Social Processes: What Determines Industrial Workers' Intention to Use Exoskeletons?

OBJECTIVE: The aim of this study is to test the unified theory of acceptance and use of technology (UTAUT) model for explaining the intention to use exoskeletons among industrial workers. BACKGROUND: Exoskeletons could help reduce physical workload and risk for injuries among industrial workers. Therefore, it is crucial to understand which factors play a role in workers' intention to use such exoskeletons. METHOD: Industrial workers (N = 124) completed a survey on their attitudes regarding the use of exoskeletons at their workplace. Using partial least squares (PLS) path modeling, the UTAUT model and a revised version of the UTAUT model were fitted to these data. RESULTS: The adapted UTAUT model of Dwivedi et al. (2017) was able to explain up to 75.6% of the variance in intention to use exoskeletons, suggesting a reasonable model fit. CONCLUSION: The model fit suggests that effort expectancy (how easy it seems to use an exoskeleton) plays an important role in predicting the intention to use exoskeletons. Social influence (whether others think workers should use exoskeletons) and performance expectancy (how useful exoskeletons seem to be for work) play a smaller role in predicting the intention to use. APPLICATIONS: This research informs companies about the optimal implementation of exoskeletons by improving the determinants of acceptance among their workers.

The age-dependent influence of self-reported health and job characteristics on retirement.

OBJECTIVES: Social scientists and economists doubt the usefulness of self-reported health status as an indicator of overall health status. Self-reported health acts as a justification for retirement when this decision is in reality driven by other reasons. In this study, we looked at income, job satisfaction, and job status. METHODS: We introduce a survival model (Cox model) that simultaneously includes both health and job characteristics as independent variables. We also take the age-dependent character of these effects into account. RESULTS: An analysis of the European Community Household Panel data did not validate the justification bias with respect to these variables. The addition of job characteristics had no influence on the effect estimates of self-reported health. CONCLUSIONS: We found significant effects for self-reported health as well as for objective health measures. The addition of job characteristics did not contribute to the explanation of the effect of self-reported health falsifying the justification bias hypothesis.