Selection or Rejection? The Role of Agent Type and Information Presentation in AI-Driven Recommendations for Older Consumers

Older consumers in China increasingly engage in online shopping but often struggle with complex purchase process due to age-related cognitive declines and limited digital literacy. Yet, little is known about how AI recommendation strategy (selection vs. rejection) and information presentation modes jointly shape older consumers’ decision-making in the AI-based decision environments. Drawing on three experimental studies, the results consistently find that AI agents are more effective in enhancing seniors’ decision certainty and behavioral intentions when adopting rejection rather than selection strategies, particularly under structured (vs. unstructured) information presentations. Both static and dynamic presentation modes interact with recommendation strategies to shape evaluation processes, reduce cognitive load, and amplify the impact of AI-based recommendations on seniors’ decision outcomes. The findings contribute to research on human-AI interaction and offer practical guidance for designing age-friendly AI recommendation systems in digital marketplaces.