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This research aims to develop an automated and optimization algorithms (OAs)-integrated 4D building information modeling (BIM) approach and a prototype and enable construction managers and practitioners to estimate the time of compound elements in building projects using the resource specification technique.

A 4D BIM estimation process was first developed by applying the resource specification and geometric information from the BIM model. A suite of OA including particle swarm optimization, ant colony, differential evolution and genetic algorithm were developed and compared in order to facilitate and automate the estimation process. The developed processes and porotypes were linked and integrated.

The OA-based automated 4D BIM estimation prototype was developed and validated through a real-life construction project. Different OAs were applied and compared, and the genetic algorithm was found as the best performing one. The prototype was successfully linked with BIM timeliner application. By using this approach, the start and finish dates of all object-based activities are developed, and the project completion time is automatically estimated.

Unlike conventional construction estimation methods which need various tools and are error prone and time-consuming, the developed method bypasses the existing time estimation tools and provides the integrated and automated process with BIM and machine learning algorithms. Furthermore, this approach integrates 4D BIM applications into construction design procedures, connected with OA automation.

The purpose of this study is to identify and analyse the key measurable returning factors, value drivers and strategic benefits associated with building information modelling (BIM) return on investment (ROI). The findings of this study provide researchers and practitioners with up-to-date information in formulating appropriate strategies to quantify the monetary value of BIM. The suggested research agenda provided would also advance what is presently a limited body of knowledge relating to the evaluation of BIM ROI.

To fill the identified gap, this study develops a comprehensive systematic review of mainstream studies on factors affecting BIM ROI published from 2000 to 2020. A total of 23 academic records from different sources such as journals, conference proceedings, dissertation and PhD theses were identified and thoroughly reviewed.

The reported BIM ROI ranged greatly from −83.3% to 39,900%. A total of 5 returning factors, namely, schedule reduction and compliance, productivity improvement, request for information reduction, rework reduction and change orders reduction were identified as the most commonly reported factors that influence BIM ROI. Four quantification techniques including general assumptions-based theoretical model, perceived BIM ROI based on survey, factors affecting BIM ROI with no reported ROI and quantified BIM ROI based on a case study were observed and pointed out in the review, together with their limitations. Finally, three major gaps were raised as the lack of consideration on the likelihood of BIM assisting in a construction project, intangible returning factors influencing BIM-based projects and industry standards in benchmarking BIM ROI.

The outcomes of this study would assist practitioners by providing the current evaluation techniques that address the limitations with BIM investment and present issues relating to the economic evaluation of BIM in the construction industry. It is also expected that presenting a deeper and wider perspective of the research work performed until now will direct a more focussed approach on productivity improvement efforts in the construction industry.

This study identifies and analyses the key measurable returning factors, value drivers and strategic benefits associated with BIM ROI on an industry scale rather than a particular organisation or a project scale.

This study aims to present a comprehensive review, critical analysis and implications of the augmented reality (AR) application and implementation in the construction industry arena and demonstrate the gaps along with the future research agenda.

The construction industry has been under pressure to improve its productivity, quality and sustainability. However, the conventional methods and technologies cannot respond to this industry's ever-growing demands while emerging and innovative technologies such as building information modelling, artificial intelligence (AI), virtual reality (VR) and AR have emerged and can be used to address this gap. AR application has been acknowledged as one of the most impactful technologies in the construction digitalization process. However, a comprehensive understanding of the AR application, its areas of effectiveness and overarching implications in a construction project life cycle remain vague. Therefore, this study uses an integration of systematic literature review and thematic analysis techniques to identify the phases of a construction project life cycle in which AR is the most effective, the current issues and problems of the conventional methods, the augmented parameters, the immediate effects of using AR on each phase and, eventually, the overall influence of AR on the entire project. Nvivo qualitative data analysis software was used to code, categorize and create themes from the collected data. The result of data analysis was used to develop four principal frameworks of the AR applications – design and constructability review session; construction operation; construction assembly; and maintenance and defect inspection and management – and the gap analysis along with the future research agenda.

The findings of this study indicated that the application of AR can be most effective in the following four stages of a project life cycle: design and constructability review session; construction operation; construction assembly; and site management and maintenance, including site management and defect inspection. The results also showed that the application of AR technology in the construction industry can align and address building industry objectives by various elements such as: reducing project costs through the application of digital technologies, saving time, meeting deadlines and reduction in project delays through integrated, live scheduling and increased safety and quality of the construction work and workers.

One of the main limitations of this study was the lack of materials and resources on the downfalls and shortcomings of using immersive technologies, AR, in the construction project life cycle. In addition, most of the reviewed papers were focused on the experiments with simulations and in the lab environment, rather than real experiments in real construction sites and projects. This may cause limitations and inaccuracy of the collected and reported data.

The results of this study indicated that the application of AR technology in construction industry can align and address building industry objectives by various elements such as: reducing project costs through the application of digital technologies; saving time; meeting deadlines and reduction in project delays through integrated, live scheduling; and increased safety and quality of the construction work and workers.

Application of AR in the various stages of a project life cycle can increase the safety and quality of the construction work and workers.

The reviewed literature indicated that substantial research and studies are yet to be done, to demonstrate the full capacity and impact of these emerging technologies in the field. The collected data and literature indicate that amongst the digital technologies, AR is one of the least researched topics in the field. Therefore, this study aims to examine the application of AR in construction projects’ life cycle to identify the stages and practices of a project life cycle where AR and its capabilities can be exploited and to identify the respective problems and issues of the conventional methods and the ways in which AR can address those shortcomings. Furthermore, this study focuses on identifying the overall outcome of AR applications in a construction project in terms of cost and time efficiency, process precision and safety.

Successful implementation of infrastructure projects has been a controversial issue in recent years, particularly in developing countries. This study aims to propose a decision support system (DSS) for the evaluation and prediction of project success while considering sustainability criteria.

To predict sustainable success factor, the study first developed its sustainable success factors and sustainable success criteria. These then formed a decision table. A rough set theory (RST) was then implemented for rules generation. The decision table was used as the input for the rough set, which returned a set of rules as the output. The generated rulesets were then filtered in fuzzy inference system (FIS), before serving as the basis for the DSS. The developed prediction tool was tested and validated by applying data from a real infrastructure project.

The results show that the developed rough set fuzzy method has strong ability in evaluation and prediction of the project success. Hence, the efficacy of the DSS is greatly related to the rule-based system, which applies RST to generate the rules and the result of the FIS was found to be valid via running a case study.

Use of DSS for predicting the sustainable success of the construction projects is gaining progressive interest. Integration of RST and FIS has also been advocated by the seminal literature in terms of developing robust rulesets for impeccable prediction. However, there is no preceding study adopting this integration for predicting project success from the sustainability perspective. The developed system in this study can serve as a tool to assist the decision-makers to dynamically evaluate and predict the success of their own projects based on different sustainability criteria throughout the project life cycle.

Over the past decade, architecture, construction and engineering (ACE) industries have been evolving from traditional practices into more current, interdisciplinary and technology integrated methods. Intricate digital tools and mobile computing such as computational design, simulation and immersive technologies, have been extensively used for different purposes in this field. Immersive technologies such as augmented reality (AR) and virtual reality (VR) have proven to be very advantageous while the research is in its infancy in the field. Therefore, this study aims to develop an immersive pedagogical framework that can create a more engaging teaching and learning environment and enhance students' skill in the ACE field.

This study developed a BIM-enabled VR-based pedagogical framework for the design studio teaching in architectural courses, using a qualitative approach. A case study method was then used to test and validate this developed framework. Architectural Master Design Studio B, at Queensland University of Technology (QUT) was selected as the case study, with South Bank Corporation (SBC) as the industry partner and stakeholder of this project.

The practicality and efficiency of this framework was confirmed through increased students' and stakeholders' engagement. Some of the additional outcomes of this digitally enhanced pedagogical framework are as follows: enhanced students' engagement, active participation, collective knowledge construction and increased creativity and motivation.

The results have proven that the developed technology-enhanced and digitally enabled teaching pedagogy and framework can be successfully implemented into architectural design studios. This can bridge the existing gap between the technological advancements in ACE industry and higher education teaching and learning methods and outcomes. It is also expected that such innovative pedagogies will future-proof students' skill set as the future generation of architects and built environment workers. A major limitation of this framework is accessibility to the required hardware such as HMD, controllers, high-capacity computers and so on. Although the required software is widely accessible, particularly through universities licencing, the required hardware is yet to be readily and widely available and accessible.

The result of this study can be implemented in the architectural design studios and other ACE related classrooms in higher educations. This can bridge the existing gap between the technological advancements in ACE industry, and higher education teaching and learning methods and outcomes. It is also expected that such innovative pedagogies will future-proof students' skill set.

Such technology-enhanced teaching methods have proven to enhance students' engagement, active participation, collective knowledge construction and increased creativity and motivation.

Despite the advancement of digital technologies in ACE industry, the application of such technologies and tools in higher education context are not yet completely explored and still scarce. Besides, there is still a significant gap in the body of knowledge about developing teaching methods and established pedagogies that embrace the usage of such technologies in the design and architecture curricula.

The purpose of this study is to examine, review and analyse the current literature on building and construction quality and determine the related themes and gaps.

A systematic review approach was adopted on the building quality literature, and keywords such as “construction” or “building”; “defect” and “quality” or “rework” were searched through the Scopus, Web of Science and Google Scholar databases. A number of articles were found and filtered by title, abstract and keyword relevancy. Further articles were cross-referenced from these and again filtered by title, abstract and keyword relevancy. The time period for the search was 2000–2020. A total of 97 articles were found and analysed on the topic.

A number of recurring themes were found throughout the literature. They are safety, occupier satisfaction, cost, time, licensing, culture, training, software and building quality frameworks, classifications and recommendations. These themes were linked to display relationships between them from the literature. Based on the project lifecycle stages, an amalgamated classification system was developed and is presented here. The gaps in the current literature have been analysed and reported on.

A comprehensive descriptive, thematic and gap analysis was conducted on the available literature of building and construction quality. The emerging themes were discovered, their relationships were demonstrated and the research gaps were identified. A new classification system positioned in the project lifecycle stages is presented.

The business benefits envisaged for BIM represent the main criteria for decision-making about BIM implementation – or shy away from BIM. Despite the significance, traditional evaluation techniques have difficulty to capture “the true value” of BIM from multiple levels and dimensions – as an effective evaluation method is supposed to. This study aims to identify the significant factors that affect BIM return on investment (ROI), develop an integrated model for companies and examine the influence of intangible returning factors of BIM on the rate of BIM implementation.

A cluster sampling technique was used; 92 questionnaires completed by Australian architecture, engineering and construction small- and medium-sized enterprises (SMEs) provided the basis to identify and analyse the key measurable returning factors, value drivers and strategic benefits associated with BIM ROI.

Applying the PLS-SEM technique, findings reveal that a lack of reliable quantification methods for the ROI factors associated with BIM significantly affects the organisation's commitments to implement BIM. In essence, the failure to adequately identify and assess these benefits could result in the system not being appropriately implemented and supported by executive sponsors, who give priority to hard and tangible ROI measurements.

The outcome of this study would be of direct appeal to policymakers, industry professionals and the academic community alike, in providing data-informed insight into the intersection between the implementation of BIM and the concept of ROI. Findings would provide a springboard for further research into using ROI factors to increase BIM implementation. Though the findings are directly applicable and contextualised for Australia, they provide lessons and offer a blueprint for similar studies in other countries and settings. That is, regardless of the context, findings raise awareness and provide a point of reference for the quantification of intangible returning factors rather than the tangible returning factors, as one of the first studies in its kind.

The study provides original insight in drawing attention to an untapped area for research in BIM implementation, namely BIM ROI. Apart from raising awareness around BIM ROI, the study is novel in providing a quantified model that establishes the links and level of impacts of various factors associated with BIM ROI. Findings of this study, particularly add value to the body of knowledge related to the business implications associated with BIM implementation in the context of Australian SMEs, while providing lessons for other countries and settings.

This study underscores the critical importance of well-functioning sewer systems in achieving smart and sustainable urban drainage within cities. It specifically targets the pressing issue of sewer overflows (SO), widely recognized for their detrimental impact on the environment and public health. The primary purpose of this research is to bridge significant research gaps by investigating the root causes of SO incidents and comprehending their broader ecological consequences.

To fill research gaps, the study introduces the Multi-Phase Causal Inference Fuzzy-Based Framework (MCIF). MCIF integrates the fuzzy Delphi technique, fuzzy DEMATEL method, fuzzy TOPSIS technique and expert interviews. Drawing on expertise from developed countries, MCIF systematically identifies and prioritizes SO causes, explores causal interrelationships, prioritizes environmental impacts and compiles mitigation strategies.

The study's findings are multifaceted and substantially contribute to addressing SO challenges. Utilizing the MCIF, the research effectively identifies and prioritizes causal factors behind SO incidents, highlighting their relative significance. Additionally, it unravels intricate causal relationships among key factors such as blockages, flow velocity, infiltration and inflow, under-designed pipe diameter and pipe deformation, holes or collapse, providing a profound insight into the intricate web of influences leading to SO.

This study introduces originality by presenting the innovative MCIF tailored for SO mitigation. The combination of fuzzy techniques, expert input and holistic analysis enriches the existing knowledge. These findings pave the way for informed decision-making and proactive measures to achieve sustainable urban drainage systems.

Previous research has demonstrated that Digital Twins (DT) are extensively employed to improve sustainable construction methods. Nonetheless, their uptake in numerous nations is still constrained. This study seeks to identify and examine the digital twin’s implementation barriers in construction building projects to augment operational performance and sustainability.

An iterative two-stage approach was adopted to explore the phenomena under investigation. General DT Implementation Barriers were first identified from extant literature and subsequently explored using primary questionnaire survey data from Hong Kong building industry professionals.

Survey results illustrated that Lack of methodologies and tools, Difficulty in ensuring a high level of performance in real-time communication, Impossibility of directly measuring all data relevant to the DT, need to share the DT among multiple application systems involving multiple stakeholders and Uncertainties in the quality and reliability of data are the main barriers for adopting digital twins' technology. Moreover, Ginni’s mean difference measure of dispersion showed that the stationary digital twin’s barriers adoption is needed to share the DT among multiple application systems involving multiple stakeholders.

The study’s findings offer valuable guidance to the construction industry. They help stakeholders adopt digital twins' technology, which, in turn, improves cost efficiency and sustainability. This adoption reduces project expenses and enhances environmental responsibility, providing companies a competitive edge in the industry.

This research rigorously explores barriers to Digital Twin (DT) implementation in the Hong Kong construction industry, employing a systematic approach that includes a comprehensive literature review, Ranking Analysis (RII) and Ginni’s coefficient of mean difference (GM). With a tailored focus on Hong Kong, the study aims to identify, analyze and provide novel insights into DT implementation challenges. Emphasizing practical relevance, the research bridges the gap between academic understanding and real-world application, offering actionable solutions for industry professionals, policymakers and researchers. This multifaceted contribution enhances the feasibility and success of DT implementation in construction projects within the Architecture, Engineering and Construction (AEC) sector.

In the study, a five-dimensional-safety risk assessment model (5D-SRAM) is developed to improve the construction safety risk assessment approaches available in the literature. To that purpose, a hybrid multi-dimensional fuzzy-based model is proposed, which provides a comprehensive ranking system for the safety risks existing in a project by considering the contextualization of the construction-related activities resulting in an accident.

The developed 5D-SRAM is based on an amalgamation of different fuzzy-based techniques. Through the proposed fuzzy analytic hierarchy process (AHP) method, the importance weights of essential risk dimensions playing role in defining the magnitude of the construction-related risks are obtained, while a precise prioritized ranking system for the identified safety risks is acquired using the proposed fuzzy technique of order preference similarity to the ideal solution (FTOPSIS).

Through the application of the proposed 5D-SRAM to a real-life case study – which is the case of green building construction projects located in Hong Kong – contributions are realized as follows: (1) determination of a more complete range of risk dimensions, (2) calculation of importance weightings for each risk dimension and (3) obtainment of a precise and inclusive ranking system for safety risks. Additionally, the supremacy of the developed 5D-SRAM against the other safety assessment approaches that are commonly adopted in the construction industry is proved.

The developed 5D-SRAM provides the concerned safety decision-makers with not only all the crucial dimensions that play roles toward the magnitude of safety risks posing threats to the workers involved in construction activities, but also they are given hindsight regarding the importance weights of these dimensions. Additionally, the concerned parties are embellished with the final ranking of safety risks in a more comprehensive way than those of existing assessment methods, leading to sagacious adoption of future prudent strategies for dealing with such risks occurring on construction sites.

Numerous studies have documented the safety risks faced by construction workers including proposals for risk assessment models. However, the dimensions considered by such models are limited, generally constrained to risk event probability combined with risk impact severity. Overlooking other dimensions that are essential towards the calculation of safety risks' magnitude culminates in overshadowing the further adoption of fruitful mitigative actions. To overcome this shortcoming, this study proposes a novel 5D-SRAM.