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Integrated project delivery (IPD) is highly recommended to be utilised with building information management (BIM), specifically with BIM level-3 implementation process. Extant literature highlights the financial management challenges facing the proposed integration. These challenges are mainly related to the IPD compensation and the conventional cost control approaches that are not consistent with IPD principles. As such, this paper presents an integration of several methods to support automating risk/reward sharing amongst project parties thus enhancing IPD core team members’ relationship.

The literature review was used to highlight the challenges that face the IPD-based cost management practices such as the risk sharing/reward sharing amongst IPD core team members and potential methods to bridge the revealed IPD gap. A framework was developed by integrating the activity-based costing (ABC) – as a method to analyse the cost structure – and earned value management (EVM) to develop mathematical models that can determine the three main IPD financial transactions (i.e. …) fairly. To demonstrate the applicability of the developed system, a real-life case study was used, in which, promising results were collected in regard to visualising the cost control data and understanding of the accumulative status of the project cost and schedule for team members.

A centralised cost management system (CCMS) for IPD is developed to enable the IPD cost structure as well as automating the risk-sharing/reward-sharing calculations. This system is linked with a web-based management system to display the output of proposed risk-sharing/reward-sharing models. Moreover, a novel grid is developed to show the project status graphically and to respect the diversity in core team members backgrounds. In addition, the case study showed that the proposed integration of different methods (ABC, EVM, BIM and web-based management system) is interoperable and applicable.

This research presents a comprehensive solution to the most revealed challenges in cost management practices in IPD implementation. The outcome of this research contributes to the body of knowledge through presenting new extensions of the EVM to be used with the IPD approach to calculate risk/reward. Moreover, the implementation of the proposed tools such as centralised cost management system (CCMS) and CCMS for IPD web system will enhance/foster the implementation of the IPD in conjunction with BIM process.

Previous studies have established to a great extent that regulatory frameworks and, in particular, procurement approaches – that are common in a particular context – have a major impact on the success of building information modelling (BIM) implementation in construction projects. Despite the close links between these two concepts, research on the effect of procurement approaches on BIM implementation is scarce. To address this gap, this paper aims to investigate the barriers that affect BIM implementation through the lens of procurement approaches.

A mixed-method approach was adopted using a questionnaire survey (n = 116) and interviews with key stakeholders (n = 12) in Jordan. The outcomes of the quantitative parts were augmented with findings from interviews.

It was revealed that the deployment of unfavourable construction procurement approaches represents a major hurdle towards BIM implementation. Though essential for enhancing BIM implementation, it is revealed that a fundamental change from the common design-bid-build (DBB) to more collaborative procurement approaches remains infeasible in view of the realities that govern the construction industry.

It was revealed the deployment of unfavourable construction procurement approaches represents a major hurdle towards BIM implementation. Though essential for enhancing BIM implementation, it is revealed that a fundamental change from the common DBB to more collaborative procurement approaches remains infeasible given the realities that govern the construction industry.

As the first of its kind, a set of recommendations for establishing supportive, workable procurement that does not deviate significantly from common procedures and practices is presented. Rather than advocating a shift to procurement approaches that are aligned with BIM, the findings offer novel insight into the necessity of developing a framework within the boundaries of the current and widely adopted procurement approaches to address the identified construction procurement issues and facilitate BIM implementation.

The amalgamation of integrated project delivery (IPD) and building information modelling (BIM) is highly recommended for successful project delivery. However, IPD lacks an accurate cost estimation methodology at the “front-end” of projects, when little project information is available. This study aims to tackle this issue, through presenting analytical aspects, theoretical grounds and practical steps/procedures for integrating target value design (TVD), activity-based costing (ABC) and Monte Carlo simulation into the IPD cost structure, within a BIM-enabled platform.

A critical review was conducted to study the status of cost estimation within IPD, as well as exploring methods and tools that can enhance the cost estimation process for IPD. Thereafter, a framework is developed to present the proposed methodology of cost estimation for IPD throughout its entire stages. A case project is used to validate the practicality of the developed solution through comparing the profit-at-risk percentage for each party, using both traditional cost estimation and the proposed solution.

After applying the proposed IPD's cost estimation framework, on a real-life case project, the findings demonstrated significant deviations in the profit-at-risk value for various work packages of the project (approximately 100% of the finishing package and 22% of openings package). By providing a precise allocation of overhead costs, the solution can be used in real-life projects to change the entire IPD cost structure and ensure a fair sharing of risk–rewards among the involved parties in IPD projects.

Using the proposed methodology of cost estimation for IPD can enhance the relationship among IPD's core team members; all revealed financial deficiencies will be considered (i.e. compensation structure, profit pooling), hence enhancing the IPD performance.

This paper presents a comprehensive solution for integrating BIM and IPD in terms of cost estimation, offering three main contributions: (1) an innovate approach to utilise five-dimensional (5D) BIM capabilities with Monte Carlo simulation, hence providing reliable cost estimating during the conceptual TVD stage; (2) mathematical models that are developed through integrating ABC into the detailed 5D BIM to determine the three IPD's cost structure limbs; and (3) a novel mechanism of managing cost saving (rewards) through distinguishing between saved resources from organisation level, to daily task level, to increase trust among parties.

This paper aims to Test the capabilities/accuracies of four deep learning pre trained convolutional neural network (CNN) models to detect and classify types of highway cracks, as well as developing a new CNN model to maximize the accuracy at different learning rates.

A sample of 4,663 images of highway cracks were collected and classified into three categories of cracks, namely, “vertical cracks,” “horizontal and vertical cracks” and “diagonal cracks,” subsequently, using “Matlab” to classify the sample to training (70%) and testing (30%) to apply the four deep learning CNN models and compute their accuracies. After that, developing a new deep learning CNN model to maximize the accuracy of detecting and classifying highway cracks and testing the accuracy using three optimization algorithms at different learning rates.

The accuracies result of the four deep learning pre-trained models are above the averages between top-1 and top-5 and the accuracy of classifying and detecting the samples exceeded the top-5 accuracy for the pre-trained AlexNet model around 3% and by 0.2% for the GoogleNet model. The accurate model here is the GoogleNet model as the accuracy is 89.08% and it is higher than AlexNet by 1.26%. While the computed accuracy for the new created deep learning CNN model exceeded all pre-trained models by achieving 97.62% at a learning rate of 0.001 using Adam’s optimization algorithm.

The created deep learning CNN model will enable users (e.g. highway agencies) to scan a long highway and detect types of cracks accurately in a very short time compared to traditional approaches.

A new deep learning CNN-based highway cracks detection was developed based on testing four pre-trained CNN models and analyze the capabilities of each model to maximize the accuracy of the proposed CNN.

The integration of building information modelling (BIM) and integrated project delivery (IPD) is highly recommended for better project delivery. Although there is a methodology for this integration, the BIM requires some improvements to foster the adoption of IPD. The purpose of this paper is to present an innovative way to support 4D BIM automation/optimisation within the IPD approach. Similar to structural and architectural design libraries, this research proposes a planning library to enable automating the formulation of schedule, as well as embedding the multi-objective optimisation into the 4D BIM.

The literature review was used to highlight the existing attempts to support the automation process for 4D BIM and the multi-objective schedule optimisation for construction projects. A case study was done to validate the developed framework and measure its applicability.

The results show that there is a cost-saving of 22.86 per cent because of using the proposed automated multi-objective optimisation. The case study shows the significance of integrating activity-based costing into 4D BIM to configure the hierarchy level of overhead activities with the IPD approach; therefore, the maximum level of contribution in managing the IPD project is 33.33 per cent by the trade package level and the minimum contribution is around 8.33 per cent by the project level.

This research presents a new philosophy to develop the 4D BIM model – planning and scheduling – a BIM library of the project activities is developed to enable the automation of the creation of the project schedule with respect to the 3D BIM design sequence. The optimisation of the project duration is considered to be automated within the creation process by using the proposed genetic algorithm model.

Incipient detection of pavement deterioration (such as crack identification) is critical to optimizing road maintenance because it enables preventative steps to be implemented to mitigate damage and possible failure. Traditional visual inspection has been largely superseded by semi-automatic/automatic procedures given significant advancements in image processing. Therefore, there is a need to develop automated tools to detect and classify cracks.

The literature review is employed to evaluate existing attempts to use Hough transform algorithm and highlight issues that should be improved. Then, developing a simple low-cost crack detection method based on the Hough transform algorithm for pavement crack detection and classification.

Analysis results reveal that model accuracy reaches 92.14% for vertical cracks, 93.03% for diagonal cracks and 95.61% for horizontal cracks. The time lapse for detecting the crack type for one image is circa 0.98 s for vertical cracks, 0.79 s for horizontal cracks and 0.83 s for diagonal cracks. Ensuing discourse serves to illustrate the inherent potential of a simple low-cost image processing method in automated pavement crack detection. Moreover, this method provides direct guidance for long-term pavement optimal maintenance decisions.

The outcome of this research can help highway agencies to detect and classify cracks accurately for a very long highway without a need for manual inspection, which can significantly minimize cost.

Hough transform algorithm was tested in terms of detect and classify a large dataset of highway images, and the accuracy reaches 92.14%, which can be considered as a very accurate percentage regarding automated cracks and distresses classification.

High-level labor waste is a major challenge in construction projects. This paper aims to identify, quantify and categorize labor waste in the context of Iranian housing construction projects.

This research uses a case study approach, with empirical data collected through direct observations and semi-structured interviews.

Having triangulated the findings from the literature review and empirical studies, a list of eight types of waste was derived for the thirteen observed laborers in ten case study projects. The empirical studies allowed the labor waste identified from the literature to be verified and refined by considering it in the context of the observed activities, and led to two new types of waste being identified which were not considered in the literature. Findings indicate that nearly 62% of laborers' time is spent on non-value-adding activities. It appeared that “unnecessary movement,” “waiting” and “indirect work” make up the highest labor waste.

This research focuses only on onsite resource flows in a housing construction site. It does not include offsite flows such as material delivery to site.

The findings have provided substantial evidence on type and amount of labor waste and provide a solid basis to stimulate construction actors to participate in reducing labor waste and improving productivity.

This paper aims to explore the emerging relationship between Industry 4.0 (I4.0) digital technologies (e.g. blockchain, Internet of Things (IoT) and artificial intelligence (AI)) and the construction industry’s gradual transition into a circular economy (CE) system to foster the adoption of circular economy in the construction industry.

A critical and thematic analysis conducted on 115 scientific papers reveals a noticeable growth in adopting digital technologies to leverage a CE system. Moreover, a conceptual framework is developed to show the interrelationship between different I4.0 technologies to foster the implantation of CE in the construction industry.

Most of the existing bodies of research provide conceptual solutions rather than developing workable applications and the future of smart cities. Moreover, the coalescence of different technologies is highly recommended to enable tracking of building assets’ and components’ (e.g. fixtures and fittings and structural components) performance, which enables users to optimize the salvage value of components reusing or recycling them just in time and extending assets’ operating lifetime. Finally, circular supply chain management must be adopted for both new and existing buildings to realise the industry's CE ambitions. Hence, further applied research is required to foster CE adoption for existing cities and infrastructure that connects them.

This paper investigates the interrelationships between most emerging digital technologies and circular economy and concludes with the development of a conceptual digital ecosystem to integrate IoT, blockchain and AI into the operation of assets to direct future practical research applications

The wood construction industry has been described as slow in adapting efficiency-increasing activities in its operations and supply chain. The industry is still facing challenges related to digitalization, such as fragmentation, poor traceability and lack of real-time information. This study evaluates the status of digitalization in construction supply chains by thematically analyzing the existing literature and mapping research trends.

A review of the key literature from 2016 to 2021 was performed. The results highlight various technologies and their applications within supply chains and identify research gaps, especially between theoretical frameworks and actual implementation using a scientometric-thematic analysis.

This paper provides a conceptual framework to further aid researchers in exploring the current trends in Supply Chain 4.0 and its applications in the wood construction industry compared to other more advanced industries. Suggested directions for future research in the wood construction Supply Chain 4.0 are outlined.

The existing literature still lacks a comprehensive review of the potential of a digitalized supply chain, especially in the construction industry. This framework is pivotal to continue explaining and observing the best ways to accelerate and implement Supply Chain 4.0 practices for digitalized supply chain management (SCM) while focusing specifically on the wood construction industry. The literature review results will help develop a comprehensive framework for future research direction to create a clearer vision of the current state of digitalization in supply chains and focus on the wood construction supply chain, thus, fully achieving the benefits of Supply Chain 4.0 in the wood construction industry.