Faculty of Engineering, University of Malaya, Malaysia.
School of Science and Technology, University of Management and Technology, Pakistan.
Int J Occup Saf Ergon. 2022 Dec;28(4):2238-2249. doi: 10.1080/10803548.2021.1984673. Epub 2021 Nov 2.
Work productivity is one of the most important economic measures in the manufacturing industry. However, the physical, psychosocial and individual risk factors of an industrial work environment affect workers' physical or mental health, resulting in work productivity loss, absenteeism and presenteeism. Therefore, this study aims to identify the most critical risk factors and develop statistical models for predicting work productivity loss, absenteeism and presenteeism of garment industry workers. A sample of 224 sewing machine operators was taken for data collection through observation and self-reported studies. The results indicated that the average work productivity loss, absenteeism and presenteeism was 38.21, 2.35 and 37.23%, respectively. Finally, the statistical models of work productivity loss, absenteeism and presenteeism was developed using multiple linear regression with precision of 69.9, 53.7 and 84.0%, respectively. Hence, this study will help garment industries to improve their work productivity by taking initiatives based on the developed models.
工作效率是制造业最重要的经济指标之一。然而，工业工作环境中的物理、心理社会和个体风险因素会影响工人的身心健康，导致工作效率下降、旷工和出勤。因此，本研究旨在确定最关键的风险因素，并为预测制衣业工人的工作效率下降、旷工和出勤建立统计模型。通过观察和自我报告研究，对 224 名缝纫机操作员进行了抽样，以收集数据。结果表明，平均工作效率损失、旷工和出勤分别为 38.21%、2.35%和 37.23%。最后，使用多元线性回归建立了工作效率损失、旷工和出勤的统计模型，其精度分别为 69.9%、53.7%和 84.0%。因此，本研究将有助于制衣业通过基于所开发模型的举措来提高工作效率。
