Journal of Internet Commerce

Generative AI and Consumer Behaviour in E-Commerce

Introduction

The rapid development of Generative Artificial Intelligence (Gen AI) is revolutionizing the digital commerce environment, redefining the way consumers interact with goods, services, and brands (Cillo & Rubera, 2025; Schmitt, 2025). From personalized experiences via AI, content generation, and virtual influencers to dynamic marketplaces fueled by generative algorithms, Gen AI is transforming the very fabric of online consumption, trust, and value co-creation (Acar, 2024; Chan & Choi, 2025; Huang & Rust, 2025).

By upgrading customer segmentation, maximizing marketing strategies, and making recommendation engines better, Gen AI technologies are revolutionizing the foundational mechanisms of online shopping operations (Mora-López et al., 2025). With users interacting with AI-created text, images, recommendations, and avatars, their attitudes, emotions, and decisions are being shaped in increasingly subtle ways (Cheng et al., 2025). The development of interactive generative AI also points to its potential for emotionally intelligent customer service and empathetic and immersive digital interaction (Huang & Rust, 2024; Pizzi et al., 2025).

Though such innovations hold out the prospects of improved consumer experience (Lou, Han & Xu, 2025), higher levels of engagement and operational efficiency. As online commerce is increasingly embedded in generative technologies, it becomes essential to consider how such systems condition market behaviour, consumer identity, and digital inclusion (Feng & Sun, 2025).

Recent studies highlight the potential and pitfalls of Gen AI. Mogaji and Jain (2024) posit that generative AI will transform consumer engagement and post-purchase conduct with tailored and engaging experiences. Huang and Rust (2025) highlight the fact that AI not only mechanizes marketing but also revolutionizes consumer research itself, necessitating new theoretical approaches to comprehend the AI-enabled consumer. Yet, researchers warn against the "dark side" of algorithmic power, which comprises bias, lack of transparency, and ethical issues regarding the ownership and manipulation of data (Kim et al., 2023; Xie, 2026).

Recent literature also points to new horizons. De Freitas, Nave & Puntoni (2025) mention that though Gen AI aids in synthetic data creation, its application in creative ideation is an untapped area. Heitmann et al. (2025) demonstrate how current AI models are not aligned with fundamental marketing goals like attention and persuasion, and whether visual advertising can be fine-tuned in generative systems. Artificial empathy being incorporated into AI-facilitated marketing interactions is another promising advancement, proving to advance affective and social customer experiences (Liu-Thompkins, Okazaki & Li, 2022).

Concurrently, Schindler et al. (2024) prove that conversational agents, when aligned with communication modality (e.g., voice for hedonic and text for utilitarian products), enhance customer satisfaction and decision fluency. However, the psychological and behavioural effects of AI-based recommendation algorithms are still not well researched (Nguyen et al., 2024).

Additional research into anthropomorphism in AI (Kumar, Jain & Sharma, 2025) finds human-like AI capabilities increase trust and emotional affinity, with organizational preparedness dictating successful chatbot use (Zhang, Følstad & Bjørkli, 2023; Sidlauskiene, 2022). In addition, AI-driven customization facilitates customers to co-create customized products, although such AI-facilitated creativity perceptions are under-researched (Lou, Han & Xu, 2025; Jia et al., 2024).

The Journal of Consumer Research urges a critical approach towards Gen AI, acknowledging its potential for transformation as well as its limitations since findings can be subject to ongoing revision in tandem with emerging technology (Schmitt, 2025).

In this context, the Journal of Internet Commerce, as a pre-eminent publishing platform for research into digital commerce, consumer behavior, and technology-facilitated marketing transformation, solicits papers for a Special Issue entitled "Generative AI and Consumer Behaviour in E-Commerce."

This Special Issue aims to contribute both theory and practice by discussing how generative technologies are reshaping the spaces of online consumption, marketing strategy, and consumer psychology. We welcome submissions that create new frameworks, models, and research techniques to analyze changing AI–consumer dynamics. Contributions that critically discuss the opportunities, challenges, and wider social implications of Generative AI in the e-commerce space are especially encouraged.

 

Scope and Aims

We invite original research contributions that address theoretical foundations, practical applications, and empirical studies related to generative AI and consumer behaviour in e-commerce contexts.

We invite proposals that engage with one or more of the following themes (or related areas):

Generative AI and Consumer Experience

• Cognitive, emotional, and behavioral reactions to AI-generated content, avatars, and virtual influencers.
• Product discovery, personalization, and purchase decision-making redesigned by Gen AI.
• Anthropomorphism and human-like AI design in shaping consumer trust and connection.
• AI’s role in post-purchase care and emotion management 

Conversational Commerce and AI-Driven Interaction

• Interactive Gen AI and artificial empathy in emotionally intelligent customer interaction.
• The rise of AI-powered chatbots, virtual assistants, and voice-based interfaces in consumer decision support.
• Psychological effects of communication modality (voice vs. text) on satisfaction and product evaluation.

Cross-Platform, Omnichannel, and Social Commerce

• Generative AI across social, mobile, and e-commerce platforms for seamless consumer journeys.
• Cross-platform personalization and content coherence within AI-powered ecosystems.
• Development of social commerce and influencer ecosystems based on generative models.
• Big data, behavioral prediction, and real-time personalization using generative models.

Creativity, Co-Creation, and Consumer Empowerment

• Gen AI as a consumer creativity tool for self-expression and co-design; dissolving boundaries between producer and consumer.
• Ownership, authorship, and perceived value in AI co-created. 

AI-Based Marketing Media and Immersive Experiences

• Generative AI advertising, AR/VR try-on, and immersive retail
• Scene generation, persuasive storytelling, and multimodal content for brand experience.

Theoretical Foundations and Conceptual Frameworks

• New theoretical perspectives describing AI-augmented consumer behavior.
• Sociotechnical, cognitive, and behavioral theory integration of human–AI interaction.
• Critical and interpretive perspectives on AI-mediated consumption and identity.

Ethics, sustainability and Societal Implications

• Algorithmic discrimination, fairness, and bias in AI-based personalization.
• Privacy, consent, and data protection in AI-facilitated consumer experiences.
• Ethical consumption, sustainability, and accountable AI for global markets.

Methodological and Research Innovations

• AI-augmented research approaches: synthetic data, text/image analysis, and simulations.
• Experimental and ethnographic research on human–AI collaboration.
• AI as marketing and consumer research collaborator.

(references on request)