The role of social community in influencing purchase intention in live-streaming E-commerce: a social learning theory perspective
Purpose Live-streaming platforms emphasize dynamic social interaction and fan engagement. Users integrate into the live-streaming community through continuous social learning activities, such as sending bullet comments, reviewing comments and interacting with celebrities. However, comprehensive research on the transactional intricacies of live-streaming e-commerce from the perspectives of community and learning is still lacking. Design/methodology/approach Focusing on the behavior characteristics of the reference group represented by online celebrities and fans in the live-streaming environment, this study utilized social learning as the theoretical basis to examine how reference groups affect consumer purchase intention through a series of intermediary effects. An empirical investigation and machine learning algorithms were utilized to explore and verify the hypothesized model. Findings The results show that: (1) reference groups’ behavior positively stimulated social presence and enhanced consumer purchase intention through the chain-mediating effect of social presence and trust in online celebrities; (2) celebrity characteristics (professionalism, attractiveness and interactivity) positively impacted consumer trust; (3) in addition, machine learning algorithms substantiated that reference groups’ behavior, social presence, trust and celebrity characteristics had a remarkably robust predictive effect on purchase intention. Originality/value These findings hold theoretical implications for understanding how the social community affects consumers’ purchase intention in the live-streaming context and practical significance for marketing strategies toward live-streaming e-commerce.
Authors
- Sihua Xu (ORCID: https://orcid.org/0000-0002-4228-2830)
- Bingfeng Bai (ORCID: https://orcid.org/0000-0003-3551-2738)
- Yin Yuan
Institutions
- Shanghai International Studies University (CN)
- Jinling Institute of Technology (CN)
Publication Details
- Journal
- Marketing Intelligence & Planning
- Published
- 2025-01-10
- DOI
- https://doi.org/10.1108/mip-03-2024-0141
- Citations
- 12
- Primary Topic
- Technology Adoption and User Behaviour
- Type
- article
- Field-Weighted Citation Impact
- 50.03