Does Anthropomorphism Reduce Perceived Loss of Control and Resistance to AI?

With advancements in technology, many brands are introducing AI to provide more personalized recommendation services, increasing consumer willingness to purchase (Gao Min, 2020). For instance, numerous companies have adopted AI to generate social media content, disguising it as human interaction with consumers (Liu, 2019). Additionally, the MemoMi brand launched the smart mirror MemoryMirror, allowing consumers to change their outfits' styles, colors, and sizes simply by waving their hands without trying them on. MemoryMirror can also predict consumer preferences based on previous choices to recommend personalized new products (Li Chenxin, 2017). Another example is the "AI Smart Outfit Recommendation" feature developed by PChome 24h Shopping and the Industrial Technology Research Institute, which uses big data analysis and AI to predict consumer preferences for clothing attributes like necklines, styles, patterns, shapes, and colors to recommend suitable apparel, thereby enhancing shopping willingness. The smart mirror from Wangzhou Trial Fitting Studio enables consumers to input their gender, height, and body type information to generate a virtual image of themselves. Consumers can then select their preferred clothing and see how it looks on the smart mirror. This device increases the average time consumers spend in-store by at least 20 minutes and provides an engaging shopping experience both in-store and online. Such smart fitting mirrors can also record consumer choices for precise future recommendations (KKnews, 2018). The Japanese minimalist eyewear design company JINS utilizes the JINS Brain AI system. Consumers only need to wear their preferred glasses for the system to assess their face shape and suitability in seconds (Shen, 2020). These examples illustrate that AI can offer consumers unique experiences that enhance purchase intentions and increase brand loyalty (Li Chenxin, 2017). AI recommendation systems are not limited to the fashion industry; they are also widely used in investment markets in Europe and America for financial management. In 2020, assets managed by AI reached $450 billion (Yan Changchuan, 2017), covering areas such as retirement planning and financial advisory services (Huang Xin, 2018; He Yuxin, 2019). These AI recommendation systems are not just products but also practical services for consumers. Despite the apparent advantages of AI services that provide convenience and personalization for consumers, not all AI services are readily adopted. Users often evaluate their perceived control over new technologies before deciding whether to adopt them (Ajzen, 1991; Elie-Dit-Cosaque et al., 2011; Lee, 2008). In marketing, increasing consumers' perceived control is a significant challenge as it involves addressing existing attitudes and habits toward new technologies while understanding what aspects of usage consumers wish to control and their priorities. Anthropomorphism often diminishes consumers' self-control abilities while increasing acceptance of new technologies (Hur et al., 2015; Kim & Kramer, 2015) and influencing consumer preferences and brand evaluations (Aggarwal & McGill, 2012). However, literature on the relationship between anthropomorphism and perceived control remains scarce. A major flaw in previous research on perceived control is its inability to provide marketers with insights into what kind of control consumers need when using AI services. This raises an intriguing issue: What is the relationship between perceived control over AI and consumers' intentions to use these services? How does anthropomorphism affect consumers' perceived control over AI? Does perceived control indirectly influence the intention to adopt such innovative services? The Social Cognitive Theory—Stereotype Content Model (SCM) posits that people evaluate others or groups based on two dimensions: warmth and competence (Fiske et al., 2007), known as the Big Two model (Fiske, 2018; Fiske et al., 2007). This theory was initially applied to interpersonal interactions regarding social group perceptions but later extended to organizational evaluations (Aaker et al., 2010). Recently, scholars have applied this theory to advertising and branding by attributing warmth and competence as personality traits to brands (Zawisza & Pittard, 2015), establishing relationships akin to those between individuals (Aggarwal, 2012). Few studies have applied warmth and competence to the anthropomorphism of objects (e.g., Kervyn et al., 2012; Zawisza & Pittard, 2015) or services. Therefore, this project aims to pioneer the application of the Stereotype Content Model to personified AI services by investigating how warmth and competence in AI services align with practical or hedonic services in achieving optimal outcomes. It seeks to clarify aspects of consumers' perceived control over AI while exploring the relationship between anthropomorphism and perceived control. Additionally, it will examine whether perceived control directly impacts usage intentions or serves as a mediator between anthropomorphism and usage intentions. The literature also lacks understanding of how anthropomorphism in AI services aligns with service categories in terms of persuasive effectiveness. Thus, this project will develop dimensions of perceived control while extending the Stereotype Content Model's application to personified AI. This project aims to provide academic and practical recommendations for reducing consumer loss of control and resistance to AI.

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