Assessing the impact of human-robot collaborative order picking systems on warehouse workers

Robotisation is increasing in warehouse operations, but human employment continues to be relevant. Traditionally manual activities, such as order picking, are being re-designed into collaborative human-robot tasks. This trend exemplifies the transition towards a human-centric Industry 5.0, focusing on synergy instead of seeking human replacement. However, human workers are increasingly hard to recruit and retain. We contribute to the underrepresented literature on human factors within the domain of operations and production management research and investigate the deployment of robotic technologies alongside human workers in a sustainable way. With a unique real-effort experiment, we investigate how the manipulation of picker's experienced levels of autonomy affects their job satisfaction and core self-evaluations, two key behavioural outcomes that determine employee turnover intentions. We establish that the introduction of human-robot collaboration positively affects job satisfaction for the contrasting collaboration dynamics of (i) gaining control (the human leading the robot) and (ii) ceding control (the human following the robot). This positive effect is larger when the human is following the robot. We additionally find that following the robot positively affects pickers' self-esteem and that self-efficacy related to human-robot interaction benefits from the introduction of collaborative robotics, regardless of the setup dynamics.

Automated summary

Robotisation is becoming more common in warehouse operations, but human employment remains relevant. The traditional manual activities are being transformed into collaborative human-robot tasks, reflecting the shift towards a human-centric Industry 5.0. However, the recruitment and retention of human workers are becoming increasingly challenging. This research investigates the sustainable deployment of robotic technologies alongside human workers, examining the impact of autonomy levels on job satisfaction and core self-evaluations, which determine turnover intentions. The findings reveal that human-robot collaboration has a positive effect on job satisfaction, particularly when the human is following the robot, and it also enhances pickers' self-esteem and self-efficacy related to human-robot interaction.