Does algorithmic recommendation complement or substitute advertising and influencers? Consumer attitudes toward recommendation information and the formation of purchase intentions

This study analyzes how consumers’ attitudes toward messages and their purchase intentions for recommended products vary depending on the source of the message—companies, influencers, or algorithms. With increasing consumer awareness of stealth marketing and the growing prevalence of algorithm-driven content that utilizes personal consumer data on platforms, examining whether the influence of different sources has shifted is theoretically and practically important. The study employed a 3 × 2 × 2 factorial design with 1,600 participants who were exposed to social media posts that varied in terms of information source, product type, and brand awareness. showed that company-generated messages were perceived as more trustworthy than those from influencers. Moreover, the purchase intention for products recommended by companies was greater than that for products recommended by influencers. Although algorithm-generated messages were not significantly more trusted than those from influencers, they still increased purchase intentions for recommended products. Hence, regardless of the perceived trustworthiness of algorithmic messages, the fact that recommendations came from an algorithm led to an increase in purchase intention. These findings imply that algorithms are not necessarily perceived as expert sources providing valuable information to complement human experts, but their presence alone is highly valued by consumers. Hence, they show potential to replace influencers. • Stealth marketing raises consumer trust in advertising. • Advertising strongly affects purchase intention. • Algorithm-based recommendations drive purchase intentions effectively. • Consumers trust algorithmic recommendations regardless of validity.