Organisational Factors of Artificial Intelligence Adoption in the South African Construction Industry
Author(s): |
Motheo Meta Tjebane
Innocent Musonda Chioma Okoro |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Frontiers in Built Environment, February 2022, v. 8 |
DOI: | 10.3389/fbuil.2022.823998 |
Abstract: |
The innovation of technology, particularly Artificial Intelligence (AI), has rapidly changed the world. It is currently at a nascent stage worldwide in the construction industry throughout the lifecycle of projects. However, construction organisations of developing countries such as South Africa are still lagging in recognising the need to adopt emerging digital innovations such as AI to improve the built sector’s performance. This study aims to identify organisational factors imperative to driving the adoption of AI in construction organisations. The study uses a quantitative survey approach to collect data through snowball sampling of industry experts on factors associated with AI adoption. With data from 169 respondents, exploratory factor analysis was adopted to identify critical organisational factors to ease AI adoption in the industry. Furthermore, confirmatory factor analysis was employed to demonstrate the relationship among the constructs. The study proposes 17 factors to drive organisational AI, categorised into four components; innovative organisational culture, competence-based development, collaborative decision-making, and strategic analysis. However, previous studies have identified organisational factors of AI in the construction and allied industries. This study presented the organisational factors of AI in the construction industry using EFA and CFA, a method not used in articles presented in the SLR identified. The use of CFA improves the measurement of the constructs. It thus enhances understanding of the underlying components of a construct and its relationship with AI in the construction industry. |
Copyright: | © Motheo Meta Tjebane, Innocent Musonda, Chioma Okoro |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10665609 - Published on:
09/05/2022 - Last updated on:
01/06/2022