Factors Influencing the Adoption of Artificial Intelligence Technologies in the South African Construction Industry
| dc.contributor.author | Mgolombane, Pumza Portia | |
| dc.contributor.supervisor | Matshabaphala, Manamela | |
| dc.date.accessioned | 2024-08-07T11:54:58Z | |
| dc.date.available | 2024-08-07T11:54:58Z | |
| dc.date.issued | 2023 | |
| dc.description | A research report submitted in partial fulfillment of the requirements for the degree of Master of Business Administration to the Faculty of Commerce, Law and Management, Wits Business School, University of the Witwatersrand, Johannesburg, 2023 | |
| dc.description.abstract | The study aimed to evaluate factors influencing the adoption of artificial intelligence technologies within the South African Construction Industry. The focus was to employ AI technology adoption strategies to enhance the construction industry’s’ performance in ensuring effectiveness and efficiency on productivity through organisational development. Since the construction industry is notorious for its resistance to integrating new technology; for example, it is more likely to continue working manually than to apply digitalisation. As a result, the slow adoption of technology is likely to have an impact on the effectiveness and efficiency of the construction industry building practices. Therefore the studies objectives were to assess, the adoption of AI technology strategies and its impact on effectiveness and efficiency within the construction industry. Moreover, opportunities and constraints of AI adoption by the construction industry to help improve its productivity. Also, the organisational development phenomenon within the construction industry and its effect on AI Technology adoption. This study employed a case study research method to obtain a comprehensive understanding and empirical questions were established in the literature based on the study’s’ aims and objectives. The quantitative data was administered through the Qualtrics tool whereby a survey link was obtained and then emailed to the participants. The data was analysed using Statistical Package for the Social Sciences tool (SPSS) version 27. 51 Respondents participated in the survey however, 9 were excluded because of incomplete surveys. According to the results of the data analysis, it was concluded that the employment of AI technology techniques may have an impact on the effectiveness and efficiency of the building sector, making this objective relevant to this study. Moreover, AI adoption by the construction industry may increase productivity by understanding the opportunities and limitations of adopting AI. Also, the phenomena of organizational development within the construction industry may impact on the adoption of AI Technology was found to be significant | |
| dc.description.sponsorship | NHBRC | |
| dc.description.submitter | MM2024 | |
| dc.faculty | Faculty of Commerce, Law and Management | |
| dc.identifier.citation | Mgolombane, Pumza Portia. (2023). Factors Influencing the Adoption of Artificial Intelligence Technologies in the South African Construction Industry [Master’s dissertation, University of the Witwatersrand, Johannesburg]. WireDSpace.https://hdl.handle.net/10539/40020 | |
| dc.identifier.uri | https://hdl.handle.net/10539/40020 | |
| dc.language.iso | en | |
| dc.publisher | University of the Witwatersrand, Johannesburg | |
| dc.rights | © 2023 University of the Witwatersrand, Johannesburg. All rights reserved. The copyright in this work vests in the University of the Witwatersrand, Johannesburg. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of University of the Witwatersrand, Johannesburg. | |
| dc.rights.holder | University of the Witwatersrand, Johannesburg | |
| dc.school | WITS Business School | |
| dc.subject | The Construction Industry | |
| dc.subject | Artificial intelligence | |
| dc.subject | Professional Construction Project Manager | |
| dc.subject | Organizational development | |
| dc.subject | Organizational architecture and Technology | |
| dc.subject | UCTD | |
| dc.subject.other | SDG-9: Industry, innovation and infrastructure | |
| dc.title | Factors Influencing the Adoption of Artificial Intelligence Technologies in the South African Construction Industry | |
| dc.type | Dissertation |