Cute or competent? Contextual dynamics of consumer acceptance toward service robots
Juanjuan Yan, Biao Luo, Kai Zhang
Abstract
Despite the prevalence of service robots, consumer attitudes toward them are mixed. We consider how conversational styles (CS) of robots influence consumer experiences in different service contexts. Two experiments investigated this issue from the theoretical perspective of the Elaboration Likelihood Model (ELM). The results show that robots with cute (vs. competent) CS lead to higher perceived entertainment (PEn); robots with competent (vs. cute) CS lead to higher perceived competence (PC). PEn and PC mediate the effect of CS on consumer service acceptance intention. We also identified the moderating role of service context in the relationship between consumer perceptions and service acceptance intention. These findings inspire service robot designers and managers to design and deploy service robots with different CS in consideration of service context to enhance the human–robot service interactions.