Consumer responses to algorithmic in-feed advertising: AI transparency as a moderator among young adults in social commerce

Abstract

Driven by the advancement and application of artificial intelligence (AI) technology, in-feed advertising has become a critical driver of consumption growth in social commerce. This study explores how stimuli from algorithmic in-feed advertising shape the psychological perceptions of young adults, thereby influencing their purchase and sharing intentions. Based on the stimulus–organism–response (SOR) theory, this research constructs a theoretical relationship model. Online questionnaire data were collected from 609 Chinese young adult respondents, and partial least squares structural equation modeling (PLS-SEM) was employed for empirical analysis. The empirical results reveal five key findings: (1) entertainment, personalization, and incentives exert positive effects on users’ affective attitude, whereas informativeness and credibility show no significant association with affective attitude; (2) informativeness, personalization, incentives, and credibility are positively correlated with cognitive attitude, while entertainment has no significant impact on cognitive attitude; (3) advertising intrusiveness negatively predicts both affective and cognitive attitudes; (4) both affective and cognitive attitudes significantly enhance users’ purchase and sharing intentions; (5) AI transparency significantly moderates the linkage between cognitive attitude and purchase intention, yet it exerts no moderating effect on the relationship between affective attitude and purchase intention. This study’s findings offer practical and theoretical insights for social commerce platforms, advertising designers, and marketers to optimize algorithmic in-feed advertising strategies and effectively stimulate young consumers’ social commerce engagement.