Artificial Intelligence (AI)-Based Technology Adoption in the Construction Industry: A Cross National Perspective Using the Technology Acceptance Model

Article


Na, S., Heo, S., Choi, W., Kim, C. and Whang, S. 2023. Artificial Intelligence (AI)-Based Technology Adoption in the Construction Industry: A Cross National Perspective Using the Technology Acceptance Model. Buildings. 13 (10), p. 2518. https://doi.org/10.3390/buildings13102518
AuthorsNa, S., Heo, S., Choi, W., Kim, C. and Whang, S.
Abstract

The research has chosen the workers in construction-related companies in South Korea and the United Kingdom (UK) as research subjects in order to analyse factors that influence their usage intention of Artificial Intelligence (AI) based technologies. The perceived usefulness had a positive impact (+) on technological satisfaction and usage intention in terms of the commonalities shown by the construction industry workers in both countries, South Korea and the UK, in adopting AI-based technologies. Moreover, the most remarkable differences were personal competence and social influence when choosing AI-based technologies. It was analysed that in the case of South Korea, personal competence had a positive impact (+) on perceived ease of use, whereas the UK had
a positive impact (+) on perceived usefulness and perceived ease of use. This study holds particular significance in the domain of cross-cultural research within the construction industry. It conducts an analysis of the factors influencing the adoption of AI-driven technologies or products, with a specific focus on the cultural differences between two nations: South Korea and the UK, which represent Eastern and Western cultural paradigms, respectively.

KeywordsArtificial intelligence; Construction industry; Technology acceptance model; Cross culture; Structural equation model
JournalBuildings
Journal citation13 (10), p. 2518
ISSN2075-5309
Year2023
PublisherMDPI
Publisher's version
License
File Access Level
Anyone
Digital Object Identifier (DOI)https://doi.org/10.3390/buildings13102518
Publication dates
Online04 Oct 2023
Publication process dates
Accepted26 Sep 2023
Deposited25 Oct 2023
Copyright holder© 2023, The Authors
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