The searching artificial intelligence: Consumers show less aversion to algorithm-recommended search product

Though artificial intelligence (AI) recommendation is a hot topic in recent marketing research, previous research has shown a convergent tendency for aversion to AI recommendation. It is imperative to find ways to promote AI usage and reduce consumers' AI aversion. This study fills this void by exploring the effect of AI (vs. human) recommenders on consumers' preferences for search versus experience products in the context of e-commerce. Two studies provide convergent evidence that consumers show less avoidance of algorithms when recommending search products compared to experience products. A behavioral experiment (Study 1, N = 112) validates that consumers are less likely to purchase experience products recommended by AI, while there are no significant differences between AI versus human recommenders when recommending search products. Using event-related potential (ERP), a further consumer neuroscience study (Study 2, N = 26) shows that consumers have a higher level of cognitive conflict (i.e., a larger magnitude of N2) when AI (vs. human) recommends experience products, while the effect disappears for search products. This paper shows that for search products, marketers can obtain similar evaluations using AI recommenders, which is relatively cheaper and more time-saving compared with human recommenders. Therefore, our work provides important implications for theory and practice on e-commerce and marketing communication.