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Using IoT devices for sensor-based monitoring of employees' mental workload: Investigating managers' expectations and
Sebastian Pütz1, Vera Rick1, Alexander Mertens1
1Institute of Industrial Engineering and Ergonomics, RWTH Aachen University, Eilfschornsteinstr. 18, 52062, Aachen, Germany.
Abstract:
Although the objective assessment of mental workload has been a focus of human factors research, few studies have investigated stakeholders' attitudes towards its implementation in real workplaces. The present study addresses this research gap by surveying N = 702 managers in three European countries (Germany, United Kingdom, Spain) about their expectations and concerns regarding sensor-based monitoring of employee mental workload. The data confirm the relevance of expectations regarding improvements of workplace design and employee well-being, as well as concerns about restrictions of employees' privacy and sovereignty, for the implementation of workload monitoring. Furthermore, Bayesian regression models show that the examined expectations have a substantial positive association with managers' willingness to support workload monitoring in their company. Privacy concerns are identified as a significant barrier to the acceptance of workload monitoring, both in terms of their prevalence among managers and their strong negative relationship with monitoring support.
