Artificial intelligent technologies for the construction industry: How are they perceived and utilized in Australia?

Artikel

Artificial intelligence (AI) is a powerful technology that can be utilized throughout a construction project lifecycle. Transition to incorporate AI technologies in the construction industry has been delayed due to the lack of know-how and research. There is also a knowledge gap regarding how the public perceives AI technologies, their areas of application, prospects, and constraints in the construction industry. This study aims to explore AI technology adoption prospects and constraints in the Australian construction industry by analyzing social media data. This study adopted social media analytics, along with sentiment and content analyses of Twitter messages (n = 7906), as the methodological approach. The results revealed that: (a) robotics, internet-of-things, and machine learning are the most popular AI technologies in Australia; (b) Australian public sentiments toward AI are mostly positive, whilst some negative perceptions exist; (c) there are distinctive views on the opportunities and constraints of AI among the Australian states/territories; (d) timesaving, innovation, and digitalization are the most common AI prospects; and (e) project risk, security of data, and lack of capabilities are the most common AI constraints. This study is the first to explore AI technology adoption prospects and constraints in the Australian construction industry by analyzing social media data. The findings inform the construction industry on public perceptions and prospects and constraints of AI adoption. In addition, it advocates the search for finding the most efficient means to utilize AI technologies. The study helps public perceptions and prospects and constraints of AI adoption to be factored in construction industry technology adoption.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Journal of Open Innovation: Technology, Market, and Complexity ; ISSN: 2199-8531 ; Volume: 8 ; Year: 2022 ; Issue: 1 ; Pages: 1-23

Klassifikation und Themen

• Klassifikation: Management
• Thema: automation ; big data ; digital twin ; industry 4.0 ; machine learning ; robotics ; social media analytics

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Regona, Massimo ; Yigitcanlar, Tan ; Xia, Bo ; Li, Rita Yi Man
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2022

Weitere Informationen

• DOI: doi:10.3390/joitmc8010016
• Handle: http://hdl.handle.net/10419/274321
• Letzte Aktualisierung: 20.09.2024, 08:22 MESZ