The best task allocation process is to decide on one’s own: effects of the allocation agent in human–robot interaction on perceived work characteristics and satisfaction

Abstract

New technologies are ever evolving and have the power to change human work for the better or the worse depending on the implementation. For human–robot interaction (HRI), it is decisive how humans and robots will share tasks and who will be in charge for decisions on task allocation. The aim of this online experiment was to examine the influence of different decision agents on the perception of a task allocation process in HRI. We assume that inclusion of the worker in the allocation will create more perceived work resources and will lead to more satisfaction with the allocation and the work results than a decision made by another agent. To test these hypotheses, we used a fictional production scenario where tasks were allocated to the participant and a robot. The allocation decision was either made by the robot, by an organizational unit, or by the participants themselves. We then looked for differences between those conditions. Our sample consisted of 151 people. In multiple ANOVAs, we could show that satisfaction with the allocation process, the solution, and with the result of the work process was higher in the condition where participants themselves were given agency in the allocation process compared to the other two. Those participants also experienced more task identity and autonomy. This has implications for the design of allocation processes: The inclusion of workers in task allocation can play a crucial role in leveraging the acceptance of HRI and in designing humane work systems in Industry 4.0.

Introduction to the special section humans and industry 4.0

“…The method has been used to identify the future main functions that would be necessary to control such new manufacturing system, especially regarding human needs like workload management and maintenance of situation awareness. Tausch (2020) proposed an online experiment to show that when operators can decide they give more meaning to their activity and their level of satisfaction is higher. The study by Moerman can be considered as a first attempt to empirically evaluate the applicability of the new theory on graceful extensibility.…”

“…For the third manufacturing system, the objective of the research is to analyze the ability to support human in the control of a complex and complicated autonomous process based on self-organized production system composed of several production robots linked by conveyors for shuttles selves-motion, and supplied with autonomous/remoted control ground mobile robots (Pacaux-Lemoine et al). The fourth application (Tausch 2020) concerns a fictional production plant for sweets. The participants were told to imagine being a worker at this plant, and responsible for the production of lollipops.…”

“…In the paper of Bounouar et al, the criteria related to consider humans are biomechanical and physiological criteria, acceptability and usefulness, usability and ease of learning as well as acceptance, satisfaction and ownership over time. In Tausch (2020), the participants in the online study were chosen using personal networks as well as online platforms, such as Thesius or SurveyCircle. They were assigned to three experimental conditions: organization-allocation condition, robot-allocation condition, and worker-allocation condition.…”

Physical and mental well‐being of cobot workers: A scoping review using the Software‐Hardware‐Environment‐Liveware‐Liveware‐Organization model

“…In this context, experimental studies have proposed optimization frameworks able to support process engineers in generating task assignments balancing both time and ergonomics (Mateus et al, 2019). Studies focusing on psychological aspects of task allocation suggest that autonomy in decision-making increases workers' satisfaction and task identity (Tausch & Kluge, 2022). Thus, increased attentional resources may be needed owing to the changing role of the worker (Brun & Wioland, 2021).…”

The effect of cognitive workload on decision authority assignment in human-robot collaboration

“…Classic human factors research suggests that, in HRC scenarios, the human should be kept in the decision loop, to avoid phenomena of complacency, loss of skill and loss of situational awareness (Wickens et al, 2015). However, some empirical human-robot interaction studies indicate that human control and decision-making are not always desirable in terms of process e ciency and subjective satisfaction (Baraglia, Cakmak, Nagai, Rao, & Asada, 2016; Matthew C Gombolay, Gutierrez, Clarke, Sturla, & Shah, 2015; Matthew Craig Gombolay, Huang, & Shah, 2015; Scerbo, 1996;Tausch & Kluge, 2020). This can be partially explained by the increased workload that follows human decision authority and responsibility in supervising autonomous systems (Harris, Hancock, & Arthur, 1993).…”