Human–Robot Collaboration Acceptance Model: Development and Comparison for Germany, Japan, China and the USA

Abstract

The use of robots in the national economy-especially in industrialized countries-is growing. At the same time, the interdependency between humans and robots is getting increasingly closer: they are engaging in direct contact with each other as more and more organizations let robots and humans work hand-in-hand. One factor that predicts successful human-robot interdependency is the acceptance of the robot by the human. Generally, only when an innovative assistive working system covers human needs and expectations, it is perceived to be useful and hence accepted. Furthermore, it has been found that cultural context has an impact on human-robot interaction, as people feel more comfortable interacting with a robot in a culturally normative way. Therefore this paper aims at presenting a human-robot collaboration acceptance model (HRCAM) with regard to the collaboration between humans and robots that is based on prior acceptance models, while also considering technology affinity and ethical, legal and social implications. Additionally, similarities and differences in robot acceptance are shown for four selected countries-both in comparison to the overall human-robot collaboration acceptance model and between the countries. The HRCAM additionally shows which variables influence perceived usefulness and perceived ease of use, and thus behavioral intention to use and use behavior. A further distinction is made between anchor variables, which can be influenced in the long term, and adjustment variables, which can be influenced in the short to medium term. The model therefore offers practitioners in the field of human-robot collaboration recommendations to increase the acceptance of robots. Keywords Technology acceptance • Human-robot interaction • Human-robot cooperation • Human-machine interaction • Cross-cultural differences • TAM

On the Intention to Use the Pepper Robot as Communication Channel in a Business Context

“…The results and correlations displayed that the TAM described IU respectively, the user acceptance towards the embodied agent suitably, whereby PU has a higher impact on IU than PEOU, which supports the premises underlying the model [19]: Utility is primarily more important for IU than usability. This also corresponds to the results of other acceptance surveys concerning robots [28].…”

Fear of Robots and Life Satisfaction

“…As firms introduce newgeneration robots into the workplace and, more broadly, new technologies associated with I4.0 then they need to include current workers who will be affected by such technologies in this introduction to allay at least some of the fears that they have. Brohol et al [10] provide recommendations for how humans could become more accepting of robots, based on a human-robot collaboration acceptance model (HRCAM). It is also necessary to highlight to workers the opportunities that could arise within the company as a result of adopting new technologies, notably related to reducing the number of monotonous tasks, to see technologies as helping their own productivity and increasing the number of tasks in the job that require creativity and imagination.…”

“…[42,58], with possible explanations for this being that people prefer living in rural areas but have to move to urban areas for work or there are mental health benefits from living closer to nature. 10 Because of the possibility that people who are fearful of robots may be fearful or negative about many others things, or maybe this way inclined we also control for individual attitudes towards whether people think their country is head- 9 See work by Powdthavee et al [57] who estimate both direct and indirect effects of education on life satisfaction. 10 That nature may have positive mental health benefits draws on the environmental psychology literature.…”

“…10 Because of the possibility that people who are fearful of robots may be fearful or negative about many others things, or maybe this way inclined we also control for individual attitudes towards whether people think their country is head- 9 See work by Powdthavee et al [57] who estimate both direct and indirect effects of education on life satisfaction. 10 That nature may have positive mental health benefits draws on the environmental psychology literature. Examples include Van den Berg et al [62], Hartig et al [44], Stigsdotter et al [59], Korpela and Kinnunen [47].…”

Success factors for introducing industrial human-robot interaction in practice: an empirically driven framework

“…While the decision phase is characterized by estimating relevant parameters and identifying circumstances which lie beyond the companies' sphere of influence, most factors in the implementation phase can be actively influenced. A similar differentiation is used by [73] in their so-called HRC acceptance model (HRC-AM), which is an adaption of the classical technology acceptance model (TAM), first introduced by [74] and further developed and adapted to different contexts like automation [75] or even HRI [73,[76][77][78]. They distinguish determinants of robot acceptance into anchor variables that lie beyond an organization's sphere of influence and adjustment variables that can be shaped by the organization.…”