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All Journal Civil Engineering Journal
Benjeddou, Omrane
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Civil Engineering, Building, Construction & Architecture

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The Challenges of Implementing Cognitive Computing in Small Construction Projects: A Data-Driven Perspective Alsehaimi, Abdullah; Alrasheed, Khaled A.; Hayat, Saleh; Nisar, Saad; Benjeddou, Omrane
Civil Engineering Journal Vol 10, No 9 (2024): September
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-09-011

Abstract

This study aims to identify and analyze the challenges of implementing cognitive computing in small construction projects, where decision-making, process optimization, and sustainability enhancements are crucial yet challenging. The research adopts a mixed-methods approach, integrating a thorough literature review, quantitative evaluation, and structural equation modeling (SEM) to explore the relationships between the identified barriers and the effective application of cognitive computing. The findings reveal significant hurdles, including complexity in customization (β = 0.327, t = 9.848, p < 0.001), data integrity and integration issues (β = 0.389, t = 14.534, p < 0.001), financial and cultural constraints (β = 0.295, t = 7.850, p < 0.001), and ethical and privacy concerns (β = 0.319, t = 8.963, p < 0.001). These barriers impede the seamless adoption of cognitive computing technologies. This research contributes novel insights into the specific challenges faced by small construction projects and provides practical recommendations to overcome these obstacles. By addressing these challenges, this study offers valuable guidance for stakeholders aiming to leverage cognitive computing to improve project outcomes in the construction industry. The novelty of this research lies in its focus on small-scale projects, a relatively underexplored area, and its comprehensive analysis of the multifaceted barriers that hinder the successful implementation of cognitive computing. Doi: 10.28991/CEJ-2024-010-09-011 Full Text: PDF
Optimizing Injection Moulding Processes for Structural Components in Construction Management Qurashi, Muhammad Nasir; Xiao, Cheng-Long; Alrasheed, Khaled A.; Benjeddou, Omrane
Civil Engineering Journal Vol 10, No 10 (2024): October
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-10-020

Abstract

The optimization of injection molding processes for structural components is critical in construction management, particularly for enhancing precision, efficiency, and sustainability. However, existing research has not fully addressed the complex interplay of factors that influence this optimization. This study aims to fill this gap by identifying and analyzing five key constructs: Structural Performance, Material Efficiency, Sustainability and Integration, Precision and Consistency, and Design Flexibility. Data were collected from 249 professionals in China using a Likert-scale survey and analyzed through Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). The results show that Structural Performance is the most significant factor (β = 0.943, p < 0.001), followed by Material Efficiency (β = 0.858, p < 0.001) and Sustainability and Integration (β = 0.772, p < 0.001). The model's predictive relevance, with a Q² value of 0.659, confirms its robustness and accuracy. These findings highlight the need for construction managers to focus on improving Structural Performance and Material Efficiency while integrating sustainability and ensuring precision and flexibility. Optimizing injection molding for construction components is challenging due to complex factors like structural performance, material efficiency, and sustainability. This study develops a novel framework using Structural Equation Modeling to rank these factors, providing insights for cost-effective, high-performance outcomes, and advancing sustainable practices in construction management. Doi: 10.28991/CEJ-2024-010-10-020 Full Text: PDF
Geopolymers: Enhancing Environmental Safety and Sustainability in Construction Aiman, Muhammad S.; Othman, Idris; Waqar, Ahsan; Hamah Sor, Nadhim; Isleem, Haytham F.; Najm, Hadee M.; Benjeddou, Omrane; Sabri, Mohanad Muayad Sabri
Civil Engineering Journal Vol 10, No 10 (2024): October
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2024-010-10-015

Abstract

This study underscores the significant environmental advantages of geopolymer, notably its capacity for substantial CO2emission reduction and sustainable waste management by repurposing industrial by-products, enhancing the environmental safety in oil and gas projects. Central to our investigation is the identification and strategic overcoming of critical obstacles to the broader application of geopolymer, aiming to bridge the gap between its recognized potential and practical implementation in construction practices. Through a comprehensive analysis involving pilot, main, and validation surveys among construction industry professionals, we employed exploratory factor analysis (EFA) and structural equation modeling (SEM) to elucidate the relationships between various barriers and the success of geopolymer concrete applications. Our findings reveal that standards and knowledge significantly influence the adoption of geopolymer concrete, with an R² value of 0.873 indicating a high predictive utility of these constructs. The research underscores the critical need for enhanced support in research and development to improve geopolymer concrete's durability and performance over time. Significantly, this study contributes novel insights into overcoming the industry's hesitancy towards geopolymer concrete, highlighting its importance for sustainable construction practices and reducing the environmental footprint of building materials. Doi: 10.28991/CEJ-2024-010-10-015 Full Text: PDF
Co-Authors Aiman, Muhammad S. Alrasheed, Khaled A. Alsehaimi, Abdullah Hamah Sor, Nadhim Hayat, Saleh Isleem, Haytham F. Najm, Hadee M. Nisar, Saad Othman, Idris Qurashi, Muhammad Nasir Sabri, Mohanad Muayad Sabri Waqar, Ahsan Xiao, Cheng-Long