This study aims to examine how hospitality employees cognitively appraise techno-uncertainty arising from service robot adoption and how such appraisals translate into task crafting behaviours. It also investigates the moderating role of person–job misfit (PJM) in shaping employees' appraisal responses to techno-uncertainty.
Data were collected through an online survey of 153 hospitality employees with direct experience working alongside service robots. The proposed research model was tested using partial least squares structural equation modelling (PLS-SEM).
The findings demonstrate that techno-uncertainty positively influences challenge and hindrance appraisals, each of which subsequently shows a positive relationship with task crafting, thus supporting dual appraisal pathways. Furthermore, PJM strengthens the relationship between techno-uncertainty and hindrance appraisal.
To reduce employees' techno-uncertainty, managers should provide advance notices of robot-related updates and provide training on new robot functions. Employees should also be granted sufficient autonomy to adjust their work tasks in response to uncertain technological changes. Finally, managers should reduce PJM by aligning job demands with employees' capabilities for robot implementation.
This study incrementally extends appraisal-based technostress research to service robot workplaces by examining the dual primary appraisal pathways that link robot-induced techno-uncertainty to task crafting. It also demonstrates that PJM strengthens the hindrance appraisal pathway.
