首页|Findings from Qingdao University Provide New Insights into Androids (Customer Acceptance of Frontline Social Robots-humanrobot Interaction As Boundary Condition)
Findings from Qingdao University Provide New Insights into Androids (Customer Acceptance of Frontline Social Robots-humanrobot Interaction As Boundary Condition)
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NETL
NSTL
Elsevier
Investigators publish new report on Robotics - Androids. According to news reporting from Qingdao, People’s Republic of China, by NewsRx journalists, research stated, “From an interactionist perspective, we argue that what happens and how service is delivered during the humanrobot interaction may alter the extent to which customers accept service robots. Extending previous research on customer acceptance of service robots and human-robot interaction, we treat the elements during the humanrobot interaction process as boundary conditions for the link between service robots’ functional and socialemotional capabilities.” Funders for this research include Shandong Provincial Natural Science Foundation for Excellent Young Scholars, Science and Technology Support Plan for Youth Innovation of Colleges and Universities of Shandong Province of China, Natural Science Foundation of Shandong Province. The news correspondents obtained a quote from the research from Qingdao University, “Specifically, we examine (1) contact frequency between customers and service robots, (2) interdependence among service robots and human service employees, and (3) service complexity, moderate the relationship between service robots’ capabilities and customer acceptance. With data collected from 997 customers who have past experience with service robots, we found that the effect of functional and socialemotional capabilities of service robots on customer acceptance are more salient when contact frequency is low rather than high, interdependence among service robots and service employees is high rather than low, and service complexity is low rather than high.”
QingdaoPeople’s Republic of ChinaAsiaAndroidsEmerging TechnologiesHuman-Robot InteractionMachine LearningNano-robotRobotRoboticsQingdao University
NETL
NSTL
Elsevier
