Gimmick or genuineness? Exploring the antecedents of AI virtual streamers aversion in live-streaming commerce

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. • Consumers' negative stereotypes indirectly influence AI virtual streamers aversion through consumer resonance and disfluency. • Interdependent consumers exhibit resistance through perceived unwarm, while independent consumers show resistance through perceived incompetent. • We incorporate both momentary experiences and reflective experiences to explore the mechanism.

Authors

Publication Details

Journal
Technological Forecasting and Social Change
Published
2025-01-16
DOI
https://doi.org/10.1016/j.techfore.2025.123981
Citations
14
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
34.73

Funders

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article

Gimmick or genuineness? Exploring the antecedents of AI virtual streamers aversion in live-streaming commerce

Xing Zhang, Xia Li, Quan Xiao, Weiling Huang
14 citations
Technological Forecasting and Social Change
AI in Service Interactions
34.73
article

Gimmick or genuineness? Exploring the antecedents of AI virtual streamers aversion in live-streaming commerce

Xing Zhang, Xia Li, Quan Xiao, Weiling Huang
article en
14 citations

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. • Consumers' negative stereotypes indirectly influence AI virtual streamers aversion through consumer resonance and disfluency. • Interdependent consumers exhibit resistance through perceived unwarm, while independent consumers show resistance through perceived incompetent. • We incorporate both momentary experiences and reflective experiences to explore the mechanism.

Technological Forecasting and Social ChangeVol. 212
National Natural Science Foundation of China, Humanities and Social Science Fund of Ministry of Education of China
Openalex Percentile: Top 0%
AI in Service Interactions
34.73
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