Cloud Computing has become a valuable platform for sustainability in many countries. This study evaluates the cloud computing implementation and its Critical Success Factors (CSFs) towards ensuring sustainable construction projects in Nigeria. Data were collected from previous literature, supplemented by a quantitative approach via a questionnaire survey. Data were collected from 104 construction professionals while cloud computing CSFs were examined using Relative Importance Ranking (RII) and Exploratory Factor Analysis (EFA). The results show that cloud computing’s awareness level is 96.2%, which means that the respondents are aware of cloud computing concept. Furthermore, the result shows that most of the respondents are adopting the concept. The analysis of the CSFs indicated that reliable data storage, performance as well as cost of accessibility and availability were the four most significant CSFs to cloud computing applications. Analysis of the CSFs through EFA generated four main components which include human satisfaction, organization, client’s acceptance, and industry-based. Consequently, this study contributed to existing body of knowledge by highlighting the cloud computing CSFs for achieving sustainable construction project. As such, the results could be a game-changer in the construction industry—not only in Nigeria but also in developing nations where construction projects are implemented through similar style and procedure. This study would be a benchmark for supporting decision-makers to improve data fragmentation, in which the use of data is paramount to the execution of construction works. Finally, the results of this study would be useful for enhancing sustainability and general management of construction projects through cloud computing implementation.

Recent advancements in Artificial Intelligence (AI) are reshaping architectural design by enhancing key design techniques such as spatial planning, parametric modeling, generative design, and performance-based analysis. AI methods like machine learning (ML) and predictive modeling support tasks from material selection to structural optimization, improving efficiency, sustainability, and creativity. By analyzing large datasets and automating complex processes, AI empowers architects to explore innovative solutions responsive to user needs and environmental factors. This study systematically reviews how AI plays a part in the architectural workflow, focusing on its ability to enhance creativity, automation, and sustainability. A structured literature review was conducted using the PRISMA framework to review peer-reviewed studies on AI applications in architectural design, urban planning, and smart cities published between 2003 and 2025. The reviewed studies demonstrate that AI enhances generative design, streamlines spatial organization, and supports sustainable architecture. However, challenges such as algorithmic bias, ethical concerns, and loss of architectural identity persist. Future research should emphasize ethical implementation, interdisciplinary collaboration, and integration with VR/AR to enable immersive, real-time, and informed design processes.

Purpose: The purpose of this paper is to investigate the applicability of cloud computing (CC) and the challenges that contribute to more successful projects with a major sustainable construction development.Design/methodology/approach: The previous studies provided information on CC implementation barriers, which were then evaluated by 104 construction stakeholders through a questionnaire survey. As a result, the exploratory factor analysis (EFA) approach was used to investigate these barriers. Furthermore, a partial least square structural equation model was used to build a model of these barriers (PLS-SEM).Findings: The EFA results revealed that the above-noted factors are in a close relation with three key components, i.e. social, economic and communication. In addition, the proposed model results found the social barrier a key challenge to the implementation of CC.Research limitations/implications: The results from this study can help decision-makers to improve the approaches regarding data fragmentation that has great effects on the execution of all construction projects. The focus of the paper is to enhance the data fragmentation processes. In addition, the results would be useful to strengthen the sustainability of existing construction projects by enhancing the implementation of CC.Originality/value: The novelty of this research work will provide a solid foundation for critically assessing and appreciating the different barriers affecting the adoption of CC.

Purpose: The purpose of this paper is to evaluate the barriers militating against the adoption of robotics in the construction industry.Design/methodology/approach: Robotics implementation barriers were obtained from the previous studies and then through questionnaire survey construction stakeholders in Nigeria evaluate these barriers. Consequently, these barriers were examined via the exploratory factor analysis (EFA) technique. Furthermore, a model of these barriers was implemented by means of a partial least square structural equation modeling (PLS-SEM).Findings: The EFA results showed that these barriers could be categorized into two: cost and technology. Results obtained from the proposed model showed that platform tools were crucial tools for implementing cloud computing.Originality/value: The novelty of this research work will be provided a solid foundation for critically assessing and appreciating the different barriers affecting the adoption of robotics.