It analyzes the evolution of these publications, compares academic output with NBP, identifies the stages of BIM maturity, and evaluates adherence to ISO 19650 standards. Through this analysis, the article presents current global and regional scenarios, providing a comprehensive overview of the current state and future prospects of BIM implementation in the road infrastructure sector. [ABSTRACT FROM AUTHOR]

Construction projects require concurrent consideration of the three major objectives of construction period, cost, and quality. To address the multi-objective optimization issues of construction projects, mathematical models of construction period, quality, and cost are established, respectively, and multi-objective optimization models are constructed for different construction objectives. A hybrid optimization method combining an improved genetic algorithm (GA) with a time-varying mutation rate and a particle swarm algorithm (PSO) is proposed to optimize construction projects, which overcomes the shortcomings of the original GA and improves the global optimality and stability of results. Various construction projects were considered, and different construction objectives were analyzed individually. Finally, an uncertainty analysis is developed for the proposed GA-PSO algorithm and compared with GA and PSO. The results indicate that the proposed hybrid approach outperforms the PSO and GA algorithms in providing a better and more stable multi-objective optimized construction solution, with performance improvements of 4.3–8.5% and volatility reductions of 37.5–64.4%. This provides a reference for the optimal design of wind farms, buildings, and other construction projects. [ABSTRACT FROM AUTHOR]

The construction industry, a major player in economic development, is facing increased pressure to address sustainability concerns amidst rapid population growth and urbanization. With global projections indicating a significant rise in building demand by 2050, sustainability has emerged as a crucial focus area and paradigm shift to enhance environmental friendliness, quality, and project outcomes. The UAE, renowned for its vibrant construction industry, offers a unique context for examining the integration of sustainable practices. The use of sustainable construction practices is growing in the UAE, where the built environment plays a key role in economic growth and environmental stewardship. The United Arab Emirates (UAE) aims to foster long-term sustainability while enhancing the standard of living for current and future generations by integrating social, environmental, and economic aspects within construction projects, while also reevaluating conventional sustainable development frameworks and embracing a triple bottom line approach. This research was conducted to explore sustainable construction material usage and evaluation in the United Arab Emirates. The literature was reviewed for sustainable building construction materials across the UAE in the SCOPUS index from 2014 to 2024, as well as the regional regulations concerning the subject. This study evaluated the increasing trend of sustainable construction material research works, as well as the sound regional parameters of sustainable construction materials implemented across the country. Through an exploration of the significance of sustainable construction materials, this research underscores the multifaceted benefits of locally sourced, recyclable, and renewable materials in reducing environmental impacts, fostering economic and social well-being, and improving overall project performance and project management practices. The construction sector's role in economic development and its substantial environmental impact are discussed in alignment with sustainable construction materials, sustainable construction practices, and the need to enhance environmental sustainability and create healthier built environments. In the realm of sustainable construction materials, project management knowledge areas encompass a range of factors. These include the properties of materials sourced regionally; the incorporation of recycled content; considerations for indoor air quality, energy, and water efficiency parameters; and how these properties relate to project scopes, scheduling constraints, and challenges. Additionally, the availability of resources and competency levels, quality control standards, specifications, communication strategies, and stakeholder involvement play crucial roles. It is important to assess both the positive and negative risks associated with these elements across construction projects. [ABSTRACT FROM AUTHOR]

A large petrochemical construction project is typically executed by multiple parties, all bound by contract agreement. During the execution phase, issues and problems may arise because the work details are not clearly specified in the contractual agreement. These issues are formally communicated and documented through written correspondence letters. By identifying important keywords within these formal letters, a comprehensive narrative of the project, including its associated issues, can be identified and analyzed. In this research, we introduce an adjusted TextRank algorithm that integrates external features from the Indonesian FastText language model and term frequency-inverse document frequency (TF-IDF) scores to identify important keywords within a dataset of correspondence letters of petrochemical projects. This enhancement involves refining phrase detection, semantic relationship estimation between words, and part-ofspeech (POS) identification for words or phrases. Our results show that the proposed adjustments result in improved evaluation scores compared to the baseline standard TextRank and standard TF-IDF, respectively by 24.1% and 25% in terms of F-1 scores. [ABSTRACT FROM AUTHOR]

Abstract Building on the theories of social capital and self-determination as complementary perspectives, this study investigates how an individual’s idea of organizational social capital affects project success by testing a dual-stage moderated mediation model with self-efficacy as a mediator and transformational leadership as a moderator at both the first and second stages. Time-lagged data from 213 project management practitioners were collected from construction project–based firms. It was revealed that self-efficacy partially mediates the effect of an employee’s perception of organizational social capital on project success. Additionally, moderation results support the proposed hypotheses. We discussed theoretical and practical implications. [ABSTRACT FROM AUTHOR]

Selecting a suitable project delivery method is one of the most critical decisions responsible for project success in heritage conservation. This is an area where projects have greater uncertainties and governance issues in comparison to other building projects. India has a huge inventory of built heritage sites, but the heritage conservation sector is highly fragmented, with a wide range of project delivery methods. This paper discusses the selection of project delivery in the Indian context, using the theoretical lenses of agency theory, transaction cost economics (TCE), and institution theory. A conceptual framework has been proposed to explain the selection based on economical and institutional constructs. Our conclusion is that when institutional factors are weak, projects are executed departmentally or through non-priced contracts. In contrast, strong institutional forces discourage non-priced contracts and replace them with priced contracts. [ABSTRACT FROM AUTHOR]

The building sector is very dynamic and complex, so construction works are surrounded by uncertainties. The deficiencies of this sector are mainly related to poor project planning and management, resulting in losses because of missed deadlines, cost overruns, reworks, and unsatisfied clients. For a project to be successful, all the parties involved should work together to effectively manage the risks that could emerge in the project life cycle. This research defines and establishes a classification of the factors causing cost and time deviations in construction projects in the Dominican Republic. For this purpose, the most common factors are compiled, and their risk levels are determined by using the data obtained in a survey in which professionals from the building sector participated. The indexes marked by the participants show that the serious risk factors are design variations and the variations made by clients, a tight project schedule and the preparation of bid offers, deficiencies in the work planning and schedule, the lack of skilled labour, and work performance errors. [ABSTRACT FROM AUTHOR]

Industrial stakeholders have complained that current blockchain systems are too expensive, particularly in temporary endeavours like construction projects. However, while researchers have examined blockchain system structure among inter-firm organizations in construction, little research has considered the data redundancy of these systems. This research, therefore, provides insight by modelling data redundancy in construction project blockchain systems. We conduct a series of laboratory experiments on a Hyperledger Fabric blockchain system, discovering that the data volume of a blockchain system grows proportionally with the size of the files to be uploaded, the number of peer nodes in the network, and the frequency of blockchain operations in construction, regardless of the block size or how the peers are dispersed in different construction organizations. Beyond identifying the factors that determine data redundancy of a blockchain system, this research provides a basis for researchers to explore the optimization of blockchain storage and the impacts of blockchain system data redundancy in construction projects. In practical terms, the proposed data redundancy model in this research provides a reference for users in construction who aim to build blockchain systems. [ABSTRACT FROM AUTHOR]

This study delves into the design and deformation patterns of support structures in urban deep excavation projects, aiming to optimize the design of these structures to ensure their safety and stability. Initially, experimental research on steel-cement soil composite beams reveals their bending resistance and ductility under various loading conditions, confirming the effectiveness of the Soil Mixing Wall method in enhancing the stability of support structures. Subsequently, theoretical calculations using the method of elastic support points were conducted and validated through a deep excavation project in Xi'an, demonstrating that this method accurately calculates the trends of horizontal displacement in support structures. Additionally, FLAC3D numerical simulations are utilized to analyze the patterns of horizontal and vertical displacement during the excavation process. The simulation results generally align with the actual measured data, showing that the support structures optimized by the elastic support points method effectively control horizontal displacement (maximum displacement of 47.8 mm) and vertical displacement (maximum heave of 67.3 mm), validating the effectiveness of the numerical simulation methods. This research not only provides theoretical and practical guidance for deep excavation projects but also holds significant reference value for the design and construction of similar engineering projects. [ABSTRACT FROM AUTHOR]

AbstractThe Jakarta–Bandung High-Speed Railway has been widely seen as China’s signature Belt and Road Initiative project in Indonesia. To date, there is scant analysis of how risk has been managed throughout the project’s life cycle or of the dynamics of power relationships – the conflicts and compromises made between coalitions of the capitalist and political classes – that are intrinsic to China–Indonesia infrastructure co-operation. This article fills this gap by investigating how Chinese companies have managed risks by building alliances with dominant socio-political forces and state capital in Indonesia – designated here as “ex post risk management.” To explore this ex post risk management, this article applies Gramscian state theory and brings the conceptualisation of risk and social forces into dialogue. It contends that the understanding of risk and risk management are contingent upon negotiated compromises between different social forces – state capital, internationalised state apparatuses, and industrial capital – that are bound via infrastructure financing and other ongoing industrial and construction projects in Indonesia. These interactive dynamics have resulted in the institutionalisation of risk through and within the state that derides the social foundation of Indonesia’s current infrastructure regime. [ABSTRACT FROM AUTHOR]

Virtual models have the potential to transform architectural design processes by introducing a novel form of participation of project stakeholders. With the concepts of material participation and digital materiality, this research shows how virtual models in meetings called ‘virtual safaris’ set up a space for participation by providing a tangible architectural demonstration. In virtual safaris, virtual models allow participants to imagine and co-design their experience in the future space instead of trying to interpret architectural plans, resulting in more detailed and concrete feedback. Based on observed virtual safaris and interviews, we categorised the participatory aspects of virtual models and safaris into technical features of the virtual models, experiential features of virtual safaris, and organising and arranging virtual safaris. We consider these categories as intertwined, specifying aspects of material participation. They highlight both the complexities of actual usage of virtual reality in co-design and the additional value of virtual safaris as a participatory setting. We conclude that ways of organising and arranging virtual safaris are central for achieving the transformation potential of virtual reality. We also highlight crucial aspects of meetings utilising virtual reality for practitioners and researchers in construction projects. [ABSTRACT FROM AUTHOR]

Developments in concrete technologies have allowed engineers to design lightweight, slender, and aesthetically attractive structures. The application of new concrete types in real projects, however, is uncommon. The lack of regulation, uncertainty in material performance, and the absence of successfully implemented projects hinders the use of modern concretes in everyday design projects. The present paper examines the application of two specific concrete types in a prototype footbridge: ultra-high-performance concrete (UHPC), and biological self-healing concrete (BSHC). The material properties of UHPC were selected and tailored specifically for the prototype structure, applying the principles of performance-based design. To evaluate the efficiency of self-healing under real environmental conditions, BSHC beams were designed as a structural part of the bridge. The step-by step presentation of the bridge development demonstrates the specifics in material design and a structural analysis of the prototype structure. The prototype structure serves as demonstrative example of the use of BSH and UHP concretes, encouraging engineers towards the wider application of advanced materials in construction projects. [ABSTRACT FROM AUTHOR]

Construction materials are at the forefront of global economic development as they provide the foundation for the infrastructure of other industries, with cementitious materials being predominantly used in construction projects. To promote sustainable development, alternative materials are added to cement mortar to increase durability and reduce emissions. In this regard, graphene oxide (GO) and fly ash (FA) are two alternative materials commonly used in cement mortar, which are readily available or are just the waste from other local material production. With different ratios, the amount of GO and FA can affect the properties of cement mortar positively or negatively. This study aims to determine the effects of GO and FA on cement mortar mixtures under material conditions. Research results show that 10 wt% FA and 0.036 wt% GO will give cement mortar the best physical and mechanical properties while ensuring other necessary properties, such as workability. When increasing FA to 30 wt% or GO to 0.05 wt%, the strength of the mortar mixture tends to decrease. Another issue is that the specific surface area of graphene is very high, which poses a significant challenge when uniform dispersion in the cement paste mixture is required. Polycarboxylate combined with a specific mixing sequence has demonstrated good dispersibility and high stability. Through this research, it is demonstrated that the addition of GO and FA has the potential for sustainable development of the construction industry by considering the contexts of the local recycled cementitious replacement materials. [ABSTRACT FROM AUTHOR]

This article aims to present the construction of a project called Feminist Futsal. Based on the experiences of female futsal coaches, this study aimed to analyze and reflect on some of the situations in which feminism was present throughout futsal seasons. For that, five specific moments were selected from field diaries: ‘The construction of the Feminist Futsal Project’; ‘The first season’; ‘Where is “Feminism”?’; ‘The second season: The uncertain path persists’ and ‘Seeds that have already been planted’. Many questions and challenges were encountered, such as how can we address important social issues and connect them to the planning of a futsal training session that does not directly deal with these topics? Do you need to link critical issues directly to the theme of the futsal training session? Where is Feminism? As a result, it was identified that feminism in the project gave women the opportunity to practice a sport, as well as the presence of a female coach; feminism was, also: in the reflections shared in the initial training sessions; in the learning community established with the research group; in the athletes sharing of knowledge with the project. In addition, feminism was at the heart of the project’s belief that men and women should have equal opportunities to participate in sports, paving the way for a fairer world. Feminism was there, facing the risks. Feminism is in the courage to put that name to a sports project. I do not know what the future holds for Feminist Futsal, nor do I have all the answers for other sports projects that might look to us. What I do know is that love and the courage to change how we view the world are the driving forces behind this project. And yes, we are already revolutionizing it. [ABSTRACT FROM AUTHOR]

Translation abstract Novel 3D Reinforcements for Concrete Structures – Part 1: Background, Development, and PotentialFacing the challenges in the construction industry, especially the pursuit of sustainability and material efficiency, this article explores the development and potential of an innovative three‐dimensional (3D) and fully automated carbon fiber reinforcement structure, known as “Mesh”. This advanced method of reinforcement offers a versatile and resource‐efficient alternative to conventional steel reinforcement and an expansion of currently used carbon grids/elements. The Mesh is characterized by its adaptability to various shapes and load paths, significantly reducing the need for concrete and reinforcement, thereby enhancing the longevity and ecological footprint of construction projects. The development of the Mesh, from initial exploratory tests to its current status, as well as possible applications, including its potential as shear, surface, split tension, or helical reinforcement, especially in prestressed components, are discussed. This contribution highlights the Mesh′s contribution to the advancement of reinforcement technology in concrete construction and is part 1 of a multi‐part publication series. [ABSTRACT FROM AUTHOR]

Any organization linked with construction needs to apply suitable standards, procedures, and structures to support the right acts by all the involved construction structures that are related to health and safety. This paper evaluates the safety management procedure of building construction projects by rating the importance of safety management factors and calculating the average practice. This has been done by conducting a case study of (94) projects constructed during 2013-2023 by designing a questionnaire that represents a successful plan of 49 factors of seven phases for a safety management system. And delivering it to stakeholders who worked on those projects. The results of the study show that the average practice of safety management is 61.27%, which is unacceptable. The typical safety management process falls between 37.54% for initial planning and 79.93% for precautions before scaffold implementation. The results revealed that the shortage in practicing safety management stages is noticeable in all building construction projects, especially for initial planning with a rate of practice of 37.54%, and the use of personal protection equipment with a rate of practice of 47.41%. There is a lack of practicing safety procedures. A team for emergency issues is rarely available in addition to the shortage of first aid centers. There are not enough medications in case of accidents. Also, the workers are not using suitable protection equipment often. There must be an emphasis on the issue of safety management in future construction projects. [ABSTRACT FROM AUTHOR]

Mega construction projects (MCPs) have long periods, complicated environments, a multiplicity of mechanical equipment and personnel, and a large number of safety risk factors on sites. The different safety risk factors of MCPs have coupling effects among them, which can produce new risks and even lead to an accident. These factors present a major challenge for project managers to take on risk management in MCPs. Although previous research has done much work on risk factor identification and control in MCPs, less attention has been given to the coupling effects among risk factors, which affect the identification effect of key safety risk factors and their coupling paths. To compensate for this gap, this research used the latent Dirichlet allocation (LDA) topic model to identify risk factors in mass accident reports, the N-K model to calculate the coupled style, and then coupled the N-K model and the social network analysis (SNA) model to identify the safety risk factors and determine the coupling paths in MCPs. The results reveal the following: (1) six first-level subsystems are identified, and there are 31 second-level safety risk factors included in MCPs; (2) H1 (low safety awareness), H2 (CAT operation), H6 (improper safety protection measures), P4 (improper safety supervisors), P5 (imperfect management system), S3 (owner's mistakes), and M2 (improper maintenance of equipment) are the key safety risk factors in MCPs; and (3) unfavorable environmental factors can easily lead to the emergence of the multirisk coupling of G-S-P-H-M-E , which should be carried out by special management. This research provides a reference for the identification and control of safety risks in MCPs and contributes to the development of complex system risk management and control research. [ABSTRACT FROM AUTHOR]

This study presents a method for estimating construction costs, even when dealing with limited and unreliable data, to enhance decision-making in the early project stages. Owners, particularly in green building projects, often face challenges due to the scarcity of usable data, making cost estimation a complex task. They struggle to differentiate between costs associated with existing buildings and green buildings. To address this issue, we introduce a novel approach that leverages conditional tabular generative adversarial networks (CTGANs) for data augmentation, overcoming the limitations of relying solely on historical data. This involves training an artificial neural network (ANN)–based model using synthetic data, effectively addressing the scarcity and imbalance present in the original small data set. Compared to models trained exclusively on the original data set, our approach yielded a remarkable reduction of approximately 66% in root-mean-square error (RMSE), while increasing the validity from 0% to 15.09%. This study not only improves construction cost estimation but also facilitates more informed decision-making for owners, even in cases with limited and unreliable data, ultimately contributing to the efficiency of the construction project planning process. [ABSTRACT FROM AUTHOR]

Construction waste causes severe environmental problems. Reducing construction waste generation becomes a major policy measure of governments to achieve sustainable development. Offsite construction approaches are effective for reducing onsite construction waste. Nevertheless, there is a lack of a clear understanding of the types and amounts of construction waste that different offsite construction approaches can reduce. This study aims to investigate the performance of the modular construction (MC) approach in construction waste generation and reduction and how it differs from that of the nonmodular offsite construction (NMOC) approaches by comparing 59 selected cases of building projects that adopt these offsite approaches compared with stick-built construction. Results indicated that the adoption of offsite construction contributed to significant onsite construction waste reduction. On average, adopting MC reduced 78.8% of overall construction waste, outperforming other construction approaches. The level of prefabrication influenced onsite construction waste generation and reduction the most, followed by the other properties like building typology, density, and material used. Seven knowledge gaps were identified in the area of waste identification, quantification, and assessment. The findings demonstrate the advantages of using offsite construction in waste control and management and add to the existing body of knowledge on onsite construction waste generation and on waste reduction through adopting MC. The identified knowledge gaps point directions of future research on waste reduction through offsite construction. Practical Applications: The results of this paper suggest that the adoption of offsite construction can contribute to significant onsite construction waste reductions compared with conventional stick-built construction. Specifically, buildings adopting the modular construction (MC) approach can reduce overall construction wastes by around 80% and outperform other nonmodular offsite construction approaches, including those that adopt one-dimensional prefabricated beams and columns, two-dimensional prefabricated panels, or three-dimensional prefabricated pods, based on the analysis of 59 building cases covering different levels of prefabrication, building typologies, building densities, and building materials. This study contributes to the investigation of onsite construction waste by proposing a systematic assessment method addressing different construction waste types and assessment criteria. It facilitates a better understanding of the advantages of offsite construction in terms of waste control and management, especially MC, which was underexplored in the literature. Seven knowledge gaps were identified in the area of construction waste identification, quantification, and assessment. Addressing these knowledge gaps will contribute to better construction waste control and management, especially in MC projects. [ABSTRACT FROM AUTHOR]

The water diversion project in Central Yunnan Province (WDP-YN) is the largest water diversion project under construction in China. However, the ecological effects of this water diversion project are still unclear. This study utilized Sentinel-2 remote sensing data to estimate fractional vegetation cover (FVC), maps spatiotemporal variations of FVC in construction areas from 2017 to 2022, and evaluates the impact of the WDP-YN on regional vegetation coverage using buffer analysis and vegetation type transition matrix methods. The study led to the following findings: (1) From 2017 to 2022, FVC within 10 km of the tunnel construction route showed a slightly downward trend or remained relatively stable with no significant changes in the spatial pattern of FVC. (2) Before and after the construction of WDP-YN, over 60% of the area within 10 km of the tunnel construction route showed no change in FVC. On Construction Route Section I (CRS-I), vegetation improved and/or degraded within 12.90% (14.10%) of the area and the regions with degraded FVC concentrated in the northern CRS-I. For Construction Route Section II (CRS-II), 11.96% and 27.51% of the regions were dominated by improved and/or degraded FVC. Vegetation changes near Groundwater Monitoring Point a (GMPa) were relatively stable. (3) The WDP-YN degraded vegetation within 2 km of both sides of CRS-I, slowing down the increase in FVC, while the WDP-YN improved vegetation within 2–6 km of both sides of CRS-II, the closer the distance to CRS-II, the faster the increase in FVC and the decrease in FVC slowed down within 0–2 km of both sides of CRS-II. This study sheds light on the impacts of water diversion infrastructure on vegetation coverage and provides practical guidance and reference for eco-environment protection and ecological restoration given water conservancy projects in China and other regions of the world. [ABSTRACT FROM AUTHOR]

Using a case study of the early sixteenth-century rebuilding of the London parish church of St Andrew Undershaft, this article focuses on the hitherto unrecognised role played by the executors of London mercantile testators in pre-Reformation church building. Drawing on the rare sets of extant accounts kept by executors in the course of their duties (which would once have been ubiquitous), the details of several ecclesiastical rebuilding projects can be revised, including that of St Andrew's. It will be argued that this realisation possesses important implications for our understanding of late medieval ecclesiastical building projects, and that executors—sometimes acting on the instruction of the testator but also (more significantly) on their discretion—should be considered a profoundly influential force in shaping the infrastructure of the pre-Reformation City. [ABSTRACT FROM AUTHOR]

Sustainable and environmentally friendly construction is the way of the future for building projects, and it is a practical illustration of how sustainable development is being implemented in the construction sector, where the control objectives are interdependent and constricting. However, when green construction is carried out, a conundrum arises since important factors like cost, environmental preservation, and safety cannot be addressed simultaneously. This issue limits the promotion of green construction. In order to solve the obstacles in the green construction process, the study chose to introduce three objectives to establish a multi-objective optimization model for project optimization. The local search idea in the mountain climbing algorithm was introduced into the non controlled sorting genetic algorithm to improve it, and a green construction multi-objective optimization model was established. Experimental verification of the feasibility and efficiency of improving non controlled sorting genetic algorithms; And evaluate and solve the established sustainable construction project. The results represent the maximum optimization values for each objective. The construction period is mainly distributed between 183–245 days, the cost distribution is between 16.6855 million yuan and 200861 million yuan, the quality distribution is between 0.864 and 0.878, the safety distribution is between 0.874 and 0.999, the environmental distribution is between 133.76 and 190.72, and the resource distribution is between 0.834 and 0.999, all of which meet the standards. Provide theoretical solutions for managers to manage green construction projects. [ABSTRACT FROM AUTHOR]

Emergency material security is the key to post-disaster emergency relief in complex environment engineering construction projects. Aiming at the emergency logistics center site path planning problem, the uncertain parameters of congestion time and maximum rescue time are described using trapezoidal fuzzy numbers, and the emergency logistics site path model of the two-phase engineering construction project is established. A quantum particle swarm optimization model is designed to avoid premature population convergence and maintain population diversity. The particle swarm algorithm uses the quantum spin gate's rotation angle update to represent the particle velocity update. Taking the engineering construction project in the western mountainous area as an example, the validity and applicability of the model are verified through model comparison and sensitivity analysis. The results of the example show that in the complex environment, the quantum particle swarm algorithm takes 29.35 s in convergence time, and the particle swarm algorithm takes 40.12 s, which is 36.69% higher than the efficiency of PSO. In total cost, the quantum particle swarm algorithm has a total cost of 46,632.40 RMB, and the particle swarm algorithm has a total cost of 48,319.51 RMB, which is 3.62% lower than the cost of PSO. The quantum particle swarm algorithm's total distance is 550.57 km, and the particle swarm algorithm's total distance is 579.35 km, 5.23% lower than the total distance of PSO. The model established in this study can scientifically select the location of emergency facilities and formulate the emergency rescue path, reduce the response time of emergency rescue and storage costs, and provide decision support for the scheduling of emergency supplies for engineering construction projects in complex and dangerous areas. [ABSTRACT FROM AUTHOR]

The rapid urbanization of Metro Manila led to a surge in condominium construction projects, which, despite offering efficient housing solutions, faced significant challenges due to dense urban environment, susceptibility to natural disasters & the health and safety issues related to accidents, losses, injuries, damages, and/or delays arising during the execution of a project which may adversely affect its success. This study explored the efficacy of the Analytic Hierarchy Process (AHP) in assessing and prioritizing risks specific to Metro Manila's condominium construction projects, addressing a critical gap in current risk assessment methodologies. The study engaged mixed methods, integrating Meta-Analysis, Experts Consultation, and AHP, to identify and prioritize Risk Factors (RFs) in condominium construction projects. A systematic review through meta-analysis revealed nine critical RFs, including Technical/Design, Financial/Economic, Environmental, Regulatory/Legal, Socio-Political, Logistics/Supply Chain, Management/Supervision, Quality, and Health and Safety Risks. Inputs from experts from a diverse group of qualified professionals had been pooled to validate these findings. Through AHP analysis, risks specific to Metro Manila's condominium construction projects were revealed, with Health and Safety Risk (19.52%), Quality Risk (15.97%) and Management/Supervision Risk (15.77%) as the major concerns. An internal consistency of 0.71% attested to the reliability testing of the results. Given the complexity of condominium construction projects, this study responds to an important demand: a more systemic understanding of risk factors. Moreover, this study is relevant to further enhance and improve sustainability in condominium projects as well as performance of the construction industry. [ABSTRACT FROM AUTHOR]

This research addresses the gap in comprehensive predictive models for construction project success rating by exploring the potential of regression models to evaluate project success rating. By analyzing 130 datasets from the National Capital Region, the study utilizes Support Vector Regression (SVR), Multiple Linear Regression (MLR), and Artificial Neural Network (ANN) with a 22-30-1 configuration (22 input neurons, 30 neurons in a single hidden layer, and 1 output neuron). The input variables represent critical success factors rated on a scale of 1-5, while the output variable represents the predicted project success percentage rating. Various statistical tools, including ANOVA, Lasso Regression, R², MAE, and MSE, are utilized for evaluation. The findings reveal that SVR achieved the highest accuracy (R² = 0.881, MAE = 2.172, MSE = 7.054), followed closely by MLR (R² = 0.874, MAE = 2.180, MSE = 7.470), while ANN (R² = 0.743, MAE = 3.076, MSE = 15.239) may require refinement. Lasso Regression identified 22 critical success factors, with Financial Condition, Effectiveness in Decision-Making, and Compliance to Quality Standards ranking as the top three. This research contributes to the advancement of construction predictive analytics, which can lead to improved decision-making and more efficient, effective, and ethical construction practices. [ABSTRACT FROM AUTHOR]

International Construction Joint Ventures (ICJVs) offer benefits to both local and foreign partners. However, their failure rates tend to be high, leading to poor ICJV performance. Effective Project Management (PM) is considered a means to resolve challenges in a construction project. Therefore, this research aims to address the challenges in ICJV projects within the Sri Lankan construction industry through PM practices to establish successful ICJVs. The research adopted a mixed-method approach. A preliminary survey was conducted to validate the challenges in the Sri Lankan context. After that, challenges were ranked based on their significance level using the Relative Importance Index (RII) method through a questionnaire survey. Then, Semi-structured interviews were conducted to identify the PM practices that can address significant challenges through code-based content analysis. The study revealed 38 challenges applicable to ICJVs and identified 88 PM practices for resolving 10 significant challenges out of the 38 identified in ICJV projects in Sri Lanka (SL). Finally, a framework was developed for successful ICJVs by addressing challenges through PM practices. This study marks the first attempt to establish a framework for successful ICJVs by addressing challenges through PM practices in the Sri Lankan construction industry. [ABSTRACT FROM AUTHOR]

A review analysis of a database of 237 small strain stiffness measurements performed on 35 different residual soils is presented. The reinterpretation of the tests was conducted with respect to the loading conditions and physicochemical parameters published in the literature. Besides, the database was completed with the results of a case study from a dam construction project in the French West Indies. On the basis of a detailed and carefully justified analysis, parameters influencing the response of saturated residual soils to small strains are identified, is proposed. The correlations between the identification characteristics of the residual soils (initial void ratio, Atterberg limits, clay fraction) and the model parameters are investigated. The article proposes a general model for the evaluation of the small-strain stiffness of saturated residual soils using, in addition to the mean effective stress (p') and the maximum mean effective stress (p'max) the initial void ratio (e0) and, for intact soils, the clay fraction (CF) or, for remoulded soils, the plasticity index (PI). [ABSTRACT FROM AUTHOR]

This study focuses on an important issue of the mental health of white-collar construction workers, a concern that has grown more serious following the COVID-19 pandemic. Therefore, the purpose of this study is to investigate the factors that influenced the mental health of the white-collar construction workers during the COVID-19 scenario. Based on the review of extant literature, a survey questionnaire was developed and distributed online to Indian professional construction workers, 206 responses were received, and a data set was prepared for further analysis. The data set was analyzed using exploratory factor analysis, and second-order confirmatory factor analysis and distinct stressors were identified. The most critical were lack of upskilling challenges (SFL=0.85) and workplace-related issues (SFL=0.85), followed by financial constraints (SFL=0.76) and family-related problems (SFL=0.44), both having a moderate impact. The results of the study were used to design a stress management matrix that recommends practical strategies to minimize work-related stress. By aligning with the UN Sustainable Development Goals, this research contributes to enhancing worker wellbeing and enhanced productivity of construction workers. [ABSTRACT FROM AUTHOR]

Project bundling is a method used by state Departments of Transportation (DOTs) and other public agencies to combine multiple construction projects into a single contract. Project bundling is typically applied when the projects share similarities in terms of type, size, and geographical location. Prior research has demonstrated cost savings and accelerated project delivery times due to this approach. However, little-to-no previous research efforts have particularly focused on developing a comprehensive guidance strategy for project bundling of various transportation projects. This paper aims to address this knowledge gap by identifying the best practices of project bundling that enable state DOTs to implement project bundling more efficiently. To achieve this goal, empirical evidence was gathered through semistructured interviews and follow-up correspondence with 16 representatives from different state DOTs and a local public agency. These interviews gathered insights into the methods and strategies used by different state DOTs to successfully bundle projects. For instance, the study discovered that agencies utilize different bundling strategies (for instance, optional-tie or mandatory-tie), as well as bundling approaches (scope-based or location-based). By qualitatively analyzing the success stories and lessons learned from these interviews, the study provides a comprehensive strategy that serves as a guide for state DOTs in navigating the project bundling for different construction projects. The main contribution of the study is the synthesis of the project bunding practices, which allows state DOTs and other transportation agencies to have a holistic approach to implementing project bundling to reap its maximum benefits. [ABSTRACT FROM AUTHOR]

In construction projects, when resources assigned to two or more simultaneous activities share the same workspace, they generate time-space conflicts associated with congestion, safety, and quality issues. The use of building information modeling (BIM) methodologies, particularly four-dimensional (4D) models, offers the possibility to facilitate the identification of these types of conflicts. Existing literature has proposed formal methods for conflict detection; however, these largely focus on automating computational analyses without providing a practical and useful procedure for planners. Moreover, previous research has not evaluated the impact of using formal conflict detection methodologies. To address these gaps, this study proposes and evaluates the use of a formal conflict detection methodology in workspaces based on 4D-BIM. The research methodology includes a first stage that develops and validates the formalized conflict detection methodology through a literature review and interviews with field professionals. The second stage quantifies the impact of using the proposed methodology through an experiment that compares the effectiveness and efficiency of a group of planners in detecting conflicts using 4D-BIM models with and without the proposed methodology. The results demonstrate that the formalized methodology enhances the planning process by increasing the detection of conflicts from 18% to 82%. Additionally, the formalized methodology reduces review time by 23% and enhances user experience. These findings contribute to improving the planning process by managing and reducing time-space conflicts in construction schedules. Consequently, the construction process will become more efficient by averting issues related to productivity, safety, and quality based on the identification of workspace conflicts. Last, the proposed methodology contributes to a better adoption of BIM by providing a structured procedure for using the 4D-BIM model to support planning processes. Practical Applications: This study lays the groundwork for companies aiming to enhance their conflict detection processes and refine planning and conflict management procedures. The practical contributions include achieving greater effectiveness and efficiency in identifying conflicts in workspaces. The proposed formalized methodology enhances productivity, reduces safety-related risks, and prevents quality issues in building projects by managing and mitigating time-space conflicts in construction programs. Additionally, the research contributes to the enrichment of BIM application in construction activity planning. It formalizes the use of BIM through a conflict detection methodology, particularly in the analysis of construction programs and the identification of workspace conflicts. The results further strengthen the application of the BIM methodology by facilitating the design of BIM processes associated with planning, incorporating the methodology proposed in this research. Furthermore, the study encourages the adoption of BIM in construction activity planning by evaluating the positive impact of the proposed formalized methodology, providing evidence for its implementation in organizations and highlighting its potential benefits in terms of effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

The construction industry suffers from frequent and expensive safety accidents, significantly affecting construction project performance. Numerous data-driven classification models have been developed to categorize construction accident outcomes. While critical influencing factors provide insights for safety prevention, existing models have given less attention to the cost of accidents—an important indicator influencing management decisions. This study aims to develop accident cost prediction models that examine crucial precursors of safety accidents, offering guidance for construction safety prevention from a financial perspective. This study collected 1,606 accident reports from the Chinese construction industry between 2005 and 2022 to address this gap. Three ensemble data-driven methods, namely random forest, extreme gradient boosting regressor (XGBoost), and natural gradient boosting regressor (NGBoost) were employed to develop accident cost prediction models. Based on the performance comparison, the random forest regression model for accident cost was determined to be the best prediction model. To extract the critical attributes affecting safety accident costs, this study utilized shapely additive explanations (SHAP) value to analyze the sensitivity and influence of input variables of data-driven models. The findings showed that collapse has the greatest impact on accident costs, as indicated by the highest mean SHAP value, followed by falling from height. Furthermore, factors such as year, safety supervision, drawing, and construction plan are noteworthy in affecting accident cost prediction. Safety department, protection, and work conditions hold a slightly higher degree of influence compared to contracting arrangement, safety culture, safety supervision, training and examination, and mechanical equipment on the model output. This study provides a dimension that might be overlooked in the investigation of safety accidents in the construction industry and the insights provided by findings will contribute to the development of targeted safety accident prevention strategies. [ABSTRACT FROM AUTHOR]

Road and highway construction projects are often a concern among surrounding communities as these projects possess significant risks to the environment, and their impacts can reach far beyond the project areas. Monitoring the environmental management plan (EMP) implementation of road and highway construction projects is challenging as it requires a high level of human resources. Thus, allowing the public to assess and report any potential misconduct in road and highway construction projects can help monitor EMP performances. This study aims to compare key performance indicators (PIs) for assessing EMP implementation in road and highway construction projects. To achieve the aim, the study objectives are to (1) determine the key PIs for road and highway construction projects, (2) develop underlying components that categorize interrelated PIs, and (3) compare the underlying components between road and highway construction projects. To achieve those objectives, this study first develops a questionnaire survey by conducting a systematic literature review and semistructured interviews with industry professionals. Throughout the process, 39 PIs for assessing EMP performances have been identified. Then, a questionnaire survey was developed using the PIs and distributed to environmental professionals, collecting 111 valid responses. Finally, the data for the study were analyzed using mean score ranking, factor analysis, and agreement analysis among the two project types. This study has identified 18 and 21 key PIs for assessing EMP implementation in road and highway construction projects. The key PIs can be categorized under four underlying components for both types of construction projects: geological, pollution, environmental change, and ecological for roads, and pollution, ecological, public safety, and geological for highways. This study adds to the environmental management literature by comparing potential PIs for road and highway construction projects, potentially helping policymakers and industry practitioners develop public assessments for EMP implementation of road and highway construction projects. [ABSTRACT FROM AUTHOR]

Construction projects inevitably encounter adversities that threaten their functionality and performance. Understanding the enhancement of project resilience, especially in extreme situations like the COVID-19 pandemic, is crucial. This study introduces a theoretical model to explore how partnering and boundary activities among project stakeholders influence project resilience, and in turn, impact project performance. Based on data gathered from a questionnaire survey involving 172 construction projects in China, the results indicate that project resilience directly and positively affects project performance during the COVID-19 pandemic. Partnering and boundary activities emerge as primary determinants of project resilience. They not only directly impact project resilience and performance, but their impact on project resilience also indirectly influences project performance. The findings offer valuable theoretical and practical insights into the improvement of project resilience through effective boundary activities and partnering. [ABSTRACT FROM AUTHOR]

This study is part of a master plan by Thailand's Department of Rural Roads to design new bridge and road construction projects across 37 provinces in the North and Northeast regions. Potential sites were evaluated based on physical accessibility and environmental factors, considering eight criteria including slope, road density, distance from existing bridges, accessibility to educational institutions, workplaces, tourist sites, hospitals, agricultural areas, and villages. Using multi-criteria decision-making (MCDA) and the Analytical Hierarchy Process (AHP) within a GIS framework, we assessed origin-destination trips to identify optimal sites for new bridges and roads. Initially, 1,534 potential bridge locations were identified and evaluated using AHP to determine the relative importance of each factor. The GIS-based MCDA process enabled effective spatial data analysis, refining the sites based on environmental constraints and proximity to existing structures. Ultimately, 185 suitable locations for bridge construction were selected, including 98 sites in Northern Thailand and 87 in the Northeast. The study demonstrates the effectiveness of combining AHP and MCDA within a GIS framework for infrastructure planning. It underscores the importance of integrating multiple criteria to achieve sustainable and efficient development. The findings offer a robust framework for policymakers to identify and prioritize infrastructure investments that address both current and future needs. [ABSTRACT FROM AUTHOR]

Effective contractor selection is crucial for successful execution of construction projects. In contrast to the conventional lowest-bid approach prevalent in the public sector, this study focuses on developing a framework that minimizes time and cost overruns by considering diverse criteria for contractor selection. A variety of machine learning models, including multi-linear regression, random forest, Support Vector Machine, and Artificial Neural Network, have been employed, with multi-linear regression proving to be the most effective, achieving the lowest Mean Squared Error of 0.00003366. To determine the final order allocation, a multi-objective mathematical model was utilized to optimize conflicting criteria, such as time and cost overruns, sustainability, risk, and safety aspects related to shortlisted contractors. The findings highlight the significance of specific selection criteria, such as turnover, experience in similar projects, qualification of staff, technology utilization, client satisfaction, accident records, available bid capacity, and socioeconomic factors. This study emphasizes a three-phase decision-making framework for contractor selection and order allocation, particularly in public construction projects, with a focus on sustainability. By adopting this approach, government agencies can enhance infrastructure projects and minimize overruns through optimization and analytical tools, which aligns with the Gati-Shakti scheme of the Indian government. It is recommended that clients embrace a holistic approach to contractor selection, considering both technical and non-technical factors, to ensure successful project outcomes. [ABSTRACT FROM AUTHOR]

The accurate identification of water‐bearing structures is urgently required for the safe construction of tunnel engineering. Currently, the direct current resistivity method is an effective method for detecting water‐bearing structures in tunnels. In the advanced detection of the direct current resistivity based on the finite element method, the traditional hexahedron mesh performs poorly for the discretization of models of complex tunnel structure sections such as horseshoe‐shaped and round sections. Therefore, this study adopts unstructured grid generation technology combining tetrahedra and hexahedra to achieve more accurate modelling of complex structures, such as round and horseshoe‐shaped sections, and establishes a forward modelling method of the direct current resistivity in tunnels based on an unstructured mesh. The maximum error between the numerical simulation and theoretical results for an infinite tabular body in full space is less than 0.8%. It is more complicated to calculate the sensitivity matrix and model constraint term for the inversion region containing two types of grid than for one. For this purpose, the sensitivity matrix of different types of grid areas is calculated, a model constraint term based on the dual constraints of volume and distance is constructed, and finally, a partitioned domain‐weighted least‐squares inversion method based on an unstructured mesh is proposed. Synthetic examples of typical water‐bearing structures are analysed, and the results show that the proposed forward and inverse methods of the direct current resistivity in tunnels based on an unstructured mesh can effectively capture the position and morphology of the water‐bearing structure. Finally, an on‐site application was conducted in the Yellow River Diversion Project in central Shanxi. The proposed method could effectively identify the water body in front of the tunnel face and guide the on‐site construction of the project. These results can improve the interpretation of the direct current resistivity data in tunnels and play a positive role in promoting the use of the direct current resistivity method to prevent and control water‐inrush disasters in tunnels with complex structures. [ABSTRACT FROM AUTHOR]

The quality of construction projects is related to the safety of people's lives and property, and also has a greater impact on the stability of the entire society; factory structure is one of the most common productive buildings, and some factory buildings have been partially lost its using function due to a long service history; in order to ensure the safety, applicability and durability of these factory buildings and continue to utilize or strengthen these factory structures, it is necessary to perform safety testing and identification for factory buildings at the first time. Structural safety assessment is the process of inspecting, measuring, analyzing and evaluating the structural effects, structural resistance and their interrelationships and finally obtaining structural safety grade of buildings that have been built or in service for many years. On the basis of summarizing and analyzing previous research works, this article expounded the research background, current status and future challenges of building safety grade identification, elaborated material testing methods, specifications, frameworks and processes of security grade identification for factory structure buildings, analyzed the concrete strength and steel corrosion detection, structural seismic identification and bearing capacity calculation of factory building, and proposed corresponding reinforcement measures and discussed its reinforcement effect. The final identification results of an engineering case are in good agreement with its actual construction conditions and on-site inspections and basically satisfactory the results of the factory building structure. The study results of this paper provide a reference for the further researches on the safety grade identification and reinforcement effect of the factory structure building. [ABSTRACT FROM AUTHOR]

The success of a construction project depends on several critical success factors in such a hazardous scenario characterized by COVID-19 and its consequent stress. One important factor is supervision by a competent project manager with higher emotional intelligence (EI) skills especially in these pandemic times of uncertainty. The selection of this kind of project manager is, by nature, one of the most important and, at the same time, most complicated decisions to be made due to a multi-criteria decision-making (MCDM) problem. Based on previous studies, the human emotion element is often overlooked in the decision-making process. Modern evaluation would require a multimodal dataset to evaluate a competent candidate for the position. In addition, it is identified that classical MCDM is static and unable to quantify real-time human emotion. Hence, in this study, our approach uses an integrated techniques for MCDM and deep learning to address the managers' selection problem. Accordingly, a number of techniques, such as convolutional neural networks and other variations of algorithms, will be tested and compared. The emotion in our facial emotion recognition intensities value will be forwarded to MCDM as part of the input and eventually yield a non-bias and quality decision. It is anticipated that this study will enable employers to simplify and implement an effective decision-making process by embedding EI into the decision-making process to improve the quality of their hires and source the perfect candidate for construction project managers. Therefore, this study is aligned with the national construction agenda under the Construction 4.0 Strategic Plan (2021-2025), which requires changes to be made within the construction industry in tandem with the rapid development of technology and smarter systems. It emphasizes the utilization of digital technology as well as skills and knowledge enhancement. [ABSTRACT FROM AUTHOR]