Yap, Sze Chee (2026) Safety technologies adoption model in the Malaysia construction industry. Master dissertation/thesis, UTAR.
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Abstract
The construction industry remains one of the most hazardous sectors, necessitating improved safety management through smart technologies. However, adoption remains limited, particularly in developing nations like Malaysia. This study examines the key enablers and inhibitors influencing smart technology adoption for occupational safety and health management. in the Malaysian construction industry. A tailored Likert-scale questionnaire was distributed to Grade 7 (G7) contractors, yielding 377 responses. Six major adoption drivers were found by factor analysis: organisational capability, cost benefit perception, external environment influence, management commitment, technological acceptability and trustworthiness, and economic viability. Furthermore, facilitators and inhibitors were ranked by mean ranking analysis, which brought to light important obstacles such inconsistent standards, interoperability problems, and the requirement for staff training and managerial support. In order to evaluate the ways in which technological, organisational, economic, and environmental factors influence smart technology perceptions of ease of use (PEU), perceived usefulness (PU), and intention to use (IU), the study also used partial least squares structural equation modelling (PLS-SEM). The results show that PEU has little effect on adoption intentions, whereas PU strongly affects IU. This study offers a road map for removing obstacles and promoting technology-driven, sustainable safety management in Malaysian construction. Keywords: Industrial safety, Technology, Building Construction, Technological change, Automation
| Item Type: | Final Year Project / Dissertation / Thesis (Master dissertation/thesis) |
|---|---|
| Subjects: | H Social Sciences > HD Industries. Land use. Labor T Technology > T Technology (General) T Technology > TH Building construction |
| Divisions: | Institute of Postgraduate Studies & Research > Lee Kong Chian Faculty of Engineering and Science (LKCFES) - Sg. Long Campus > Master of Engineering Science |
| Depositing User: | Sg Long Library |
| Date Deposited: | 10 Sep 2026 21:57 |
| Last Modified: | 10 Sep 2026 21:57 |
| URI: | http://eprints.utar.edu.my/id/eprint/7929 |
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