Gimmick or genuineness? Exploring the antecedents of AI virtual streamers aversion in live-streaming commerce
Quan Xiao, Xia Li, Weiling Huang, Xing Zhang
Abstract
AI virtual streamers are emerging as a novel presence in live-streaming commerce. However, a considerable portion of consumers are still averse to these AI entities. While existing research predominantly emphasizes the positive impacts of AI virtual streamers, it often overlooks the factors contributing to consumer aversion. To address this critical yet underexplored gap, this study employs the antecedent-belief-consequence (ABC) framework to examine the determinants of consumer aversion to AI virtual streamers. Data collected from 402 consumers with a comprehensive understanding of AI virtual streamers was conducted using the partial least squares-structural equation modeling (PLS-SEM) approach. The results validate the impact of two key antecedents (i.e., anthropomorphism and technophobia) on the consequences (AI virtual streamers aversion) and explore the underlying mechanism of beliefs through the reflexive stage (i.e., perceived unwarm and perceived incompetent) and the reflective stage (i.e., consumer resonance and disfluency). Additionally, multigroup analysis (MGA) based on self-construal indicates significant group differences, with interdependent (independent) consumers being more likely to exhibit aversion through the perceived unwarm (perceived incompetent) pathway. These findings contribute to the current body of research by clarifying the multi-stage and multi-dimensional processes through which technophobia and anthropomorphism drive AI virtual streamers aversion. Practitioners can leverage these insights to address the underlying causes of consumer aversion, thereby facilitating the integration of AI virtual streamers into live-streaming commerce.