Metacognitive Experience: How AI Recommendations Shape Purchase Intention
Although existing studies have shown that AI recommendation systems have potential in enhancing consumers’ purchase intention, there remains a lack of systematic research. This study aims to explore how the interaction between information presentation formats and AI role types influences consumers’ purchase intention. Based on metacognitive experience theory, two experiments are designed to analyze processing fluency as a mediator and consumers’ AI knowledge as a moderator. The results reveal that the interaction between information presentation format and AI role type significantly affects consumers’ purchase intention, while their separate effects are insignificant. Different from existing studies on separate factors, this study demonstrates that AI interactive marketing performance hinges on the matching of design and role positioning. This study extends the application of the theory of metacognitive experiences in the field of human–AI interaction and provides targeted recommendations for the interface design of AI recommendation systems.
Authors
- Xintao Yu (ORCID: https://orcid.org/0000-0002-4806-8798)
- Qiang Yang (ORCID: https://orcid.org/0000-0002-5373-1566)
- Qing Gu (ORCID: https://orcid.org/0000-0002-5948-4690)
- Ding Yuan (ORCID: https://orcid.org/0000-0001-8107-7218)
Institutions
- Nanjing Audit University (CN)
- Liaoning University of Technology (CN)
- Chongqing University of Arts and Sciences (CN)
Publication Details
- Journal
- Journal of theoretical and applied electronic commerce research
- Published
- 2026-06-09
- DOI
- https://doi.org/10.3390/jtaer21060183
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00