Document Type
Article
Publication Date
2019
Abstract
Understanding individual threat avoidance motivation and behavior is a critical component in designing effective cyber security solutions for both users and organizations. Technology threat avoidance theory (TTAT) asserts that individuals’ perceptions regarding their susceptibility to and the resulting severity of technology threats influence their awareness of the threats, which, in turn, influences their motivation and behavior to avoid them. While TTAT provides cogently and logically explains individuals’ technology threat motivations and behaviors, empirical tests have produced equivocal results particularly in terms of the influence of susceptibility and severity on threat perceptions. Due to these inconsistencies in the threat calculus involving susceptibility, severity, and threat, we need more work to improve and understand individual threat motivations. Additionally, TTAT does not account for individual differences such as risk propensity, distrust propensity, and impulsivity that have been shown to affect cyber security behavior. To address these gaps, we present an empirical assessment of a refined TTAT model, which includes individual differences and models the influence of susceptibility on threat perceptions as partially mediated by severity. Results indicate that, while perceived susceptibility is a significant predictor of threat perceptions, severity perceptions partially mediates its effect. Our results also support the inclusion of risk propensity and distrust propensity in the TTAT model as personal characteristics that significantly affect overall threat perceptions.
DOI
10.17705/1CAIS.04422
Publisher
Association for Information Systems
Repository Citation
Carpenter, D., Young, D. K., Barrett, P., & McLeod, A. J. (2019). Refining technology threat avoidance theory. Communications of the Association for Information Systems, 44. https://doi.org/10.17705/1CAIS.04422
Publication Information
Communications of the Association for Information Systems