Familiarity with Big Data, Privacy Concerns, and Self-disclosure Accuracy in Social Networking Websites: An APCO Model

摘要

Social networking websites have not only become the most prevalent communication tools in today’s digital age but also one of the top big data sources. Big data advocates promote the promising benefits of big data applications to both users and practitioners. However, public polls show evidence of heightened privacy concerns among Internet and social media users. We review the privacy literature based on protection motivation theory and the theory of planned behavior to develop an APCO model that incorporates novel factors that reflect users’ familiarity with big data. Our results, which we obtained from using a cross-sectional survey design and structural equation modeling (SEM) techniques, support most of our proposed hypotheses. Specifically, we found that that awareness of big data had a negative impact on and awareness of big data implications had a positive impact on privacy concerns. In turn, privacy concerns impacted self-disclosure concerns positively and self-disclosure accuracy negatively. We also considered other antecedents of privacy concerns and tested other alternative models to examine the mediating role of privacy concerns, to control for demographic variables, and to investigate different roles of the trust construct. Finally, we discuss the results of our findings and the theoretical and practical implications.Recommended Citation Alashoor, Tawfiq; Han, Sehee; and Joseph, Rhoda C. (2017) "Familiarity with Big Data, Privacy Concerns, and Self-disclosure Accuracy in Social Networking Websites: An APCO Model," Communications of the Association for Information Systems