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Conference proceeding
Privacy as a Planned Behavior: Effects of Situational Factors on Privacy Perceptions and Plans
Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, pp 169-178
21 Jun 2021
Abstract
To account for privacy perceptions and preferences in user models and develop personalized privacy systems, we need to understand how users make privacy decisions in various contexts. Existing studies of privacy perceptions and behavior focus on overall tendencies toward privacy, but few have examined the context-specific factors in privacy decision making. We conducted a survey on Mechanical Turk (N=401) based on the theory of planned behavior (TPB) to measure the way users’ perceptions of privacy factors and intent to disclose information are affected by three situational factors embodied hypothetical scenarios: information type, recipients’ role, and trust source. Results showed a positive relationship between subjective norms and perceived behavioral control, and between each of these and situational privacy attitude; all three constructs are significantly positively associated with intent to disclose. These findings also suggest that, situational factors predict participants’ privacy decisions through their influence on the TPB constructs.
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13 citations in Scopus
Details
- Title
- Privacy as a Planned Behavior: Effects of Situational Factors on Privacy Perceptions and Plans
- Creators
- A. K. M. Nuhil Mehdy - Boise State UniversityMichael D. Ekstrand - Boise State UniversityBart P. Knijnenburg - Clemson UniversityHoda Mehrpouyan - Boise State University
- Contributors
- Judith Masthoff (Editor) - Utrecht UniversityEelco Herder (Editor) - Radboud University, The NetherlandsNava Tintarev (Editor) - University of Maastricht, The NetherlandsMarko Tkalčič (Editor) - University of Primorska
- Publication Details
- Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, pp 169-178
- Conference
- UMAP '21: 29th ACM Conference on User Modeling, Adaptation and Personalization, 29th (2021)
- Series
- ACM Conferences
- Publisher
- ACM
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Scopus ID
- 2-s2.0-85109493167
- Other Identifier
- 991021868092204721