With the extensive integration of the digital economy, algorithm-controlled products have become widely embedded in consumers' daily lives. Existing research on preferences for algorithm products primarily focuses on technical features or system transparency, largely overlooking the influence of consumers' psychological states and emotional motivations. Social exclusion is a common occurrence that threatens psychological needs and triggers compensatory consumption. Based on the S-O-R model and compensatory consumption theory, this study explores how various forms of social exclusion affect consumers' preferences for algorithm-controlled products and examines the mechanisms underlying these effects. This study primarily utilized the experimental method to validate the theoretical model. The findings reveal that: (1) Compared to being ignored, rejected consumers prefer high-adaptability algorithm products, while ignored consumers prefer low-adaptability algorithm products. (2) The need to belong mediates the relationship between being rejected social exclusion and the preference for high-adaptability products, whereas the need for control mediates the relationship between being ignored social exclusion and the preference for low-adaptability products. (3) Self-acceptance significantly moderates these effects; the aforementioned compensatory mechanisms are only significant among consumers with low self-acceptance. This research extends the theory of social exclusion to the context of human-computer interaction and algorithm consumption. Practically, it provides enterprises with novel marketing strategies based on consumers' psychological needs and helps consumers maintain rationality and psychological well-being in the algorithmic era.

Social Exclusion, Algorithm-controlled Products, The Need To Belong, The Need For Control, Self-acceptance