Workforce development: understanding task-level job demands-resources, burnout, and performance in unskilled construction workers

• Published in: Safety science Vol. 123; p. 104577
• Main Authors: Lee, Wonil, Migliaccio, Giovanni C., Lin, Ken-Yu, Seto, Edmund Y.W.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01-03-2020; Elsevier BV
• Subjects: Burnout; Construction industry; Construction materials; Exhaustion; Job demand-resources model; Levels; Materials handling; Multivariate statistical analysis; Observational studies; Occupational health; Occupational safety; Partial least squares structural equation modeling; Personnel management; Productivity; Safety; Task analysis; Wearable sensors; Workforce; Productivity; Job demand-resources model; Burnout; Safety; Wearable sensors; Partial least squares structural equation modeling
• ISSN: 0925-7535; 1879-1042
• DOI: 10.1016/j.ssci.2019.104577

•How job characteristics interact with burnout to influence performance.•Protocols for integrating wearable sensors into burnout research.•The direct effect of personal resources on productivity.•The full mediating effect of exhaustion between task demands and productivity.•The partial mediating effect of disengagement between personal resources and safety.
This study examines how task demands and personal resources affect unskilled construction worker productivity and safety performance. It extends the job demands-resources (JD-R) burnout model to show how job characteristics interact with burnout to influence performance. A modified model was designed to measure burnout, with exhaustion and disengagement among unskilled construction workers taken into consideration. An observational study was conducted in a laboratory environment to test the research hypotheses and assess the prediction accuracies of outcome constructs. Twenty-two subjects participated in multiple experiments designed to expose them to varying levels of task-demands and to record their personal resources as they performed common construction material-handling tasks. Specifically, both surveys and physiological measurements using wearable sensors were used to operationalize the model constructs. Moreover, partial least squares structural equation modeling was applied to analyze data collected at the task and individual levels. Exhaustion and disengagement exhibited different relationships with productivity and safety performance outcomes as measured by unit rate productivity and ergonomic behavior, respectively. Subjects with high burnout and high engagement showed high productivity but low safety performance. Thus, exhausted workers stand a greater chance of failing to comply with safety. As the sample and the task performed in the experiment do not cover the experience and trade of all construction workers, our findings are limited in their application to entry-level and unskilled workers, whose work is mainly manual material-handling tasks.