Virtual influencers in social media versus the metaverse: Mind Perception, blame judgements and brand trust

IF 10.5 1区 管理学 Q1 BUSINESS
Sian Joel-Edgar , Soumyadeb Chowdhury , Peter Nagy , Shuang Ren
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引用次数: 0

Abstract

The rise of virtual influencers (VIs) in digital marketing channels, such as social media platforms and the metaverse, raises critical, under-researched questions about blame attribution to these digital entities and its subsequent impact on brand trust. Our research addresses this gap by applying the theoretical lens of mind perception to two studies using an experimental causal chain design approach. Study 1 revealed that consumers attribute higher mind perception to a human VI and consequently place more blame on them in negative scenarios compared to AI-powered VI. Additionally, we found that perceived mind perception was unaffected by the digital channel (social media versus metaverse). Study 2 demonstrated that brand trust diminishes more significantly when an AI-powered VI is blamed compared to a human VI. These insights contribute to understanding the psychological mechanism of blame judgement towards VIs, and highlight the importance for brands to consider the repercussions of using AI-powered VI.
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来源期刊
CiteScore
20.30
自引率
10.60%
发文量
956
期刊介绍: The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.
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