Aug 2026· Journal of Consumer Affairs· Vol 60· 0 citations· 103 references
TL;DR
It is found that AI‐created activism elicits greater negative affect, ultimately reducing decision comfort, and this effect attenuates when consumers are conservative or have a high tendency to anthropomorphize AI.
Abstract
With the prevalence of emerging technologies, brands are increasingly using generative artificial intelligence (AI) to craft branding messages, including those reflecting sociopolitical views through brand activism. Although generative AI is effective in content creation, its use in value‐laden contexts may differentially alter individual affective responses, thereby impacting consumer well‐being. We address this gap by examining how AI‐created brand activism messages influence consumers' negative affect and decision comfort. Across five studies, we find that AI‐created activism elicits greater negative affect, ultimately reducing decision comfort. This occurs because consumers perceive these messages as less authentic. This effect attenuates when consumers are conservative (vs. liberal) or have a high tendency to anthropomorphize AI. This work advances the literature on brand activism, generative AI, and consumer affect by clarifying how AI use in brand activism reshapes consumers' emotional and decisional experiences and offering insights into how brands can effectively navigate such sociopolitical communication.
Brands are more frequently adopting virtual influencers (VIs) to lead activism campaigns. However, little is known about when and how such activism effectively drives consumer engagement. This research, in Study 1, examines 14,464 Instagram posts from 18 diverse VIs using large‐scale analytics to assess engagement intensity and the dynamics of this VI‐driven brand activism. We find that VI‐driven brand activism not only increases engagement volume but also paradoxically stimulates meaningful conversational participation through comments, alongside passive expressions of approval through likes. This pattern signals a shift from surface‐level affective responses to heightened conversational engagement, reflecting greater cognitive and behavioral investment by consumers. Study 2 shows that brand activism driven by VIs increases the intention to engage, compared with that driven by human influencers. Crucially, more realistic VIs are associated with greater engagement intensity, suggesting that humanlike characteristics enhance consumers' willingness to interact with VI‐generated content. Next, the type of ownership also matters:
non‐brand‐owned
VIs outperform
brand‐owned
ones in engagement intensity. Credibility benefits hinge on nonbrand ownership, as it heightens the perceived legitimacy of the VIs and, in turn, increases the intensity of consumer engagement. However, the engagement benefits of nonbrand ownership are more pronounced for active engagement (comments) than for passive engagement (likes). These findings provide actionable insights for selecting VI‐based brand ambassadors to promote activism campaigns.
Sampa Anupurba Pahi, Debasis Pradhan, Abhisek Kuanr et al.· Psychology & Marketing· 0 citations
With the widespread adoption of conversational artificial intelligence (Conv-AI), consumers have recently reshaped how they search, evaluate, and build relationships with brands. Accessibility and bidirectional communication have created a dynamic interface for the digital ecosystem. Yet despite a growing body of research, the field remains focused on productivity gains and the convenience of AI in digital commerce. But there is very little about how this Conv-AI intermediation affects the emotional aspect of consumer–brand love. This study draws on parasocial relationship theory and relationship marketing to advance the construct of parasocial displacement: the proposition that conversational AI agents do more than help consumers reach brands. They compete with brands for the consumer’s limited emotional attention. The authors test the proposition in three preregistered experiments (n = 791) set in realistic digital commerce scenarios. Study 1 (n = 212) shows that AI-mediated brand interactions reduce brand love compared with direct brand exposure, with the effect amplified when the AI agent presents a richer package of anthropomorphic social cues. Study 2 (n = 322) also finds that the effect passes through AI-induced parasocial attachment by careful attention and distraction. Study 3 (n = 257) demonstrates the moderation displacement of brand heritage, in which brands are largely protected, whereas emerging brands become vulnerable. This study extends parasocial theory from media personalities to algorithmic agents and proposes a triadic consumer–AI–brand framework. This triadic framework replaces the traditional dyadic models in AI-mediated branding activities. In practice, this framework identifies heritage brand equity as a relational buffer within the digital market ecosystem and proposes digital governance, disclosure for AI use, and agentic brand strategy.
Subhankar Das, S. Mondal· Journal of Theoretical and A...· 0 citations
In a technologically changing consumer behavior, it has never been more important to learn how artificial intelligence (AI) affects the purchase of green products triggered by emotions and nostalgic stimuli. This paper focuses on how nostalgia proneness and cues, artificial intelligence‐based individualized experience, brand attachment, and consumer affective reaction influence the development of purchase intentions for green products, thus applying attachment theory and emotional marketing framework to the sustainable consumption setting. The analysis of the data was conducted with the help of the SmartPLS 4.0 software with a sample of 397 environmentally conscious consumers. The findings reveal that nostalgia proneness and nostalgic cues positively influence emotional responses, which subsequently strengthen brand connection and purchase intention toward eco‐friendly products. Furthermore, emotional response and brand connection serve as significant sequential mediators in explaining consumers' sustainable purchase behavior. The moderation analysis demonstrates that AI‐driven personalized experiences significantly strengthen the relationship between nostalgic cues and emotional response, whereas their moderating effect on the relationship between nostalgia proneness and emotional response is not significant. These findings indicate that AI‐driven personalization is more effective in enhancing the emotional impact of externally embedded nostalgic stimuli than consumers' inherent nostalgic tendencies. By integrating nostalgia, emotional response, brand connection, and AI‐driven personalization within the context of sustainable consumption, this study provides important theoretical and practical insights for marketers seeking to promote eco‐friendly products in both emerging and developed markets.
Nabeel Rehman, Asad Abbas Jaffari, Maria Palazzo· Corporate Social Responsibil...· 0 citations
This study aims to examine how consumers respond when personified brands disclose using artificial intelligence (AI) in generating social media marketing content and explore effective communication strategies for mitigating the negative impact of such disclosures.
Three online experiments with a total of 576 participants were conducted to explore the effect of AI disclosures on consumers’ behavioral intentions toward personified brands on social media, along with the underlying mechanisms of the effect and the boundary conditions created by brands’ communication strategies.
AI disclosures significantly reduced consumers’ behavioral intentions on social media. This effect was driven by declines in perceived brand authenticity and humanness. Brand personification mitigated the reduction in perceived brand humanness but did not restore brand authenticity, leaving the negative impact of AI disclosures on behavioral intentions unchanged. Analysis of communication strategies showed that, under AI disclosures, proactive corporate social responsibility (CSR) communicated through socioemotional messages produced the most favorable outcomes for personified brands.
This research provides the first examination of how AI disclosures shape consumer responses in the context of brand personification. It advances theory on AI-mediated marketing communication and offers practical guidance for branding professionals aiming to sustain favorable consumer responses when integrating AI into brand personification strategies.
Linwan Wu· Journal of Product & Bra...· 0 citations
The swift rise of computer-generated “virtual” or artificial-intelligence (AI) influencers, in parallel with traditional human endorsers, has prompted brands to reconsider which type of influencer more effectively fosters consumer engagement and brand loyalty. This study utilizes source credibility theory, parasocial interaction theory, and the uncanny valley framework to analyze consumer reactions to both human and AI influencers across six dimensions: perceived authenticity, source credibility, parasocial interaction, consumer engagement, brand attachment, and purchase intention. A between-subjects survey involving 320 participants was conducted, exposing them to a social media endorsement campaign featuring either a human or an AI influencer. Results from independent-samples t-tests indicated that human influencers outperformed their AI counterparts across all dimensions. The most significant disparities were observed in perceived authenticity (d = 0.93) and parasocial interaction (d = 0.86), while the difference in consumer engagement was notably smaller (d = 0.24). Hierarchical regression analysis revealed that parasocial interaction and source credibility were the strongest predictors of brand attachment alongside engagement together accounting for 59.1% of variance. Interestingly, the type of influencer lost its predictive power when these psychological factors were considered. Additionally, a moderation analysis pointed to a compensatory trend: after adjusting for perceived authenticity, the engagement gap between the two types of influencers narrowed to an insignificant level. These findings lend support to a mechanism-based perspective where the type of influencer influences engagement and brand attachment indirectly via credibility and relational dynamics rather than solely through the distinction between human and AI influencers. The study concludes with managerial insights, theoretical implications, limitations, and suggestions for future research avenues.
P. Chandrika Reddy, Arputha Sahaya Raj J, V. R. Hiremath et al.· Canadian Journal of Marketin...· 0 citations
With the widespread adoption of social e-commerce platforms, users are increasingly exposed to branded content that blends commercial persuasion with personal expression, raising important questions about how users psychologically respond to such content in terms of engagement-related behavioral tendencies. This study investigates how advertisement recognition influences users' willingness to participate, and examines the moderating role of expressive authenticity as well as the boundary conditions introduced by platform-level advertising disclosures. Using a multi-source dataset that combines objective content features from 600 beauty brand collaboration posts on the Xiaohongshu platform with users' subjective perception ratings, hierarchical regression and group analyses were conducted to test the proposed relationships. The results show that advertisement recognition significantly reduces participation willingness, consistent with the activation of persuasion knowledge. Expressive authenticity positively predicts participation willingness and attenuates the negative effect of advertisement recognition when explicit advertising labels are absent. However, this buffering effect disappears when official platform advertising labels are present, indicating that institutional disclosure alters users' processing of authenticity-related cues. These findings suggest that expressive cues can mitigate persuasion-related resistance only under specific disclosure conditions, contributing to a more nuanced understanding of psychological responses to native advertising in social media contexts.
Wenjing Liu· Frontiers in Communication· 0 citations
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.