Online privacy-related predictors of Facebook usage intensity

The paper aims to assess which aspects of online privacy concern and reported privacy behavior predict Facebook usage intensity. The 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. The 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. The 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. The 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. •Predicts high/low Facebook usage intensity of online privacy concern and behavior.•Framework of uses-and-gratifications theory and third-person theory.•Results identify the most important privacy concern and behavior aspects for Facebook.•Loss of privacy control is strongest predictor of Facebook usage intensity.•Results can assist Facebook to focus on relevant concern and behavior changes.