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Rapid urbanization and the shortcomings of traditional construction methods motivate construction professionals to explore faster and more sustainable approaches such as off-site construction (OSC). Thus, the purpose of this paper is to identify the drivers influencing OSC adoption and to explore the key drivers of its widespread adoption in Egypt.

A comprehensive global literature review was performed initially to develop an up-to-date list of OSC adoption drivers, which was confirmed in the Egyptian context through a pilot study. Then, social network analysis (SNA) was utilized to determine the most influential drivers as well as shortlist them to construct the final questionnaire survey. A total of 57 stakeholders in the Egyptian construction industry responded. Lastly, the relative importance index (RII) was calculated to rank the drivers, revealing the key drivers.

The results revealed that higher productivity, improving project quality control, shortening construction time, improving product quality and improving supervision and inspection are the top five drivers. On the contrary, government policies and regulations is the least significant driver.

This research contributes to the body of knowledge by introducing a comprehensive, up-to-date list of drivers, which helps the stakeholders gain a better understanding of the driving enablers of adopting OSC generally and helps Egyptian stakeholders make more informed decisions about its implementation specifically.

Given the growing interest in modern construction techniques and the emergence of innovative technologies, construction site layout planning research has progressively been investigating approaches to adopt innovative concepts and incorporate renewed approaches to improve widespread efficiency. This research develops a decision-making tool that optimizes construction site layout plans. The developed model targets two main objectives: minimizing material transportation costs and maximizing safety by optimally placing facilities on construction sites.

A novel approach is devised based on the integration of Building Information Modeling and Generative Design (BIM-GD). This engine is used to optimize the multi-objective site layout problems to identify layout alternatives in the early project stages. Parametric modeling uses Dynamo to construct the model and explore constraints initially. Finally, the GD environment is utilized to create different design alternatives, and then the decision-making procedure selects the most appropriate design alternative. Additionally, a case study is applied to validate the effectiveness of the developed model.

The results indicate the effectiveness of the proposed GD tool and its potential for more complex applications. The GD engine examined optimal layout plans, balancing different objectives and adhering to appointed geometric constraints. A case study was conducted to assess the model's effectiveness and showcase its suitability. Construction Site Layout Planning (CSLP) is an essential step in design that can influence considerable aspects, such as material transportation expenses and different safety standards on the site. Employing visual programming for parametric modeling within Dynamo-Revit creates an expedient and user-friendly platform for planning engineers who may require more programming expertise to create and program algorithmic models visually. Utilizing GD in CSLP has proven to be a powerful tool with consequential prospects for improving applications and executing more models.

The findings from this framework are intended to help construction practitioners select the most appropriate site layout during early project stages while incorporating different safety criteria inside construction sites to alleviate actual safety risks.

A new approach is proposed that utilizes an integrated BIM-GD engine to optimize multi-objective site layout problems. This approach targets two main objectives: minimizing material transportation costs and maximizing safety by optimally placing facilities in construction sites.

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study aims to establish a Greenness of Construction Technologies (GCT) evaluation model using the method of analytic network process (ANP).

Green construction is increasingly vital in promoting sustainability within the construction industry. The development and promotion of green construction technologies are central to this endeavor. However, existing evaluations mainly target building components, construction projects or certain construction processes. There is a notable absence of research into the greenness of construction technologies. Assessing the greenness of construction technologies is crucial for streamlining resource utilization and reducing waste. To address this gap, this study establishes a GCT evaluation model using the method of ANP.

Among the four formwork technologies of plastic, steel, plywood and wooden formwork, the plastic formwork exhibits the best performance in terms of environmental friendliness, economic and social effects, while facing issues like material wastage and low static strength. The results align with practical observations which validates the model’s applicability.

This research contributes to the field by introducing the concept of greenness into construction technology evaluation for the first time. The establishment of the GCT evaluation model promotes the adoption of green construction technologies and advances sustainable practices in the construction industry.

The Government’s investment in infrastructure projects is considerably high, especially in bridge construction projects. Government authorities must establish an initial forecasted budget to have transparency in transactions. Early cost estimating is challenging for Quantity Surveyors due to incomplete project details at the initial stage and the unavailability of standard cost estimating techniques for bridge projects. To mitigate the difficulties in the traditional preliminary cost estimating methods, there is a requirement to develop a new initial cost estimating model which is accurate, user friendly and straightforward. The research was carried out in Sri Lanka, and this paper aims to develop the artificial neural network (ANN) model for an early cost estimate of concrete bridge systems.

The construction cost data of 30 concrete bridge projects which are in Sri Lanka constructed within the past ten years were trained and tested to develop an ANN cost model. Backpropagation technique was used to identify the number of hidden layers, iteration and momentum for optimum neural network architectures.

An ANN cost model was developed, furnishing the best result since it succeeded with around 90% validation accuracy. It created a cost estimation model for the public sector as an accurate, heuristic, flexible and efficient technique.

The research contributes to the current body of knowledge by providing the most accurate early-stage cost estimate for the concrete bridge systems in Sri Lanka. In addition, the research findings would be helpful for stakeholders and policymakers to propose policy recommendations that positively influence the prediction of the most accurate cost estimate for concrete bridge construction projects in Sri Lanka and other developing countries.

Based on the extended theory of planned behavior, this study aims to examine potential intentions-related factors that affect Islamic tax compliance moderated by information and communication technology (ICT) adoption.

A quantitative cross-sectional design was used to distribute questionnaire sets to 975 working Muslim Omanis by using convenience sampling method. PLS-SEM was mainly used to examine the data.

All the factors determine behavioral intention to pay Islamic tax (BIIT), which significantly predicts Islamic tax compliance behavior (ITCB). However, perceived control behavior negatively determines intention. ICT adoption moderates the link between BIIT and ITCB.

This study offers both practical and theoretical implications that can guide efforts to promote Islamic tax compliance and advance our understanding of tax behavior within the ETPB framework.

This study accounted for crucial factors determining intention than earlier ones using the ETPB. Considering technological advancements, the study also assessed the moderating role of ICT between BIIT and ITCB.

In recent times, there has been a lot of research focused on performance measurement (PM) in project-based sectors. However, there are very few studies that were reported on the significance of PM in the construction sector. Keeping track of an organization in achieving organizations goals and objectives seems an important way. One of the major challenges faced by the industry is unavailable of an appropriate PM system for assessing organizational performance. Most of the PM approaches consider the traditional project triangle assessment of project success. Based on the limitations identified in existing PM models, the purpose of this paper is to develop a comprehensive PM model, i.e. Modified Project Quarter Back Rating (MPQR) applicable for construction projects.

A detailed list of performance areas as a method for PM is analyzed in the construction industry context. Also, industry-specific professionals conducted semi-structured interviews to assess whether these performance areas are sufficient to measure and understand the PM systems.

The research finding focuses on developing the MPQR model that considers both financial and non-financial areas for performance assessment to provide a holistic assessment of project performance.

MPQR model provides an opportunity to set the benchmark for overall performance for construction organizations.

The findings of the study are expected to provide guidelines to construction professionals for implementing the performance model that will improve performance in the construction industry.

The construction business is widely recognised for its inherent complexity and dynamic nature, which stems from the nature of the job involved. The industry is often regarded as one of the most challenging industries globally in terms of implementing environmental, health and safety (EHS) practices. However, in the absence of EHS, the construction industry cannot be considered sustainable. Therefore, this study aims to identify the trends, knowledge gaps and implications of EHS research to enhance construction activities and knowledge.

The study adopted a science mapping approach involving bibliometric and scientometric analysis of 407 construction EHS publications from the Scopus database with the VOSviewer software. The study is based on journal articles from the Scopus database without restriction to any time range.

The main focus of construction EHS research identified in the study includes sustainability-related studies, risk-related, environmental issues, EHS management, integrated management systems studies, health and safety related and EHS in the construction process. Some emerging areas also identified include productivity, design, culture, social sustainability and machine learning. The most influential and productive publication sources, countries/regions and EHS publications with the highest impact were also determined.

Documents published in the Scopus database were considered for analysis because of the wider coverage of the database. Journal articles written in English language represent the inclusion criteria, whereas other documents were excluded from the analysis. The study also limited the search to articles with the engineering subject area.

The research findings will enlighten stakeholders and practitioners on the focal knowledge areas in the EHS research domain, which are vital for enhancing EHS in the industry.

To the best of the authors’ knowledge, this review-based study is the first attempt to internationally conduct a science mapping on extant literature in the EHS research domain through bibliometric and scientometric assessments.

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.

Electronic wallets (e-wallet) systems have revolutionized transactional activities, prompting individuals to adopt digital payment methods. This study investigates the determinants of the continuance intention of the e-wallet system Touch 'n Go in Malaysia. We propose a framework integrating the diffusion of innovation theory (DOI) and mental accounting theory, thereby assessing the impacts of product-related factors (convenience, compatibility, perceived risk and perceived compatibility) and the moderating role of personal-related factors [personal innovativeness (PI) and personal anxiety].

Data were collected involving 381 Malaysian Touch 'n Go users. The partial least squares structural equation modeling (PLS-SEM) was applied as a data analysis technique.

As demonstrated by the results, convenience serves as a facilitator, while perceived risk acts as an inhibitor, influencing the continuance intention of the application. Compatibility and perceived complexity are found to be insignificant antecedents. However, neither PI nor personal anxiety was found as moderators.

This research brings contributions to the electronic commerce literature by extending the understanding of the predictors and moderators of the continuance intention of Touch 'n Go users in Malaysia. We discuss how these findings implicate the two theories and offer insights for service providers and policymakers to promote the post-adoption intentions of Touch 'n Go.

Adopting sustainable building materials (SBMs) is one way to reduce the negative environmental impacts of the built environment. However, the adoption of SBMs is not as high as expected. This study aims to investigate which factors affect the adoption of SBMs.

A literature review and discussions with professional practitioners formed an initial list of variables affecting readiness to adopt SBMs. A questionnaire survey was designed, and data from industrial practitioners were collected using the snowball sampling method. The data collected from 218 respondents were analyzed using the PLS-SEM technique.

The findings show that SBM adoption is critically influenced by readiness at different levels (market, organization, and employee). Specifically, market readiness enhances organization preparedness (beta = 0.628), and organization readiness positively affects employee readiness (beta = 0.510). Market, organization, and employee readiness positively impact the adoption of SBMs (beta = 0.386, 0.364, and 0.158, respectively). Moreover, the relationship between market and employee readiness is fully mediated by organization readiness (indirect effect = 0.320; p = 0.000). Organization readiness positively mediates the relationship between market readiness and SBM adoption (indirect effect = 0.050; p = 0.001). The relationship between organization readiness and SBM adoption is fully mediated by employee readiness (indirect effect = 0.229; p = 0.000). Additionally, employee readiness positively mediates the relationship between market readiness and SBM adoption through organization readiness (indirect effect = 0.080; p = 0.000).

While past studies have predominantly focused on human perception, this study recognizes the importance of contextual factors like market conditions, Organization readiness, and employee readiness in shaping the adoption of SBMs. Thus, it fills a notable void in the literature and highlights the need for a broader theoretical framework that incorporates both individual perceptions and external contextual influences.