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Architecture, engineering and construction (AEC) is an important industry worldwide and one of the largest economic sectors in several developing countries, particularly in Iran. The Iranian AEC sector suffers from low productivity and needs to adopt building information modeling (BIM) to reduce inefficiencies. Therefore, this paper was conducted to identify the BIM barriers and propose practical solutions to overcome them in Iran.

A comprehensive literature review, two rounds of the Delphi technique and semi-structured interviews with 12 Iranian experts in the AEC sector were conducted. The data were analyzed using the mean score, standard deviation and nonparametric tests.

The present study identified 26 BIM barriers in the Iranian AEC community and provided practical strategies for improving BIM adoption. The identified barriers were categorized into six main groups including source barriers, financial barriers, unawareness barriers, organizational barriers, regulatory barriers and market-demand barriers. The main three BIM barriers in Iran were the lack of government intervention, change-resistant and the gap between industry and academia. Kruskal–Wallis tests revealed that there are no statistically significant differences in perceptions of BIM barriers between respondents. The Mann–Whitney test indicated that there is no statistically significant difference in perceptions between engineers and architects except for one.

There are few studies on BIM adoption across developing countries, particularly in Iran. Moreover, the results can also be used in other developing nations with similar conditions.

In the realm of construction education, the investigation of immersive learning and extended reality (XR) technologies has experienced a surge in recent times. Nevertheless, there remains a notable lack of comprehension surrounding the most efficient ways to integrate these technologies into tailored teaching approaches for vocational construction training. This research study aims to pinpoint the key factors that construction vocational education and training (VET) providers must consider when introducing XR technologies into their training schemes.

This study conducted an in-depth literature review to develop an initial framework to summarise training, technology and institutional factors influencing the educational-technology integration of XR technologies in VET. In addition, this study utilised a Delphi technique, including semi-structured group discussions and two rounds of online follow-up questionnaires, to capture VET experts’ judgements on the importance of decision-making criteria.

This study has identified the critical factors to be considered in the VET sector when adopting XR technologies. Findings revealed institutional factors were the most important criteria for participants, followed by training and technology factors.

The current decision-making process focuses on selecting XR technologies rather than evaluating their performance after implementation. Therefore, more research is needed to monitor the implementation of this technology in curricula from a senior management perspective. This will help to understand the cost and value factors related to the value proposition of XR technologies in courses.

To ensure the success and long-term viability of the technology-curriculum interface, it is important to consider factors such as the availability of technical and educational support, data security and cost-effectiveness. It is also crucial to focus on ease of use and content development that emphasises instruction to create engaging content for learners.

The potential impact of this study is underpinned by two facts: (1) it constitutes the first effort made in the field to comprehensively elicit VET expert judgements in relation to XR technologies, and (2) it offers decision-making criteria that are at play in seeking to take advantage of high-cost technologies that are rapidly evolving. While there is no simple checklist for XR implementation, this study takes a step further to identify significant factors influencing XR integration in vocational construction training.

The construction industry remains one of the most hazardous industries worldwide, with a higher number of fatalities and injuries each year. The safety and well-being of workers at a job site are paramount as they face both immediate and long-term risks such as falls and musculoskeletal disorders. To mitigate these dangers, sensor-based technologies have emerged as a crucial tool to promote the safety and well-being of workers on site. The implementation of real-time sensor data-driven monitoring tools can greatly benefit the construction industry by enabling the early identification and prevention of potential construction accidents. This study aims to explore the innovative method of prototype development regarding a safety monitoring system in the form of smart personal protective equipment (PPE) by taking advantage of the recent advances in wearable technology and cloud computing.

The proposed smart construction safety system has been meticulously crafted to seamlessly integrate with conventional safety gear, such as gloves and vests, to continuously monitor construction sites for potential hazards. This state-of-the-art system is primarily geared towards mitigating musculoskeletal disorders and preventing workers from inadvertently entering high-risk zones where falls or exposure to extreme temperatures could occur. The wearables were introduced through the proposed system in a non-intrusive manner where the safety vest and gloves were chosen as the base for the PPE as almost every construction worker would be required to wear them on site. Sensors were integrated into the PPE, and a smartphone application which is called SOTER was developed to view and interact with collected data. This study discusses the method and process of smart PPE system design and development process in software and hardware aspects.

This research study posits a smart system for PPE that utilises real-time sensor data collection to improve worksite safety and promote worker well-being. The study outlines the development process of a prototype that records crucial real-time data such as worker location, altitude, temperature and hand pressure while handling various construction objects. The collected data are automatically uploaded to a cloud service, allowing supervisors to monitor it through a user-friendly smartphone application. The worker tracking ability with the smart PPE can help to alleviate the identified issues by functioning as an active warning system to the construction safety management team. It is steadily evident that the proposed smart PPE system can be utilised by the respective industry practitioners to ensure the workers' safety and well-being at construction sites through monitoring of the workers with real-time sensor data.

The proposed smart PPE system assists in reducing the safety risks posed by hazardous environments as well as preventing a certain degree of musculoskeletal problems for workers. Ultimately, the current study unveils that the construction industry can utilise cloud computing services in conjunction with smart PPE to take advantage of the recent advances in novel technological avenues and bring construction safety management to a new level. The study significantly contributes to the prevailing knowledge of construction safety management in terms of applying sensor-based technologies in upskilling construction workers' safety in terms of real-time safety monitoring and safety knowledge sharing.

This study aims to find whether sukuk (Islamic bonds) possess a safe haven property for investors or not.

To analyze this statement, the study used data from MSCI World conventional and MSCI World Islamic indices from August 17, 2012 to June 8, 2022. The study used the generalized autoregressive conditional heteroskedasticity (GARCH) variance technique, the most common technique used in stock data analysis.

The results dictate the absence of sukuk as a safe haven for investors as both the conventional and Islamic markets show decoupling behavior. The study finds concrete evidence of a strong association between the debt-based bond market and the Islamic sukuk market. As these markets mostly like to move in a parallel direction, a recession in a conventional bond market likely means a recession in the Islamic sukuk market.

This study is unique in incorporating the MSCI World Islamic Index and other Islamic indices of several Muslim countries, which was absent in previous research. Second, this study is unique because it adds a separate regression for the COVID era to show whether the movement of indices changed during regression.

The oil and gas industry form the main resource of economy in Iraq and constructing any project in such sectors requires a huge amount of expenses due to the unique requirements that oil and gas facilities required in such projects. Therefore, adopting an appropriate technological approach such as building information modeling (BIM) which is unfortunately not adopted yet in Iraq is essential to successfully deliver these projects. Thus, this paper aimed to introduce BIM to Iraq through Basra Oil Company (BOC) which is one of the biggest public oil and gas companies in Iraq.

The related literature of journals articles, conference proceedings and published reports have been reviewed. As a result, firstly: a hypothesis has been derived that is “If Basra Oil Company (BOC) adopts and applies BIM approach instead of the 2D approach currently used to manage its projects, the company can overcome several constraints in managing its projects that associated with such 2D traditional approach”; secondly: homogenous, consistence and reliable web-based questionnaire has been designed as its Cronbach’s alpha equal to 0.897 and 0.711 for BIM benefits and barriers, respectively. This questionnaire distributed to the BOC related professionals to test such hypothesis by investigating their readiness and accepting of BIM approach and to rank BIM barriers based on five-point Likert scale.

Based on the analysis using IBM SPSS Statistics 26 of 115 responses, almost 50% of the respondents had experience 11–15 years, while 22.6% had experience more than 15 years in oil and gas industry construction projects. Those participants were from diverse engineering majors that are: 4.3% Architectural Engineers, 31.3% Civil Engineers, 20% Mechanical Engineers, 22.6% Electrical Engineers and 21.7% from other engineering majors. The respondents’ departments demography was 16.5% of design department, 12.2% of construction department, 20.9% of Project Management Department, 12.2% of Maintenance department, 4.3% of HSE Department, 13% of Production Department and 20.9% of “Other Department.” The study resulted in 1: accepting BIM approach to be an alternative of current 2D-traditional approach used by the company to manage and construct its projects, since mean of collected data is (4.4332), Kruskal–Wallis H test significance values were 0.398 and 0.372; and ANOVA test significance values were 0.433 and 0.599 among Engineering Majors groups and Company’s Department groups, respectively. 2: Disclosed and sequenced BIM barriers in the company based on their criticality. 3: verifying reliably how BIM attributes are important to oil and gas construction projects in Iraq, 4: the company top management and company policies are the most critical potential factors to hinder or adopt and implement BIM in the company, 5: while cost is not seen a critical barrier to implement BIM in the oil and gas sector.

The limitation of this study is the excluding of decision makers of BOC, thus more profound future studies need to be conducted where top management and decision makers are involved, particularly the present study demonstrated that support of company top management is the most critical factor which can help the company to adopt (BIM).

The study concludes that BIM approach is valuable for managing projects in oil and gas sector in Iraq and identify the originality in output by using the research method. This noble study provides a leverage for enhanced research to adopt and implement building information modeling (BIM) in Iraq as the study originally demonstrates benefits and identifies the critical barriers in BIM implementation to push the boundaries toward adopt Digitalization and reduce CO2 emission in Iraqi oil and gas sector. The study can be used as evidence and platform to encourage professionals and practitioners to present more sophisticated tools of BIM in the oil and gas industry, especially for facility and operation management. These findings achieved via oil and gas experts, and it is first time to achieve such findings from a case study in Iraqi oil and gas sector.

Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.

The study aims to predict a low-velocity impact on a plate reinforced with carbon nanotubes (CNTs) using machine learning models.

The first-order shear deformation plate theory (FSDT) is used to express the plate displacements filed. The Hertz nonlinear contact law is used to predict the contact between impactor and plate. Using the energy method and Hamilton’s principle, the motion equations are extracted. The six main parameters considered as inputs to machine learning models are CNTs percentage, impactor radius, plate thickness, plate length and width, CNTs distribution profile and impactor initial velocity. These input parameters are used to predict two impact targets including contact force and contact time.

As the values of the targets are continuous, the machine learning task is considered a regression problem. Therefore, this study uses different regression models to predict the targets. These regression models include linear regression, stochastic gradient descent regressor, Bayesian regression, partial least squares regression, Gaussian process regression, multilayer perceptron regressor, support vector regression and decision tree regression. To validate the effectiveness of the regression models, experiments are designed based on different evaluation metrics. The results of the experiments demonstrate that the machine learning models achieve promising performance in predicting the contact force and contact time based on the input parameters.

Due to the volume of high numerical calculations of impact mechanics to reach the response, the targets of the impact problem are predicted using a variety of machine learning methods.

Nanofluids are used in technology, engineering processes and thermal exchanges. In thermal transfer processing, these are used for the smooth transportation of heat and mass through various mechanisms. In the current investigation, we have examined multiple effects like activation energy thermal radiation, magnetic field, external heat source and especially slippery effects on a bioconvective Casson nanofluid flow through a stretching cylinder.

Several studies used non-Newtonian fluid models to study blood flow in the cardiovascular system. In our research, Lewis numbers for bioconvection and the influence of important parameters, such as Brownian diffusion and thermophoresis effects, are also considered. This system is developed as a partial differential equation for the mathematical treatment. Well-defined similarity transformations convert partial differential equation systems into ordinary differential equations. The resultant system is then numerically solved using the bvp4c built-in function of MATLAB.

After utilizing the numerical approach to the system of ordinary differential equations (ODEs), the results are generated in the form of graphs and tables. These generated results show a suitable accuracy rate compared to the previous results. The consequence of various parameters under the assumed boundary conditions on the temperature, motile microorganisms, concentration and velocity profiles are discussed in detail. The velocity profile decreases as the Magnetic and Reynolds number increases. The temperature profile exhibits increasing behavior for the Brownian motion and thermal radiation count augmentation. The concentration profile decreased on greater inputs of the Schmidt number and magnetic effect. The density of motile microorganisms decreases for the increased value of the bio-convective Lewis number.

The numerical analysis of the flow problem is addressed using graphical results and tabular data; our reported results are refined and novel based on available literature. This method is useful for addressing such fluidic flow efficiently.

This study examines the impact of inter-organisational justice (i.e. distributive, procedural and interactional) in the buyer–supplier relationship on supply risk and, in turn, on a firm’s marketing and financial performance.

A structured survey was administered both online and in-person to Jordan-based manufacturing companies. The 137 responses received were analysed using partial least structural equation modelling.

The study found that while establishing both procedural and interactional justice in the relationship has a negative impact on supply risk, promoting distributive justice, surprisingly, has no impact. Moreover, supply risk was found to be detrimental to the firm’s marketing and financial performance.

This study considers only the direct role of inter-organisational justice in reducing supply risk. Future research could enhance our understanding of this role by exploring the underlying mechanisms and conditions that could govern it.

Managers can alleviate supply risk by ensuring procedural and interactional justice in the relationship through involving suppliers in the decision-making processes, consistently adhering to established procedures and communicating transparent and ample information.

Addressing supply risk can help in maintaining community resilience and economic stability.

The study highlights inter-organisational justice as a new approach to mitigating supply risk. Moreover, by examining how supply risk can affect a firm’s marketing performance, it also highlights a new implication of supply risk. Furthermore, by exclusively examining the impact of supply risk on a firm’s financial performance, the study provides a more nuanced interpretation of the effect of supply risk and how it can be reduced.

Following the COVID-19 pandemic, most higher education institutes shifted to online learning as the sole alternative to continuing education while mitigating the risks imposed by the pandemic. This has raised several concerns regarding students’ learning experience, satisfaction and academic achievement, particularly in countries where students have restrained technological resources (i.e. developing nations). The current research aims to investigate the key factors influencing students’ attitudes, satisfaction and academic achievement among university students in an emerging market context (i.e. Morocco). The moderating effect of students’ motivation to study online was also scrutinized.

The authors propose an integrated conceptual framework that combines the technology acceptance model (TAM) with the outcomes of prior literature related to online learning. Based on data collected from 850 Moroccan university students, the authors empirically tested the conceptual model using a partial least squares (PLS) estimation.

First, attitude toward online learning and satisfaction positively impact university students’ academic achievement; at the same time, attitude positively impacts students’ satisfaction with online learning. Second, students’ satisfaction and attitude toward online learning were found to be mainly influenced by instructor performance, ease of use of the online learning platform, information quality, interactivity and perceived usefulness (PU). Finally, student motivation acts as a moderator, e.g. students with higher motivation to learn online are more likely to develop a favorable attitude toward online learning and can, therefore, accomplish better academic performance.

The current study makes a considerable contribution to the literature by contributing to the on-going debate about the potentials and challenges of online learning, particularly in an emerging country where education remains a considerable challenge. The study findings can help higher education institutes gauge the quality of online education programs and design efficient strategies to develop high-quality online learning for students. Our findings have implications not only for educational institutions and instructors in developing markets but also for the vendors of online course delivery software.