To address limitations in diversity and novelty in AI recommendations, e-commerce platforms are increasingly leveraging influencer recommendations to assist in consumer decision-making. Many online merchants now provide both AI and influencer recommendations to consumers simultaneously. But is the combined recommendation method always the most effective? Existing research requires further insight into this question. This study adopts signaling theory and uniqueness theory, using an experimental approach to compare the effects of AI, influencer, and combined recommendations on online consumer decision-making. The results indicate that both combined and AI recommendations are more effective than influencer recommendations in enhancing online consumers' purchase intentions, with no significant difference between these two types of recommendations. Additionally, it is found that combined recommendations significantly increase purchase intentions more than influencer recommendations for hedonic products, whereas there is no significant difference for utilitarian products. For prevention-focused consumers, combined recommendations exert a greater positive influence than influencer recommendations when purchasing hedonic products, although this difference is not significant for utilitarian products.