Search Results (88)

Workplace health and safety issues have long plagued the construction industry. While safety efforts have traditionally focused on physical risks, increasing attention is being paid to mental health and work-related stressors, which can negatively affect both productivity and safety. In Saudi Arabia, the construction sector presents a unique context because of its highly diverse, multinational workforce. Workers of different nationalities often operate on the same job site, leading to potential communication barriers, cultural misunderstandings, and inconsistent safety practices, all of which may amplify stress and safety risks. This research aims to investigate the influence of work-related stressors on construction workers’ safety in Saudi Arabia and identify which stressors most significantly contribute to the risk of injury. A structured questionnaire was distributed to 349 construction workers across 16 job sites in Saudi Arabia. The survey measures ten key stressors identified in the literature, including job site demand, job control, job certainty, skill demand, social support, harassment and discrimination, conflict with supervisors, interpersonal conflict, and job satisfaction. Data were analyzed using logistic regression and Pearson correlation to examine relationships between stressors and self-reported injuries. The findings indicated that work-related stressors significantly predict workplace injury. While the first regression model showed a modest effect size, it was statistically significant. The second model identified job site demand and job satisfaction as the most influential predictors of injury risk. Work-related stressors, particularly high job demands and low job satisfaction, substantially increase the likelihood of injury among construction workers. These findings emphasize the importance of incorporating psychosocial risk management into construction safety practices in Saudi Arabia. Future studies should adopt longitudinal designs to explore causal relationships over time and include qualitative methods such as interviews to gain a deeper understanding. Additionally, factors such as nationality, organizational policies, and management style should be investigated to better understand their moderating effects on the stress–injury relationship. Full article

Improving construction site safety remains a critical challenge in Saudi Arabia’s rapidly growing construction sector, where high accident rates and diverse labor forces demand evidence-based managerial interventions. This study investigated the influence of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behaviors (WSB) in the Saudi construction industry, emphasizing the mediating roles of Workers’ Safety Awareness (WSA), Safety Competency (WSC), and Safety Actions (SA). The conceptual framework integrates these three mediators to explain how managerial attitudes and practices translate into frontline safety outcomes. A quantitative, cross-sectional design was adopted using a structured questionnaire distributed among construction workers, supervisors, and project managers. A total of 352 from 384 valid responses were collected, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. The findings revealed that MSP does not directly influence WSB but has significant indirect effects through WSA, WSC, and SA. Among these, WSC emerged as the most powerful mediator, followed by WSA and SA, indicating that competency is the most critical driver of safe worker behavior. These results provide robust empirical support for a multidimensional mediation model, highlighting the need for managers to enhance safety behaviors not merely through supervision but through fostering awareness and competency, providing technical training, and implementing proactive safety measures. Theoretically, this study contributes a novel and integrative framework to the occupational safety literature, particularly within underexplored Middle Eastern construction contexts. Practically, it offers actionable insights for safety managers, industry practitioners, and policymakers seeking to improve construction safety performance in alignment with Saudi Vision 2030. Full article

The waste management and recycling industry in Saudi Arabia is facing ongoing challenges in reducing the negative impact resulting from the recycling process. Different types of waste lack an efficient and accurate method for classification, especially in cases that require the rapid processing of materials. A deep learning prediction model based on a convolutional neural network algorithm was developed to classify and predict the types of construction and demolition waste (CDW). The CDW image dataset used contained 9273 images, including concrete, asphalt, ceramics, and autoclaved aerated concrete. The model obtained an overall accuracy of 97.12%. The Green Ground image prediction model is extremely useful in the construction and demolition industry for automating sorting processes. The model improves recycling rates by ensuring that materials are sorted correctly, thus reducing waste sent to landfills, by accurately identifying different types of materials in CDW images. As part of Saudi Arabia’s 2030 sustainability objectives, these steps contribute to achieving a greener future, complying with environmental regulations, and promoting sustainability. Full article

The construction industry continues to generate vast volumes of waste, which harm the environment and negatively impact socio-economic sustainability, especially in a developing country like Saudi Arabia. Prior to investigating effective approaches for managing waste, we must identify the main drivers of construction waste. This paper develops metrics and criteria for identifying and ranking the waste cause factors (WCFs) in the construction of mega-projects in Saudi Arabia. The methodology adopted includes a thorough literature review and a survey ranking waste factors based on a five-point Likert-scale. Data collected from 239 participants across three distinct construction mega-projects were analysed using one-way analysis of variance (ANOVA) with its corresponding post hoc tests, and the identified waste factors were ranked according to their relative importance index (RII). The findings of this study indicate that the main sources of waste in Saudi Arabia involve design changes and complexity, poor project coordination, inefficient waste management systems, lack of supervision, drawing errors, low skill levels among workers and designers, and procurement mistakes. The results and discussions derived from the investigation aim to deepen the understanding of the causes of waste in large-scale construction, which could inform researchers, policymakers, and professionals, whose joint contributions should enable effective waste management strategies in large construction projects. Full article

The Fourth Industrial Revolution (4IR) has accelerated the construction industry’s shift toward digital transformation. This progress is mainly driven by the emergence of innovative technologies, including artificial intelligence (AI) and digital twins (DTs). While global research has extensively explored the benefits and challenges of AI-based DTs, the rapid growth of Saudi Arabia’s construction sector—fueled by substantial local investments and international partnerships—underscores the urgent need to examine their specific impact within this context. To address this gap, this study aims to investigate the potential benefits and challenges of integrating AI-driven DTs into Saudi Arabia’s construction industry. To achieve this, a structured literature review and a survey were conducted among architecture, engineering, and construction (AEC) firms, with 106 complete responses analyzed using correspondence analysis (CA). The findings revealed that AI-driven DTs substantially benefit Saudi Arabia’s construction industry. For example, among the 17 identified benefits, the top-ranked ones include AI capabilities to improve analytics, AI’s facilitation of digital twins in modeling complex real-world systems, and the facilitation of strategic decision making. However, several challenges hinder the realization of these benefits, including a lack of standardization of integrated DT and AI in construction projects, a lack of understanding of AI’s capabilities, a lack of logistics and the limited availability of IT infrastructure, and the complexity of AI algorithms. These findings underscore the transformative potential of integrating AI-driven DTs to optimize construction performance, improve decision-making, and address real-world complexities. This study provides actionable insights for stakeholders and recommends future research exploring strategies for overcoming adoption challenges, fostering technological innovation, and capacity building in Saudi Arabia’s construction sector. Full article

The global building and construction industry faces increasing challenges related to efficiency, performance, and sustainability, which significantly impact project success, particularly in developing economies. The timely and successful completion of building and construction projects is crucial for economic development; however, various barriers hinder effective project execution. This study identifies and empirically analyzes the critical barriers affecting building and construction project performance in two developing countries with distinct economic profiles, Ghana and the Kingdom of Saudi Arabia (KSA). A comprehensive literature review and expert interviews identified fourteen key barriers to project performance, ensuring clarity and technical relevance. Using an empirical questionnaire survey targeting experienced professionals, including contractors, clients, and consultants, the study employed the Relative Importance Index (RII) and Spearman’s correlation analysis to rank and examine the interrelationships between these barriers. The findings reveal that poor communication (RII = 0.831, ranked 1st), project cost and schedule constraints (RII = 0.806, ranked 2nd), and inadequate monitoring and evaluation (RII = 0.786, ranked 3rd) are the most significant barriers to project success in both contexts. These challenges align with global sustainability concerns, particularly Sustainable Development Goal (SDG) 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities), which emphasize resilient infrastructure and sustainable urban development. The study highlights the crucial role of decision makers, regulatory frameworks, and financial planning in overcoming these barriers and enhancing project outcomes. By addressing these constraints, the study provides actionable insights for policymakers, project managers, and industry stakeholders to improve project execution efficiency and foster sustainable building and construction practices. Future research should explore adaptive mitigation strategies and technological innovations that enhance project delivery efficiency in developing economies. Full article

This paper highlights the transition from traditional procurement systems to the newly introduced eProcurement system in Saudi Arabia, emphasizing the differences and improvements and their implications for sustainable development. The new system aims to enhance transparency, clarify purchasing methodologies, and build trust with the government through effective governance of government purchases and tender management. Guided by Royal Decree, this system aligns with the eProcurement Program to transition into digital processes for proficient bids and government purchases, contributing to more efficient and sustainable procurement practices. While some public agencies have attempted to adopt the new model contract for executing construction projects, it has faced challenges due to its lack of alignment with the best practices and sustainability considerations. The authors argue that many large projects remain exempt from this system, which poses obstacles to achieving the goals of sustainable economic development. The objective of this paper is to explore the newly revised Saudi procurement contracts in comparison with traditional public works contracts, with a focus on how they address socio-economic and environmental sustainability. The research provides an overview of various aspects related to public works contracts (PWCs) in Saudi Arabia, including framework agreements, online reverse auctions, industry localization, knowledge transfer, traditional lump sum contracts, two-phase tenders, and construction project competitions, analyzing their alignment with sustainable development goals. There is limited literature on recent models introduced by the Saudi government, but there are extensive resources on general contract law principles and international public policy. This foundation helps with understanding the legal aspects of public works contracts in Saudi Arabia, their alignment with international standards, and their implications for fostering sustainable development. By examining the literature, researchers can gain insights into the legal and policy framework governing public works contracts in Saudi Arabia and their role in promoting sustainability. The importance of this research lies in its comparative analysis, offering valuable insights into the evolution of procurement practices in Saudi Arabia and their contribution to sustainable socio-economic growth. Full article

Science, technology, engineering, and mathematics (STEM) are crucial for economic development and play a significant role in achieving sustainable development goals. Despite this, there is a shortage of skilled STEM professionals and a declining interest in STEM education and careers. The Saudi Vision 2030 goal of economic diversification and sustainable development aims to transform Saudi Arabia into a knowledge-based economy driven by innovation and sustainability. This study investigates factors influencing adolescents’ attitudes toward STEM careers in Saudi Arabia, with comparative insights from Bahrain and Singapore. Structural equation models (SEM) were constructed for each country to analyze the influence of scientific self-concept, school belonging, and teacher effectiveness on students’ choices of science careers. Mediation analysis examined the interest and value of science as mediators in these relationships. Confirmatory factor analysis was conducted to validate model constructs before building SEM models. Data from TIMSS 2019 for eighth-grade students was used to develop model constructs based on relevant items from the student questionnaire. Findings reveal that students’ interest in and value of science significantly influence career decisions, with self-concept and teacher engagement playing crucial roles. Teacher effectiveness had the strongest impact on science interest in Saudi Arabia and Bahrain, while self-concept was most influential in Singapore. These results highlight the importance of fostering teacher engagement and self-concept to encourage students’ career paths in science. To support this, Saudi Arabia should enhance teacher training programs by integrating mentorship, active learning strategies, and technology driven instruction to improve student engagement. Adopting Singapore’s blended learning model can foster self-confidence and independence in STEM education, while hands-on learning and career exposure programs can strengthen students’ self-concept and long-term commitment to STEM fields. Additionally, expanding extracurricular STEM initiatives and industry partnerships will help connect classroom learning to real-world applications. By aligning STEM education reforms with these insights, Saudi Arabia can cultivate a skilled workforce that supports its economic transformation under Vision 2030. Full article

The aim of this study is to examine the factors that drive Saudi Arabian Generation Z’s intention to use voice assistants (VAs) in banking. The Technology Acceptance Model (TAM) was extended by incorporating three additional constructs: subjective norms, which capture the social influence of close relationships, including family and friends; personal innovativeness, which reflects the openness to new technologies that is characteristic of Generation Z; and perceived trust, which addresses concerns related to security and reliability that are critical in financial contexts, thereby enhancing our understanding of this phenomenon among Generation Z. A survey of 292 Generation Z respondents was collected and structural equation modeling (SEM) was employed for data analysis. The findings of the study reveal that factors such as perceived usefulness, attitude, subjective norms, personal innovativeness, and perceived trust all have a significantly positive impact on Generation Z’s intention to use AI-enabled VAs in banking. Additionally, the results indicate that perceived usefulness is influenced by ease of use, while attitude is affected by ease of use, perceived usefulness, personal innovativeness, and trust. Despite the Saudi government’s support and initiatives for the development of the AI-fintech industry, there is still a lack of understanding about consumer behavioral intention toward AI-enabled VAs in Saudi Arabia and, particularly among Generation Z. This study contributes to the existing literature and provides valuable recommendations for policymakers and fintech service providers seeking to implement effective AI-enabled VAs that enrich consumers’ engagement and experience. Full article

The food industry at the global and local levels is increasingly exposed to severe challenges and disruptions because of rising consumer demands, and rigorous and strict local and international regulations related to food safety and environmental concerns, all of which necessitate the adoption of proven and recognized management philosophies and sustainable practices to run the manufacturing process. Although the food manufacturing industry has adopted total quality management, lean manufacturing practices, and other management philosophies, more efforts are still needed to enhance sustainable performance. The purpose of this study is to explore the integrated impact of TQM and lean manufacturing on the sustainability performance of the food manufacturing industry in Saudi Arabia. Moreover, it investigates the causal relationship between TQM and sustainability performance as well as the direct relationship between TQM and lean manufacturing. The survey questionnaire is used as the primary instrument for collecting data from food manufacturing organizations. Based on the literature review, a theoretical framework is built to hypothesize relationships between the constructs. A structural equation modeling and artificial neural network (SEM-ANN) combined approach is used to analyze the results. The findings of the present study show that TQM and lean manufacturing have a positive impact on sustainability performance. The study also identifies the list of valid constructs for total quality management and lean manufacturing, with a high impact of sustainability performance dimensions. Full article

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. Full article

This research examines the proposition that enhancing sustainable innovation can be particularly effective when the focus is on strategy, machine learning, and digitalization. The study specifically targets the complex interactions among strategic alignment (SA), sustainability-oriented innovation (SOI), and digital transformation (DT) within small and medium-sized enterprises (SMEs) in Saudi Arabia, particularly within the service sector. A moderated mediation framework was constructed to analyze the influence of SA on SOI, the mediating role of DT, and the moderating effect of strategic orientation (SO). Data were collected through structured surveys from 339 SMEs using a quantitative research design and a cross-sectional methodology. The partial least squares structural equation modeling (PLS-SEM) technique was employed to validate the proposed framework and hypotheses. The results indicate that SA significantly boosts SOI, with DT acting as a strong mediator in this connection. Furthermore, SO moderates the relationships between SA and SOI, SA and DT, and DT and SOI, highlighting its essential role in shaping the dynamics of sustainable innovation. These findings emphasize the necessity of aligning strategic initiatives with digital advancements to foster innovation that achieves a balance among economic, social, and environmental objectives. This study contributes to existing literature by filling the research gap regarding SOI and DT in Saudi SMEs and offers practical insights for SMEs facing sustainability challenges. Future research should delve deeper into digital technology configurations, industry-specific contexts, and cross-national applications to improve the applicability of these findings. Full article

The effective selection of highway projects is essential for driving economic growth and facilitating trade in Saudi Arabia’s cities. However, current studies lack a comprehensive approach that assesses highways based on a full spectrum of economic, environmental, and social cost–benefit factors tailored to Saudi Arabia’s construction industry. This study addresses this gap by developing a framework that incorporates the aspects. The methodology comprises five steps: (1) a literature review to identify benefit and cost criteria; (2) expert surveys to select significant criteria; (3) the application of the stepwise weight assessment ratio analysis (SWARA) method to determine criteria weights; (4) structured expert interviews to establish criteria quality weights; and (5) validation through application to three case studies, comparing the results with those obtained using the ANP method. The findings show that economically efficient road choices yield increased productivity and support industrial growth, while the most significant environmental benefit is reducing carbon emissions. Social benefits, as emphasized by experts, include accident reduction. Cost factors are also considered, with savings on vehicle operation costs identified as the most significant, as opined by the expert surveyed. Among the analyzed highways, Khurais Road, Riyadh, was the most efficient from the SWARA approach, with a value of 0.8, and the ANP case study conducted, with a normalized score of 0.045 and 0.230 for both benefits and cost criteria. Full article

Existing research has primarily focused on investigating barriers in developed countries, emphasising economic, technical, and governmental factors which impede the diffusion of green building practices. However, developing regions, including the Middle East, often must be represented in green building research. Understanding these region-specific barriers is important for developing tailored solutions. In addition, existing identified green building barriers have primarily been obtained from the industry sector, while perspectives from other stakeholders, such as academia, have less attention. Hence, this study compares the perspectives of academic and industry professionals regarding the possible barriers which may impede the adoption of green buildings, with a particular focus on cultural, educational, and social factors. A mixed-method approach was employed, including a large-scale survey (n = 1112) with 54% of the participants being from the industrial sector and 46% being from the academic sector, as well as 17 semi-structured interviews to triangulate the data obtained from the survey. The study was conducted in Saudi Arabia as a representative case of the Middle East. Participants reported 23 barriers, which were themed into six groups: economic, technical, governmental, market demand, educational, and cultural barriers. Notably, seven of these barriers were reported for the first time in this study, including a lack of integrating green building concepts into university curricula, cultural preferences for traditional construction practices, resistance to change, prioritisation of economic factors over environmental and social considerations, a limited number of completed green building projects, delays in the permit and approval processes, and a lack of leadership and coordination. The statistical analysis revealed significant differences between the industry and academic perspectives (p < 0.05, d = 0.61) regarding the barriers to adopting green buildings, with academics over-reporting the educational, cultural, and technical barriers compared with the industry sector. Based on the identified barriers, five strategies were suggested which could help promote the widespread adoption and long-term sustainability of green buildings in the Middle East. Full article

The Fourth Industrial Revolution (Industry 4.0) has profoundly transformed industries worldwide through the integration of advanced digital technologies, including artificial intelligence, digital twins, building information modeling (BIM), and the Internet of Things (IoT). The Architecture, Construction, and Engineering (ACE) sectors are increasingly adopting these innovations to meet the evolving demands of the global market. Within this dynamic context, Saudi Arabia has emerged as a front-runner and significant investor in this sector, as evidenced by the launch of ambitious mega-projects such as NEOM and The Line. These developments prompt valuable discussions about the readiness of graduates to adapt to rapid technological advancements and meet the current demands of the Saudi market. Although numerous studies have explored this issue, the Saudi context presents unique challenges and opportunities due to the accelerated pace of change within the ACE sectors, driven by the goals of Vision 2030. For this reason, this paper aims to address this gap by exploring the readiness of architectural programs in the context of Saudi Arabia to meet the demands of Industry 4.0. To achieve this, a comprehensive literature review was conducted, developing an analytical framework. Subsequently, a multiple-cases approach was employed, with an overall top-level discussion on the undergraduate architecture program subjects available in the five regions in Saudi Arabia. A combination of field observations, domain expertise, and evidence-based coding methods was employed to develop the SWOT analysis. The SWOT framework was utilized to identify key strengths, weaknesses, opportunities, and threats within the current academic programs. The findings were then analyzed in a comprehensive discussion, highlighting necessary transformations in existing programs. The methodology employed in our study involves prolonged engagement and persistent observation to enhance the quality and credibility of the discussion. This paper serves as a roadmap for guiding future educational reforms and aligning architectural education with emerging industry demands and technological advancements in the field. Four key themes are essential for aligning architectural education with Industry 4.0: sustainability in the built environment, innovation and creativity, digital applications in the built environment, and entrepreneurship and leadership in venture engineering. It also strongly emphasized sustainability courses and noted notable deficiencies in preparing students for a digitally driven professional landscape. For example, the average program comprises 162 credit hours and 58 courses, with only six related to Industry 4.0. The top five institutions offering Industry 4.0 courses ranked from highest to lowest are ARCH-U11, ARCH-U8, ARCH-U3, ARCH-U4, and ARCH-U15. ARCH-U11 offers the most Industry 4.0 courses, totaling 15, which account for 26.8% of its courses and 15% of its credit hours, in contrast to ARCH-U20, which offers no courses. The novelty of this research lies in its comprehensive analysis of the readiness of architecture program curricula from 20 Saudi universities to meet the requirements of Industry 4.0. Importantly, these findings support previous studies that established guidelines that mandate the inclusion of sustainability, innovation, and digital skills in architectural education programs. Contribution to the knowledge and findings is valuable for educational institutions, policymakers, and industry leaders, offering insights into evolving architectural education to meet future industry demands and foster technological innovation and sustainable development. Moreover, it provides actionable recommendations for curriculum development in alignment with Vision 2030. Contrary to expectations, findings show that lower-ranked universities offer more Industry 4.0-related courses than higher-ranked ones, emphasizing the need to align university evaluation standards with labor market demands. Full article