Statement of problem
Public safety is improved if individual users are able to make informed choices about disclosure of personal information. Privacy calculus is a method for balancing perceived risks and benefits of online transactions (Krasnova et al. 2012; Dinev & Hart 2006). This depends on a categorising risk, but there is no consensus on a risk typology (Rosenblum 2007; Swedlow et al. 2009, p.237; Facebook Inc. 2017; Haynes & Robinson 2015). This research will investigate the nature of risk using empirical data from an analysis of actual user behaviour and sets out to address the following research questions:
- Is there a reliable typology for personal risk that can be used to analyse the privacy calculus that users engage in?
- What is the nature of the interactions and risks that users engage in when they use the Internet?
- Can the new risk typology be applied to existing empirical data to refine the privacy calculus?
- What effect will the new categorisation of risk have?
- Can these figures be used to improve the predictions of user behaviour?
Dinev, T. & Hart, P., 2006. An Extended Privacy Calculus Model for E-Commerce Transactions. Information Systems Research, 17(1), pp.61–80.
Facebook Inc., 2017. Facebook Privacy Basics. Available at: https://www.facebook.com/about/basics [Accessed April 7, 2017].
Haynes, D. & Robinson, L., 2015. Defining User Risk in Social Networking Services. Aslib Journal of Information Management, 67(1), pp.94–115.
Krasnova, H., Veltri, N.F. & Günther, O., 2012. Self-disclosure and Privacy Calculus on Social Networking Sites: The Role of Culture. Business & Information Systems Engineering, 4(3), pp.127–135.
Rosenblum, D., 2007. What Anyone Can Know: the privacy risks of social networking sites. IEEE Security & Privacy, 5(3), pp.40–49.
Swedlow, B. et al., 2009. Theorizing and Generalizing about Risk Assessment and Regulation through Comparative Nested Analysis of Representative Cases. Law & Policy, 31(2), pp.236–269.