Our new paper was recently accepted to Computers in Human Behavior! The paper, led by group member Ron Hirschprung, with Eran Toch, group member Frank Bolton, and Prof. Oded Maimon, aims to estimate people’s value of privacy through an iterative process that helps users to better fine-tune their privacy value. Here is the abstract (note – before the camera-ready version):

In many types of information systems, users face an implicit tradeoff between disclosing personal information and receiving benefits, such as discounts by an electronic commerce service. While these benefits are relatively measurable, the value of privacy involved in disclosing the information is much less tangible, making it hard to design and evaluate information systems that manage personal information. Meanwhile, existing methods to assess and measure the value of privacy, such as self-reported questionnaires, are notoriously unpredictive of real–world behavior. To overcome this obstacle, we propose a methodology called VOPE (Value of Privacy Estimator), which relies on behavioral economics’ Prospect Theory (Kahneman & Tversky, 1979) and valuates people’s privacy preferences in information disclosure scenarios. VOPE is based on an iterative and responsive experiment in which users take or leave a transaction that includes a component of information disclosure. To evaluate the method, we conduct an empirical experiment (n=195), estimating people’s privacy valuations in electronic commerce transactions given different configurations of the tested transaction. We report on the convergence of estimations and validate our results by comparing the values to theoretical projections, to existing results (Tsai et al., 2011), and to another independent experiment that required participants to rank the sensitivity of information disclosure transactions. Finally, we discuss how information systems designers and regulators can use VOPE to create and to oversee systems that balance privacy and utility.