Revealing the resistance of virtual streamers: intrusiveness, privacy disclosure and perceived justice
Purpose Faced with the challenges of rapidly evolving business environments, practitioners in live streaming commerce are increasingly integrating virtual technologies (i.e. virtual streamers) into their digital transformation strategies. Although virtual streamers are anticipated to experience substantial growth, they continue to face significant challenges, particularly due to consumer reluctance and resistance to adoption. Hence, this study focuses on exploring resistance to virtual streamers by examining it through the lens of perceived justice, intrusiveness and privacy disclosure risks in live streaming commerce. Design/methodology/approach An online survey was administered to examine consumer perceptions of virtual streamers. A total of 303 valid responses were collected and analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN). Findings The findings reveal that perceived justice negatively impacts intrusiveness and privacy disclosure risks, which in turn positively influence consumers’ resistance intention to virtual streamers in live streaming commerce. Originality/value This study enhances the understanding of virtual streamers by employing a perceived justice, intrusiveness and privacy disclosure framework to explain consumer resistance, offering a fresh perspective beyond the traditional technology acceptance paradigm. Additionally, it provides practical insights for addressing and reducing resistance to virtual streamers in live streaming commerce.
Authors
- Jessica Sze Yin Ho (ORCID: https://orcid.org/0000-0003-4005-1542)
- Zhucheng Shao (ORCID: https://orcid.org/0000-0002-2507-9566)
Institutions
- Heriot-Watt University Malaysia (MY)
Publication Details
- Journal
- Asia Pacific Journal of Marketing and Logistics
- Published
- 2025-04-25
- DOI
- https://doi.org/10.1108/apjml-12-2024-1895
- Citations
- 4
- Primary Topic
- Privacy, Security, and Data Protection
- Type
- article
- Field-Weighted Citation Impact
- 16.81