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Revolutionizing construction: A cutting-edge decision-making model for artificial intelligence implementation in sustainable building projects.
Kineber, Ahmed Farouk; Elshaboury, Nehal; Oke, Ayodeji Emmanuel; Aliu, John; Abunada, Ziyad; Alhusban, Mohammad.
Afiliación
  • Kineber AF; College of Project Management, Built Environment, Asset & Maintenance Management, School of Engineering and Technology, Central Queensland University, Melbourne, Australia.
  • Elshaboury N; Department of Civil Engineering, Canadian International College, 6th October City, Zayed Campus, Giza, 12577, Egypt.
  • Oke AE; Construction and Project Management Research Institute, Housing and Building National Research Center, Giza, 12311, Egypt.
  • Aliu J; Department of Quantity Surveying, Federal University of Technology, Akure, 340110, Nigeria.
  • Abunada Z; Institute for Resilient Infrastructure Systems, College of Engineering, University of Georgia, Athens, GA, USA.
  • Alhusban M; School of Engineering and Technology, Central Queensland University, Melbourne, VIC, 3000, Australia.
Heliyon ; 10(17): e37078, 2024 Sep 15.
Article en En | MEDLINE | ID: mdl-39286223
ABSTRACT
This study examines how certain artificial intelligence (AI) drivers affect the industry's adoption of this technology in the construction industry. The research methods comprised a comprehensive analysis of previous studies to pinpoint the primary factors influencing AI adoption in the construction industry. Data collection was carried out through a well-structured survey involving relevant stakeholders in the building construction sector. The three main constructs of technological devices, advancement, and knowledge were found from the set of drivers with the technique of exploratory factor analysis. The deployment of AI in construction has the potential to improve health and safety and expedite project completion, as this research has evaluated. To figure out how these factors relate to the adoption of AI in the construction industry, partial least squares structural equation modeling was used. The study's conclusions showed that the influence of AI installation in the construction industry is reasonably significant thanks to the technology, advancement, and knowledge, contributing around 15 % of the effects that have been directly witnessed. The practical implications of AI for policy makers, engineers, and construction stakeholders are extensive and provide valuable insights for customized strategies aimed at using AI's potential to improve projects, promote sustainability, and elevate health and safety standards.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article País de afiliación: Australia Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Heliyon Año: 2024 Tipo del documento: Article País de afiliación: Australia Pais de publicación: Reino Unido