Computers in Human Behavior Reports (Aug 2024)
The impact of self-conscious emotions on the continuance intention of digital voice assistants in private and public contexts
Abstract
Digital voice assistants (DVAs) are application programs that can understand and interpret natural language voice commands. They are embedded in various products like smartphones and smart speakers and have thus become integral in everyday life, interpersonal communications, and social relationships. Despite users tend to humanize DVAs, emotions that arise in interpersonal interactions such as self-conscious emotions (i.e., pride, shame, guilt, and vicarious embarrassment) and their influence on human-machine interaction remain unstudied. Grounding on regulatory focus theory, we argue that these emotions are fundamental for promoting or preventing future DVA use. Additionally, drawing on social influence theory, we contend that the influence of self-conscious emotions on continuous DVA use varies across specific usage situations. Thus, we extend the expectation-confirmation model with self-conscious emotions and empirically compare user reactions between different social scenarios (alone and with friends in private vs. public places). Analyzing 860 DVA user responses through structural equation modeling and multigroup analysis, our findings reveal that pride consistently positively influences continuance intention across all social contexts. Furthermore, shame acts as an important inhibitor of continuance intentions in public, while guilt inhibits continuance intentions in private places. Vicarious embarrassment, however, does not exhibit significant effects in any scenario. These results carry valuable implications for both research and management in understanding and optimizing DVA user experiences.
