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Influencer-product attractiveness transference in interactive fashion marketing: the moderated moderating effect of speciesism against AI

Junjun Cheng*, Jiaxuan Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Fashion marketers are adopting attractive virtual personalities to replace human influencers on social media, but the impact of consumer bias against virtual influencer acceptance is not fully understood. Drawing upon match-up hypothesis, attribution theory and speciesism against artificial intelligence (AI), this research investigates how speciesism shapes the influencer-product attractiveness transference in AI-powered influencer marketing for fashion products.

Design/methodology/approach: Three studies were conducted (N = 1,385) to test the influencer-product attractiveness transference, the moderating role of influencer type and the moderated moderating role of speciesism against AI.

Findings: Our studies validated the attractiveness transference and revealed that influencers’ attractiveness promotes purchase intention via perceived product attractiveness. The adoption of virtual (vs human) influencers weakens the attractiveness transference and attenuates the mediating effect. Low speciesism boosts the effectiveness of virtual influencers, such that attractiveness transference disappears only when high-speciesism consumers react to virtual influencers.

Originality/value: Our findings clarify how influencers’ physical appearance, AI application and speciesism together impact interactive fashion marketing, offering practical insights into successful influencer strategies on social media.

Original languageEnglish
Pages (from-to)712-729
Number of pages18
JournalJournal of Research in Interactive Marketing
Volume19
Issue number4
DOIs
Publication statusPublished - 13 May 2025
Externally publishedYes

Keywords

  • Attractiveness transference
  • Physical attractiveness
  • Product attractiveness
  • Speciesism
  • Virtual influencer

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