Version 1
: Received: 10 November 2022 / Approved: 15 November 2022 / Online: 15 November 2022 (11:25:43 CET)
How to cite:
Gambo, N.; Musonda, I. Effect of Fourth Industrial Revolution's Biological Driver on Construction Occupational Related Diseases in Gauteng, South Africa. Preprints2022, 2022110289. https://doi.org/10.20944/preprints202211.0289.v1
Gambo, N.; Musonda, I. Effect of Fourth Industrial Revolution's Biological Driver on Construction Occupational Related Diseases in Gauteng, South Africa. Preprints 2022, 2022110289. https://doi.org/10.20944/preprints202211.0289.v1
Gambo, N.; Musonda, I. Effect of Fourth Industrial Revolution's Biological Driver on Construction Occupational Related Diseases in Gauteng, South Africa. Preprints2022, 2022110289. https://doi.org/10.20944/preprints202211.0289.v1
APA Style
Gambo, N., & Musonda, I. (2022). Effect of Fourth Industrial Revolution's Biological Driver on Construction Occupational Related Diseases in Gauteng, South Africa. Preprints. https://doi.org/10.20944/preprints202211.0289.v1
Chicago/Turabian Style
Gambo, N. and Innocent Musonda. 2022 "Effect of Fourth Industrial Revolution's Biological Driver on Construction Occupational Related Diseases in Gauteng, South Africa" Preprints. https://doi.org/10.20944/preprints202211.0289.v1
Abstract
The persistence of diseases that affect construction workforce as a result of activities on construction sites poses a danger to the sustainable development of the industry. This resulted to a huge loss of skilled labour and economic development of the industry and the entire country. The arrival of the fourth industrial revolution (4IR) technologies urges an urgent need to assess the effect of the technology’s biological driver on the construction occupation related diseases. Therefore, this study is aimed at assessing the effect of 4IR on the construction occupation related diseases in Gauteng, South Africa. The study is quantitative in design and questionnaire survey were administered to project and Health and Safety (H&S) managers in Gauteng, South African construction sector using a proportionate simple random sampling technique. For data analysis, the Warp PLS-SEM 8.0 software algorithm was used for the analysis of the collated data. The study found that the effects of the 4IR’s biological driver variables ranges between moderate to high effects for genome sequencing (GENSE) and Neurotechnology (NEURO) respectively. The combined predictive relevance of the two (2) variables predicts 64% of the construction occupation related diseases. This implies that the adoption of the driver would help reduce the causes of construction-related diseases. Hence, implies that continuous deployment of 4IR technologies would ensure that construction occupation related diseases are easily identified and put on alert.
Keywords
South Africa; fourth industrial revolution’s biological drivers; health and safety; construction occupations; construction-related diseases
Subject
Public Health and Healthcare, Public, Environmental and Occupational Health
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
