CCE Theses and Dissertations

Date of Award


Document Type


Degree Name

Doctor of Philosophy in Information Systems (DISS)


Graduate School of Computer and Information Sciences


Easwar Nyshadham

Committee Member

Souren Paul

Committee Member

Gerry Van Loon


Information technology, Quantitative psychology and psychometrics, Affect, Behavioral Intentions, Feeling, Implicit Attitudes, Privacy Behaviors, Privacy Concerns


The purpose of this study was to investigate the influence of affect on privacy concerns and privacy behaviors. A considerable amount of research in the information systems field argues that privacy concerns, usually conceptualized as an evaluation of privacy risks, influence privacy behaviors. However, recent theoretical work shows that affect, a pre-cognitive evaluation, has a significant effect on preferences and choices in risky situations. Affect is contrasted with cognitive issues in privacy decision making and the role of affective versus cognitive-consequentialist factors is reviewed in privacy context.

A causal model was developed to address how affect influences privacy concerns and privacy behaviors. The model of privacy risk proposed in this model argues that affect (or “feelings”) influences privacy behaviors directly as well as thru privacy concerns.

To test the model, subjects were recruited using Mechanical Turk and paid for their participation. Affect, the key construct in this research, was measured using a word association technique as well as methods developed in the implicit attitudes research. Well-known scales were used to measure privacy concerns and behavioral intentions. Data was collected from subjects using a pretested privacy scenario.

Data analysis suggests that, in line with published IS research, privacy concerns affect privacy behaviors. Affect has no impact on privacy concerns nor on privacy behaviors at the traditional 5% level of significance, though it is significant at the 10% level of significance. Improving the instruments used to measure affect, use of a large sample size to detect small effect sizes and more control over the instrument administration instead of an online survey are suggested for future research.