Match or Mismatch? How Matching Personality and Gender between Voice Assistants and Users Affects Trust in Voice Commerce

Abstract

Despite the ubiquity of voice assistants (VAs), they see limited adoption in the form of voice commerce, an online sales channel using natural language. A key barrier to the widespread use of voice commerce is the lack of user trust. To address this problem, we draw on similarity-attraction theory to investigate how trust is affected when VAs match the user’s personality and gender. We conducted a scenario-based experiment (N = 380) with four VAs designed to have different personalities and genders by customizing only the auditory cues in their voices. The results indicate that a personality match increases trust, while the effect of a gender match on trust is non-significant. Our findings contribute to research by demonstrating that some types of matches between VAs and users are more effective than others. Moreover, we reveal that it is important for practitioners to consider auditory cues when designing VAs for voice commerce.