随着人工智能技术的快速发展，人工智能推荐在营销领域的应用日益广泛。人工智能推荐为消费者提供了获取产品建议的新途径，一定程度提高了购买决策的效率和准确性。然而，尽管人工智能推荐在营销领域受到广泛关注，但关于其如何满足不同消费者心理需求的研究仍存在空白，了解消费者对于人工智能应用的态度和反应能够帮助我们更好地使用和推广新的技术，优化营销的效果。

社会排斥作为普遍存在的心理学现象，深刻影响着个体的情感、认知以及行为等层面。在营销领域，社会排斥对消费者购买决策和购买行为的影响日益受到关注。现有研究多关注于社会排斥对消费者心理和行为的具体影响，本文将社会排斥与人工智能推荐相结合，探讨社会排斥如何影响消费者对推荐类型的偏好。

通过四个实验本文最终得出结论：社会排斥会影响消费者对推荐类型的偏好，与人工智能推荐的产品相比，在社会排斥的情境下，消费者更偏好专家推荐的产品。进一步，本文的实验结果表明，独特性需求在影响机制中起中介作用，即在社会排斥的情境下，消费者独特性需求降低，因而更偏好专家推荐（vs. 人工智能推荐）的产品。同时，消费者创新性在其中起调节作用，在社会排斥情境下，消费者创新性较高的个体独特性需求降低，对专家推荐的偏好增加，对人工智能推荐的偏好降低，而消费者创新性较低的个体对不同推荐类型的偏好变化不大。另外，自我建构（独立自我）在其中起调节作用，在社会排斥情境下，低独立自我个体对专家推荐的偏好会被强化，对人工智能推荐的偏好会被削弱，而高独立自我个体对不同推荐类型的偏好变化不大。

综上，本研究通过实证研究，揭示社会排斥与人工智能推荐之间的关系及其内在机理，帮助我们更好理解消费者在不同场景中对于人工智能推荐的反应，为社会排斥的相关研究提供了新的讨论视角，为营销领域的研究和实践提供新的思路和方法。同时，为企业和营销人员提供了一定的营销启示。

With the rapid advancement of artificial intelligence (AI) technology, artificial intelligence recommendation is increasingly being widely utilized in the marketing field. AI recommendation offers consumers a novel approach to obtain product advice, thereby enhancing the efficiency and accuracy of purchasing decisions. However, despite the widespread attention AI recommendations have garnered in marketing, there remains a research gap regarding how they cater to the psychological needs of diverse consumers. Understanding consumer attitudes and reactions towards AI applications can assist us in better utilizing and promoting new technologies.

As a ubiquitous psychological phenomenon, social exclusion exerts a profound impact on individual cognition, emotion, and behavior. In the realm of marketing, there has been an increasing focus on the influence of social exclusion on consumers' purchasing decisions and behaviors. This paper integrates artificial intelligence recommendation with social exclusion to investigate how it influences consumers' preference for different types of recommendations.

Through four experiments, this paper draws the following conclusion: Consumers prefer products recommended by experts (vs.AI) in the context of social exclusion. Further, need for uniqueness plays a mediating role. In the context of social exclusion, need for uniqueness decreases and therefore consumers prefer expert recommendation (vs.AI). At the same time, consumer innovation plays a moderating role. In the context of social exclusion, consumers with higher innovation have higher preference for expert recommendation. In addition, self-construction plays a moderating role.

In summary, this study reveals the relationship between AI and social exclusion recommendation and its internal mechanism through empirical research, helps us better understand consumers’ responses to AI recommendation in different scenarios, provides a new perspective for the study of social exclusion, and provides new ideas and methods for the research and practice of marketing.