Online privacy-related predictors of Facebook usage intensity

Abstract

PurposeThe paper aims to assess which aspects of online privacy concern and reported privacy behavior predict Facebook usage intensity. Design/methodology/approachThe data were obtained by collecting 598 surveys via a non-probability, convenience sampling method. A logistic regression was conducted to predict high and low Facebook usage intensity with regard to online privacy-related attributes. FindingsThe findings indicated that only five of the 16 online privacy-related items predicted Facebook usage intensity. The top three items related mainly to the control of online privacy. Research limitations/implicationsThe results of the study identify the most important privacy concern and privacy behavior aspects that Facebook should take note of. The significant predictors of Facebook usage intensity could provide insight into those privacy attributes, which are the most critical to address, when considering the continuous evolution of the online privacy model for Facebook. Originality/valueThe uses-and-gratification theory and the third-person theory provide a framework for understanding and describing the empirical results – by referring to the tension experienced between online privacy concerns and online privacy behavior. The value of this study lies in the identification of the online privacy-related attributes that significantly predict Facebook usage intensity.