The proliferation of generative artificial intelligence (AI) chatbots such as ChatGPT has sparked a transformation in the dynamics of human–machine interactions. However, little is known about the psychological mechanisms underlying generative AI chatbot–human relationships. Building on the investment model, this study examined the influence of generative AI user-friendliness and playfulness on ChatGPT commitment and continuance usage intention. The results of an online survey conducted in the United States (N = 446) indicated that user-friendliness and playfulness positively affect satisfaction, investment size, and perceived quality of alternatives. Both satisfaction and investment size positively affect commitment to ChatGPT, thereby influencing the intention to continue using generative AI chatbots. However, the quality of alternatives did not significantly affect user commitment to ChatGPT. The findings of this study contribute to our understanding of building user relationships with generative AI chatbots by identifying user-friendliness (representing utilitarian value) and playfulness (representing hedonic value) as key factors in determining generative AI continuance usage intention.

With the rapid evolution of artificial intelligence (AI), this study aims to examine the interplay among the perceived usability, perceived enjoyment, perceived responsiveness, and intention to continue using ChatGPT. Structural equation modeling (SEM) was used to investigate our proposed model. We recruited 446 ChatGPT users through an online survey conducted on the Connect platform, powered by CloudResearch. Perceived usability (β = 0.254) and enjoyment (β = 0.438) significantly influence satisfaction with ChatGPT. However, perceived responsiveness is not significantly related to perceived attachment or satisfaction. Furthermore, we established that perceived attachment (β = 0.405) and satisfaction (β = 0.447) are pivotal in shaping users’ intentions to continue using ChatGPT, providing insights into human–AI interactions. The practical implications of our findings suggest that generative AI chatbots should be crafted with a focus on enjoyable, user-centered interfaces that foster long-term user satisfaction and engagement. AI developers should design AI conversation flows and chatbot personas to optimize the user experience.

As AI-generated news expands with advancing media technology, understanding its impact on consumer engagement becomes increasingly important. This study investigates how readers’ awareness of an article’s AI or human authorship affects their engagement with news content. The findings indicate that AI-generated news content results in lower liking behaviors compared to human-written content, with this effect mediated by the article’s perceived credibility rather than its perceived authenticity. Additionally, the mediating effect of news credibility is moderated by the perceived human-likeness of AI, with the negative impact being weaker when AI is perceived as more human-like. These findings extend the literature on human-computer interaction in journalism by highlighting the negative impact of AI use on consumer engagement, identifying perceived credibility as its underlying mechanism, and introducing a new paradigm focused on AI’s human-likeness. Practically, the findings suggest that careful management of AI authorship and its perceived human-likeness is essential.

This empirical study investigates the structural relationships among virtual influencer attributes, perceived creepiness, perceived authenticity, emotional attachment, and word-of-mouth intentions of social media users. To be specific, this study conceptually identifies the roles of the virtual influencer attributes of language similarity, interest similarity, social attractiveness, physical attractiveness, and attitude homophily on perceived creepiness and perceived authenticity of the virtual influencer, as these in turn affect emotional attachment and word-of-mouth. This study collected data from social media users in the United States via a survey approach and found that creepiness was significantly influenced by attitude homophily while perceived authenticity was significantly affected by language similarity, interest similarity, physical attractiveness, and attitude homophily. In addition, this study found significant relationships among perceived creepiness, perceived authenticity, emotional attachment, and word-of-mouth intention. This empirical study has both theoretical and practical implications for virtual influencer marketing.