Algorithmic Persuasion and Consumer Trust in Vietnam: Mediating Mechanisms and Configurational Pathways of AI-enabled Marketing Communication

The proliferation of artificial intelligence-enabled marketing communication represents a fundamental transformation in consumer-brand interactions, yet the psychological mechanisms through which algorithmic persuasion influences consumer trust remain inadequately theorised, particularly within emerging market contexts. This study examines the structural pathways and configurational patterns through which AI-driven marketing communication shapes consumer trust amongst Vietnamese consumers, employing an integrative theoretical framework synthesising the Elaboration Likelihood Model, Trust Transfer Theory, and Technology Acceptance Model. Utilising partial least squares structural equation modelling and fuzzy-set qualitative comparative analysis on data from 398 Vietnamese consumers, the research reveals that perceived personalisation, algorithmic transparency, and human-likeness serve as critical mediating mechanisms linking AI communication attributes to consumer trust. The findings demonstrate that perceived personalisation exerts the strongest direct effect on trust formation, whilst algorithmic transparency operates predominantly through enhancing perceived credibility. Configurational analysis uncovers four distinct pathways to high consumer trust, revealing equifinality in trust formation processes. Multigroup analysis documents significant differences across age cohorts, with younger consumers demonstrating greater receptivity to AI-enabled communication. These findings advance theoretical understanding of algorithmic persuasion whilst offering strategic insights for organisations navigating digital transformation in Southeast Asian markets characterised by distinctive cultural values and technological adoption patterns.

• Publication year

  2025

• Venue

  International journal of economics, business and management research

• Publication date

  Unknown publication date

• Fields of study

  Not labeled

• Identifiers
  DOI 10.51505/ijebmr.2025.91219
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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