With the deep integration of artificial intelligence technology into the marketing activities of e-commerce platforms, AI advertising has reshaped the communication between enterprises and consumers through personalized recommendations, intelligent in...
With the deep integration of artificial intelligence technology into the marketing activities of e-commerce platforms, AI advertising has reshaped the communication between enterprises and consumers through personalized recommendations, intelligent interaction, and generative content. However, while AI advertising enhances marketing effectiveness, its heavy reliance on consumer data also gives rise to perceived privacy risks. In addition, consumers differ in their ability to understand AI technology, which means that their responses to AI advertising are not entirely consistent. Against this background, it is worth exploring how perceived characteristics of AI advertising influence purchase intention through advertising trust, and what boundary roles privacy concerns and AI literacy play in this process.
Taking Chinese e-commerce platforms as the research context, this study constructs an integrated mediation and dual-moderation model of perceived characteristics of AI advertising–advertising trust–purchase intention, based on the Stimulus–Organism–Response (SOR) theory and privacy calculus theory. This study divides the perceived characteristics of AI advertising into four dimensions: perceived personalization, perceived informativeness, perceived interactivity, and perceived novelty, which are regarded as external stimuli (S). Advertising trust is regarded as consumers’ internal psychological state (O), while purchase intention is regarded as the behavioral response (R). Privacy concerns and AI literacy are introduced as dual moderating variables to represent two types of boundary conditions: risk inhibition and capability enhancement, respectively. In addition, this study further conducts a supplementary analysis based on differences in platform types, namely transaction-oriented platforms and content-oriented platforms.
This study surveyed Chinese consumers with experience of exposure to AI advertising and obtained a total of 417 valid questionnaires. SPSS 26.0, AMOS 24.0, and PROCESS Macro v4.0 were used to conduct reliability and validity tests, structural equation modeling analysis, Bootstrap mediation testing, moderation effect and simple slope analyses, and multi-group comparison analysis.
The empirical results show the following. First, perceived personalization, perceived informativeness, perceived interactivity, and perceived novelty all have significant positive effects on advertising trust, among which perceived informativeness has the strongest effect. Second, advertising trust has a significant positive effect on purchase intention. Third, advertising trust plays a partial mediating role between the four perceived characteristics and purchase intention. Fourth, privacy concerns significantly negatively moderate the relationships between perceived personalization, perceived informativeness, and advertising trust; the moderating effect on the path between perceived interactivity and advertising trust is marginally significant, while the moderating effect on the path between perceived novelty and advertising trust is not significant. Fifth, AI literacy significantly positively moderates the relationships between perceived personalization, perceived informativeness, and advertising trust, while its moderating effects on the paths involving perceived interactivity and perceived novelty are not supported. The multi-group analysis further indicates that the mechanism differs to some extent across platform contexts. Specifically, the effect of perceived novelty on advertising trust shows a significant difference between groups and mainly functions in content-oriented platforms, whereas the effect of perceived personalization and the effect of advertising trust on purchase intention are relatively stable across both types of platforms.
This study extends research on AI advertising effects from the perspective of consumer perception, verifies the mediating mechanism of advertising trust, and reveals the boundary conditions for the formation of trust in AI advertising from the perspectives of privacy risk perception and technological understanding capability. The findings provide theoretical and practical implications for e-commerce platforms and advertisers in optimizing AI advertising strategies, enhancing advertising trust, and promoting consumers’ purchase intention.