| Abstract: |
Artificial intelligence (AI)-enabled voice assistants (VAs) such as Amazon
Alexa increasingly assist shopping decisions and exhibit empathic behavior.
The advancement of empathic AI raises concerns about machines nudging
consumers into purchasing undesired or unnecessary products. Yet, it is
unclear how the machine’s empathic behavior affects consumer responses and
decision-making outcomes during voice-enabled shopping. This article draws
from the service robot acceptance model (sRAM) and social response theory
(SRT) and presents an individual-session experiment where families (vs.
individuals) complete actual shopping tasks using an ad-hoc Alexa app
featuring high (vs. standard) empathic capabilities. We apply the experimental
conditions as moderators to the structural model, bridging selected
functional, social-emotional, and relational variables. Our framework
collocates affective empathy, explicates the bases of consumers’ beliefs,
and predicts behavioral outcomes. Findings demonstrate (i) an increase in
consumers’ perceptions, beliefs, and adoption intentions with empathic
Alexa, (ii) a positive response to empathic Alexa holding constant in family
settings, and (iii) an interaction effect only on the functional model
dimensions whereby families show greater responses to empathic Alexa while
individuals to standard Alexa. |