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In this study, construction-related carbon emissions were evaluated across different countries, utilizing 7038 observations from 1990 to 2023. Building and cement production data were combined with economic and demographic indicators to perform descriptive analysis, principal component analysis (PCA), and multiple regression modeling for emission driver identification and the development of the Construction Carbon Sustainability Index (CCSI). The results of this study demonstrate that cement production, combined with building activities, generates the most significant emissions, while population expansion and urban growth patterns create the highest levels of emission intensity. The two main components from the PCA explain more than 80% of national emission patterns through their combination of “Cement and Building Emission Intensity” and “Economic and Urban Development Drivers.” The CCSI shows that OECD and G20 nations achieve the best construction sustainability results, whereas China and India produce the most carbon emissions due to their rapid development, which relies heavily on resource utilization. The findings demonstrate that sustainable construction requires both production efficiency improvements and policy reforms to establish a global standard for construction sector growth that meets net-zero emission targets.

This study establishes the Construction Embodied Energy and Emissions Index (CEEEI) to assess the comprehensive environmental impacts of construction work in 148 countries from 2000 to 2023. The index combines data on material, energy, and carbon intensity from four international open databases. The three latent components derived from Principal Component Analysis (PCA) account for 72.1% of the total variance. They are categorized into the following factors: Economic–Urban Development, Carbon Governance, Industrial Carbon and Material Intensity, and Energy Source and Decarbonization Structure. The CEEEI adjusted (CEEEIadj) evaluates countries based on their embodied efficiency, revealing that developed nations, including the UK, Netherlands, and Sweden, have the lowest embodied emissions, whereas fast-urbanizing, fossil-dependent countries perform poorly. The regression analysis shows that GDP per capita, urbanization rates, and fossil energy consumption ratios are vital determinants of embodied intensity. This study offers a reproducible open-data system that enables construction organizations worldwide to develop decarbonization policies.

This study explores the opportunities and challenges of integrating artificial intelligence (AI) into engineering education. Through a review of the literature and a qualitative focus group study, an assessment was made for the role of AI in personalizing learning, enhancing simulation engagement, providing real-time feedback, and preparing students for AI-integrated workplaces. The study emphasizes how AI may significantly improve educational experiences by making them more dynamic, interactive, and successful. It also draws attention to important issues, such as moral questions, algorithmic biases in AI, infrastructure constraints, the need for AI literacy training for educators, and a range of student perspectives on AI engineering education. The results support a systematic approach to AI integration, highlighting the necessity of cooperative efforts by educators, legislators, curriculum designers, and technologists in order to overcome these obstacles. The study makes the case that AI can transform engineering education by negotiating these challenges and providing students with the information and skills needed for the digital future, all the while assuring fair and moral access to technology-enhanced learning.

Cost overruns represent a continuous challenge within the construction industry, frequently affecting the success of projects. This study explores the factors influencing cost during the construction phase in Saudi Arabia, utilizing data from a survey of 1076 engineers working in the Saudi construction industry. The results identify a number of cost-related factors, including inadequate project management, poor cost estimation, and design errors. Interestingly, some factors, such as currency exchange rate fluctuations and social and cultural influences, were found to have a limited impact on construction costs. Furthermore, the study highlights the role of experience and education level in shaping engineers’ perceptions of these cost factors. The study employs statistical analysis, including Pearson’s chi-squared test, to demonstrate associations between demographics, project characteristics, and cost-influencing factors. The findings suggest the need for refined project management practices, enhanced technical training, and the implementation of digital technologies such as Construction 4.0 to mitigate cost-related risks. This research provides significant insights for construction professionals and policymakers seeking to enhance cost management within the Saudi construction sector, thereby contributing to the ongoing development initiatives aligned with Saudi Arabia’s Vision 2030.

Cost overruns present a continuing challenge within the construction industry worldwide, carrying substantial financial consequences for project stakeholders, specifically in developing economies such as Saudi Arabia. This study employs a dual-method approach combining Principal Component Analysis (PCA) and Analysis of Variance (ANOVA) to comprehensively analyze the factors influencing construction cost during the construction phase in Saudi Arabia. Utilizing survey data collected from 1076 engineers working in the construction industry of Saudi Arabia, PCA identified three key components: (1) project management and technical deficiencies, (2) external and regulatory influences, and (3) financial and economic risks. Meanwhile, the ANOVA examined differences in the perception of those factors across several demographics and project-specific characteristics. Findings highlight critical areas where focused intervention could improve cost management practices. Combining these results, this study presents an integrated framework for construction industry stakeholders with helpful recommendations. This integrated analysis provides a robust framework for construction professionals and policymakers to prioritize cost management strategies, in accordance with Saudi Arabia’s Vision 2030 goals to encourage a resilient and efficient construction industry.

The construction industry relies on the Internet of Things (IoT) and wearable technologies to enhance workplace safety. This research investigates the use of IoT and wearable technology among Saudi Arabian construction sector employees, analyzing their implementation difficulties and the factors contributing to successful implementation. A structured questionnaire was distributed to 567 construction professionals across different roles and projects. Frequency analysis was used to study adoption patterns, chi-square tests to study demographic factors, and principal component analysis for exploratory factor analysis to discover hidden adoption factors. The findings show that smart safety vests and helmets receive the highest level of recognition. On the other hand, advanced monitoring systems, including fatigue and environmental sensors, are not used enough. Group differences in device adoption were investigated in terms of years of experience, academic qualification, job role, and project budget. The findings from factor analysis show that three main factors determine adoption rates, which include (1) safety and operational effectiveness, (2) worker acceptance and support structures, and (3) technical and adoption barriers. A data-driven system is created to help policymakers and industry leaders accelerate construction safety digitalization efforts.

Renewable energy has become an important element of today’s modern technology targeting high-efficiency energy production. As part of its 2030 Vision, Saudi Arabia is aiming to increase its energy production through renewable sources. The purpose of this research study is to explore the factors affecting public willingness to adopt renewable energy technologies in the western region of Saudi Arabia. This was achieved through an extensive literature review of previous studies conducted worldwide and resulted in the extraction of 19 factors that affect public willingness to adopt renewable energy technologies. Following a quantitative research design, random cross-sectional data of 416 participants using the extracted factors were collected via an online questionnaire survey. Following a dimension reduction statistical approach, key components were extracted with exploratory factor analysis using principal component analysis. Five main components clustering the 19 extracted factors were revealed: cost and government regulations and policies, public awareness and local market, environment and public infrastructure, residential building, and renewable energy technology systems. The implications of this research study assist in guiding governments, regulations and policy makers, marketing agencies, and investors to better understand the concerns and enablers of renewable energy technologies adoption from the public perspective.

The hazardous nature of the construction industry requires giving increasing attention to safety management and the available means to eliminate or reduce the risks of workers’ injuries. Workers in the construction industry of Saudi Arabia face similar daily risks as workers face in other countries. The safety climate significantly influences safety performance, making research in the field of safety climate a vital step toward raising safety levels at construction sites. This study aims at exploring key components of determinants for safety climate evaluation of Saudi Arabian construction sites. Using data collected from 401 industry practitioners, a dimension reduction statistical approach and exploratory factor/principal component analysis were conducted on 13 safety climate factors that were found to significantly correlate with safety climate evaluation of construction sites. The study revealed three key components of determinants for safety climate evaluation of Saudi Arabian construction sites. Notable components are safety commitment, safety interaction, and safety support. Implications of this study include assisting construction industry stakeholders to bolster the safety climate at their construction sites, which should lead to improved safety performance levels.

Workers’ wellbeing and safety is important in the construction industry due to the high risk of accidents. Safety climate development is a positive initial step toward raising the safety levels of construction practitioners. This study aims at revealing the factors influencing safety climate perceptions in the construction industry of Saudi Arabia. A set of extracted factors from the literature was validated and used to design a comprehensive questionnaire survey. Data was collected from 401 personnel working on 3 large construction project sites in Saudi Arabia. Descriptive statistics and the crosstabulation algorithm, Kendall’s tau-b correlation test, were used to analyze the data. The study revealed a set of 13 factors influencing safety climate perceptions, which are: Supervision, guidance and inspection, appraisal of risks and hazards, social security and health insurance, workmate influences, management safety justice, management commitment to safety, education and training, communication, workers’ safety commitment, workers’ attitude toward health and safety, workers’ involvement, supportive environment, and competence. The results also indicate the significant and anticipated role of top management in safety climate at sites. Implications of this study include assisting construction industry stakeholders to better understand and enhance safety climate, which in turn will lead to improved safety behavior, culture, motivation, and performance.

The purpose of this research study is to reveal the current status of and the willingness to adopt renewable energy technologies in the western region of Saudi Arabia. The main contribution of this work is the revealed levels of background knowledge presented on six types of renewable technologies, as well as five willingness perspectives on adoption by different sociodemographics. This was achieved following a quantitative research study to randomly collect cross-sectional data from 416 participants using a carefully designed questionnaire survey. Descriptive and inferential statistics were used to analyze the collected data. Results of the study provided and ranked the background knowledge of participants’ viewpoints on six renewable energy sources. It was revealed that education is paramount in increasing the level of awareness of renewable energy technologies. The results also ranked the five willingness perspectives to adopting renewable energy technologies. It was revealed that the economic factor is the main factor influencing the willingness to adoption. The analysis also showed that age was an important factor influencing the adoption of these technologies. This research study acts as a guide assisting energy policy-makers, government agencies, and investors in designing better-targeted public awareness and marketing campaigns on renewable energy technologies. This is in turn will assist in achieving the energy efficiency and production targets of Vision 2030 in Saudi Arabia.