AIS Transactions on Human-Computer Interaction
Abstract
For business-to-consumer (B2C) electronic-commerce (ecommerce) transactions to work, website users must disclose sensitive information (such as credit card information). To establish a long-term customer relationship, organizations desire further information about current and potential customers (e.g., their name, user preferences, product preferences, physical address, and email address). Both ecommerce literature and interpersonal relationship research indicate that self-disclosure is a key dependent variable in burgeoning long-term relationships. In this study, I use a survey methodology (N = 281) and tests key antecedents that the ecommerce B2C relationship stage theory proposes as they relate to self-disclosure. This research model identifies the following antecedents of self-disclosure: attraction, perceived rewards, switching cost, involvement, and trust. Survey results show that trust and perceived rewards explain significant amounts of variance in self-disclosure intention in an online B2C context. I discuss implications for both practice and theory with the results.
DOI
10.17705/1thci.00112
Recommended Citation
Campbell, D. E.
(2019).
A Relational Build-up Model of Consumer Intention to Self-disclose Personal Information in E-commerce B2C Relationships.
AIS Transactions on Human-Computer Interaction, 11(1), 33-53.
https://doi.org/10.17705/1thci.00112
DOI: 10.17705/1thci.00112
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