Exploring user resistance to self-disclosure in social commerce: the effects of privacy and social value
Purpose Encouraging social commerce users to self-disclose in the post-purchase stage becomes essential for platforms to enhance user stickiness and promote transactions. However, the privacy-related issues may yield user resistance. Drawing on restricted access/limited control (RALC) theories of privacy, this study investigates the impact of privacy and social value on user resistance to self-disclosure in the social commerce community. Design/methodology/approach This study integrated four privacy-related variables, social value and user resistance into one model. An online survey was conducted, and partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses and research questions. Findings The findings identified the role of privacy-related variables as user resistance antecedents. Importantly, privacy literacy significantly strengthened the negative relationship between social value and user resistance. The negative relationship between social value and user resistance was more salient among users with better privacy literacy. Additional analysis showed that different dimensions of perceived privacy policy have dissimilar impacts on privacy concerns and control. Surprisingly, among the five dimensions of perceived privacy policy, enforcement was the only significant element that addressed user resistance. Originality/value This study develops and validates a theoretical model to deepen our understanding of the complex factors driving self-disclosure resistance. It also offers practical insights for platforms to reduce user resistance through improved policies and enhanced social value.
Authors
- Lianshan Zhang (ORCID: https://orcid.org/0000-0002-5309-9281)
- Shuoshuo Li (ORCID: https://orcid.org/0009-0009-2666-9953)
- Junjun Li
Institutions
- Shanghai Jiao Tong University (CN)
Publication Details
- Journal
- Online Information Review
- Published
- 2025-06-19
- DOI
- https://doi.org/10.1108/oir-11-2024-0708
- Citations
- 1
- Primary Topic
- Privacy, Security, and Data Protection
- Type
- article
- Field-Weighted Citation Impact
- 4.20